CN115097885A - A kind of automatic control method and system for fruit ripening - Google Patents

Abstract

The invention relates to an automatic regulation and control method and system for fruit ripening, wherein the method comprises the following steps: classifying the types and the maturity of fruits to be processed according to a preset knowledge base, and determining ripening accelerating parameters of the classified fruits to be processed according to the knowledge base and preset market demands; setting a ripening environment according to ripening parameters, ripening fruits to be processed according to the ripening environment, and collecting a ripeness signal of the fruits to be processed, a temperature and humidity signal of the ripening environment and a micro-gas concentration signal in the ripening process; determining a fruit maturity threshold of the fruit to be processed in the ripening process according to the maturity signal; and adjusting the ripening environment and the air-conditioned environment according to the fruit ripening degree threshold and the delivery condition so as to realize the self-adaptive dynamic adjustment of the ripening process of the fruits to be treated. The fruit ripening method can improve the ripening quality of the fruits and reduce the fruit loss and energy waste.

Description

A kind of automatic control method and system for fruit ripening

technical field

The invention relates to the technical field of fruit processing, in particular to an automatic control method and system for fruit ripening.

Background technique

The post-ripening fruit has a very short storage period under the condition of full maturity, so it is generally picked in the period when the maturity is not high. However, at this time, the fruit has high firmness and low soluble solid content, and cannot be eaten directly. It needs to be naturally ripened or ripened to achieve an edible state. However, the spontaneous ripening of fruit has problems such as long ripening time and bad taste, which brings inconvenience to consumers. Therefore, it is very important to carry out post-harvest ripening for peeled and edible post-ripening fruits. Today's ripening technology is mainly based on temperature control, which is an indispensable link in the post-ripening fruit supply chain.

In the prior art, in order to improve the ripening efficiency, a large amount of fruit is usually ripened by using a ripening warehouse. Put the ethylene generator into the warehouse and set its working time to be about 10 hours. After the work is finished, the ethylene gas is discharged, and then the temperature is adjusted manually according to the ripening of the fruit to accelerate the ripening of the fruit. During the period, workers need to check the warehouse at least three times a day, and the general ripening cycle is 3-5 days. The regulation of the entire ripening process is mainly judged manually. However, due to the limited energy of labor, most of them choose random inspections, which cannot represent the overall maturity status of fruits, and the opening and closing of the warehouse will change the ripening environment, resulting in waste of energy and loss of fruit.

SUMMARY OF THE INVENTION

In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide an automatic control method and system for fruit ripening.

For achieving the above object, the present invention provides the following scheme:

An automatic control method for fruit ripening, comprising:

The types and maturity of the fruits to be processed are classified according to the preset knowledge base, and the ripening parameters of the classified fruits to be processed are determined according to the knowledge base and the preset market demand; the ripening parameters include the ripening parameters. Days and ripening environmental parameters; the ripening environmental parameters include temperature and humidity signals and micro-gas concentration signals;

The ripening environment is set according to the ripening parameters, and the fruit to be treated is ripened according to the ripening environment, and the ripeness signal of the fruit to be treated and the ripening environment are collected during the ripening process. The temperature and humidity signal and the micro gas concentration signal;

Determine the fruit maturity threshold of the fruit to be treated in the ripening process according to the maturity signal;

The ripening environment is adjusted according to the fruit maturity threshold, so as to realize dynamic adjustment of the ripening process of the fruit to be processed.

Preferably, the category and maturity of the fruit to be treated are classified according to a preset knowledge base, and the ripening parameters of the classified fruit to be treated are determined according to the knowledge base and preset market demand, including:

Constructing the knowledge base; the knowledge base is used to store the fruit varieties, fruit maturity levels and the ripening environment parameters corresponding to different ripening days;

Use the knowledge base to classify the varieties of the fruits to be treated, and obtain the classified fruits to be treated;

According to the knowledge base, the classification of the ripeness of the fruit to be treated is divided to obtain the ripeness of the classified fruit to be treated;

The ripening days are determined according to the preset market demand, and the ripening environment parameters corresponding to the ripening days are selected from the knowledge base; the temperature and humidity signals include temperature signals and humidity signals; The gas concentration signal includes oxygen concentration signal, carbon dioxide concentration signal and ethylene concentration signal;

The ripening parameters are determined according to the ripening environmental parameters and the ripening days.

Preferably, the collection of the ripeness signal of the fruit to be processed, the temperature and humidity signal of the ripening environment, and the micro-gas concentration signal during the ripening process include:

A maturity acquisition device is arranged above the fruit to be processed; the maturity acquisition device includes a color sensor, a spectral sensor and a sound wave sensor; the maturity signal includes a color signal, a spectral signal and a sound wave signal; the color sensor used to collect the color signal of the fruit to be processed; the spectral sensor is used to collect the spectral signal of the fruit to be processed; the acoustic wave sensor is used to collect the acoustic wave signal of the fruit to be processed;

The temperature and humidity signal and the micro-gas concentration signal are collected by an environmental information acquisition device; the environmental information acquisition device includes a temperature and humidity sensor, an oxygen sensor, a carbon dioxide sensor and an ethylene sensor.

Preferably, the setting method of the maturity collection device includes:

The color sensor, the spectral sensor and the acoustic wave sensor are placed side by side as a sensor array, and three groups of sensor arrays are arranged in total; each group of sensor arrays are placed at equal intervals along the width direction of the warehouse;

Determine the distribution positions of the maturity collection devices according to a first setting formula; the first setting formula is:

Among them, a and b are the width and length of the ripening warehouse, respectively; l is the distance between the first group of sensor arrays, the second group of sensor arrays and the third group of sensor arrays; c1, c2 and c3 are the The collection coverage radius of the color sensor, the coverage radius of the spectral sensor, and the coverage radius of the acoustic wave sensor; c is the minimum coverage radius in the three groups of sensor arrays; x is the sensor array along the ripening warehouse once The distance moved in the length direction, n is the number of times the sensor array moves from the head end to the end along the length direction of the ripening warehouse; h is the vertical distance of the sensor array above the fruit, the change of h and c have a positive correlation;

Dynamically adjust the installation height of the maturity acquisition device according to the actual size of the ripening warehouse;

The sensor array is uniformly moved along the length direction of the ripening warehouse to scan and collect the color signal, the spectral signal and the sound wave signal of the fruit to be processed by column by column.

Preferably, the setting method of the environmental information collection device includes:

Determine the distribution position of the environmental information collection device in the length direction of the ripening warehouse according to the second setting formula; the third setting formula is:

Wherein, a and b are the width and length of the ripening warehouse, respectively; s _i is the mutual distance between the sensor groups, and s is the difference between the distances between two adjacent sensor groups in the length direction of the ripening warehouse; n _y is the number of sensor groups in the length direction of the ripening warehouse; ε is a calculation parameter;

Determine the distribution position of the environmental information collection device in the width direction of the ripening warehouse according to the fourth setting formula; the third setting formula is:

Wherein, sx is the mutual distance between the sensors in the width direction of the ripening warehouse; _nx is the number of sensor groups in the width direction of the ripening warehouse; c4, c5, c6, c7 and c8 are the temperature and humidity, respectively The collection coverage radius of the temperature sensing unit of the sensor, the humidity sensing unit of the temperature and humidity sensor, the oxygen sensor, the carbon dioxide sensor and the ethylene sensor;

The environmental information collection devices are arranged according to the distribution positions of the environmental information collection devices in the length direction of the ripening warehouse and the distribution positions of the environmental information collection devices in the width direction of the ripening warehouse.

Preferably, determining the fruit maturity threshold of the fruit to be treated in the ripening process according to the maturity signal, including:

According to the knowledge base, the fruit is divided into ripeness grades to obtain multiple grades;

For the fruits corresponding to each grade, the maturity signals of different sensors at three different positions are collected respectively, and the signal vectors of each grade are constructed according to the maturity signals;

establishing a first maturity classifier based on color features, a second maturity classifier based on spectral features, and a third maturity classifier based on sonic features;

inputting the color feature signal in the signal vector into the first maturity classifier to obtain a first maturity threshold;

inputting the spectral characteristic signal in the signal vector into the second maturity classifier to obtain a second maturity threshold;

inputting the acoustic wave characteristic signal in the signal vector into the third maturity classifier to obtain a third maturity threshold;

The fruit maturity threshold is determined based on the first maturity threshold, the second maturity threshold and the third maturity threshold.

Preferably, the adjustment of the ripening environment according to the fruit maturity threshold to realize the dynamic adjustment of the ripening process of the fruit to be processed includes:

Carry out coupled modeling according to the fruit maturity threshold and preset controllable environmental factors to obtain a regression curve of the controllable factors; the expression of the regression curve is:

Wherein, CF represents the set of controllable environmental factors, RP is the fruit maturity threshold, t is the ripening time, T is the preset ripening time period, [[f ₁ , g ₁ ], [f ₂ ,g ₂ ],[f ₃ ,g ₃ ],[f ₄ ,g ₄ ],[f ₅ ,g ₅ ]] are the functions corresponding to temperature, humidity and oxygen, respectively relationship, the functional relationship corresponding to carbon dioxide, and the functional relationship corresponding to ethylene; Y1, Y2, Y3, Y4 and Y5 are the temperature value, humidity value, oxygen concentration, carbon dioxide concentration and ethylene concentration calculated according to the regression curve respectively; R ₁ , R ₂ and R ₃ are the first maturity threshold, the second maturity threshold and the third maturity threshold respectively; w ₁ , w ₂ and w ₃ are the collected color signal and spectral signal respectively The weight of the sound wave signal in the classification of fruit ripeness grades;

The parameters of the ripening environment are adjusted according to the regression curve.

Preferably, after collecting the ripeness signal of the fruit to be processed, the temperature and humidity signal and the micro gas concentration signal of the ripening environment during the ripening process, the method further includes:

Signal the color signal, the spectral signal, the acoustic wave signal, the signal collected by the temperature and humidity sensor, the signal collected by the oxygen sensor, the signal collected by the carbon dioxide sensor, and the signal collected by the ethylene sensor processing; the formula for the signal processing is:

Wherein, VT is the temperature value of the signal collected by the temperature and humidity sensor, VH is the humidity value of the signal collected by the temperature and humidity sensor, VO is the oxygen concentration value of the signal collected by the oxygen sensor, and VCO is the carbon dioxide sensor. The carbon dioxide concentration value of the collected signal, VCH is the ethylene concentration value of the signal collected by the ethylene sensor; α, β, γ, λ are weight parameters; VT _1i , VT _2i , VT _3i , VT _4i are the values of the Temperature value; VH _1i , VH _2i , VH _3i , VH _4i are the humidity values of each area respectively; VO ₁ , VO ₂ , VO ₃ , VO ₄ are the oxygen concentration of each area respectively; VCO ₁ , VCO ₂ , VCO ₃ , VCO ₄ is the carbon dioxide concentration in each area; VCH ₁ , VCH ₂ , VCH ₃ , VCH ₄ are the ethylene concentration in each area, respectively; a _i , bi , c _i , d _i are the proportional parameters occupied by each interference signal _, respectively .

Preferably, the adjustment of the parameters of the ripening environment according to the regression curve includes:

Calculate the ripeness threshold of the fruit under the current environment according to the functional relationship corresponding to the temperature and the ripeness classifier and obtain the target temperature, and adjust the ripening environment temperature according to the ripeness threshold of the fruit and the target temperature;

Calculate the maturity threshold of the fruit under the current environment according to the functional relationship corresponding to the humidity and the maturity classifier and obtain the target humidity, and adjust the humidity according to the maturity threshold of the fruit and the target humidity;

Calculate the maturity threshold of the fruit under the current environment according to the functional relationship corresponding to the oxygen and the maturity classifier to obtain the target oxygen concentration, and adjust the oxygen concentration according to the fruit maturity threshold and the target oxygen concentration;

Calculate the maturity threshold of the fruit under the current environment according to the functional relationship corresponding to carbon dioxide and the maturity classifier to obtain the target carbon dioxide concentration, and adjust the carbon dioxide concentration according to the fruit maturity threshold and the target carbon dioxide concentration;

According to the functional relationship corresponding to the ethylene and the maturity classifier, the maturity threshold of the fruit under the current environment is calculated and the target ethylene concentration is obtained, and the ethylene concentration is adjusted according to the fruit maturity threshold and the target ethylene concentration.

An automatic control system for fruit ripening, comprising:

A knowledge base classification unit, configured to classify the type and maturity of the fruit to be processed according to the preset knowledge base, and determine the ripening parameters of the classified fruit to be processed according to the knowledge base and the preset market demand; Described ripening parameter includes ripening days and ripening environment parameter; Described ripening environment parameter includes temperature and humidity signal and micro gas concentration signal;

A signal acquisition unit, configured to set a ripening environment according to the ripening parameters, and to ripen the fruit to be processed according to the ripening environment, and collect the ripeness signal of the fruit to be processed during the ripening process , the temperature and humidity signal and the micro gas concentration signal of the ripening environment;

Threshold calculation unit, for determining the fruit maturity threshold of the fruit to be treated in the ripening process according to the maturity signal;

An adjustment unit, configured to adjust the ripening environment and the modified atmosphere environment according to the fruit maturity threshold and the storage situation, so as to realize adaptive dynamic adjustment of the ripening process of the fruit to be processed.

According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

The present invention provides an automatic control method and system for fruit ripening, wherein the method includes: classifying the type and maturity of the fruit to be processed according to a preset knowledge base, and according to the knowledge base and preset market demand Determine the ripening parameters of the classified fruits to be treated; the ripening parameters include the ripening days and the ripening environment parameters; the ripening environment parameters include temperature and humidity signals and micro-gas concentration signals; according to the ripening Parameter setting the ripening environment, and ripening the fruit to be treated according to the ripening environment, and collect the ripeness signal of the fruit to be treated, the temperature and humidity of the ripening environment during the ripening process signal and the micro gas concentration signal; determine the fruit maturity threshold of the fruit to be treated in the ripening process according to the maturity signal; adjust the ripening environment according to the fruit maturity threshold to achieve Dynamic adjustment of the ripening process of the fruit to be treated. The invention can improve the ripening quality of fruits, and can reduce fruit loss and energy waste.

Description of drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings required in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the present invention. In the embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative labor.

Fig. 1 is the method flow chart in the embodiment provided by the present invention;

2 is a schematic structural diagram of a system module in an embodiment provided by the present invention;

FIG. 3 is a detailed schematic flowchart of an embodiment provided by the present invention.

FIG. 4 is a connection diagram of system units in an embodiment provided by the present invention.

Fig. 5 is the comparison diagram of the hardness result of the traditional method in the embodiment provided by the present invention and this method;

Fig. 6 is the traditional method in the embodiment provided by the present invention and the comparison diagram of the adhesion degree result of this method;

Fig. 7 is the comparison chart of the chewiness result of the traditional method in the embodiment provided by the present invention and this method;

FIG. 8 is a comparison diagram of the recovery results between the traditional method in the embodiment provided by the present invention and the present method.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the present application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor a separate or alternative embodiment that is mutually exclusive of other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

The terms "first", "second", "third" and "fourth" in the description and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order . Furthermore, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, including a series of steps, processes, methods, etc. is not limited to the listed steps, but optionally also includes unlisted steps, or optionally also includes inherent to these processes, methods, products or devices. other steps.

The purpose of the present invention is to provide an automatic control method and system for fruit ripening, which can improve the quality of fruit ripening and reduce fruit loss and energy waste.

In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

Fig. 1 is the method flow chart in the embodiment provided by the present invention, as shown in Fig. 1, the present invention provides a kind of automatic control method for fruit ripening, comprising:

Step 100: classify the types and maturity of the fruits to be processed according to a preset knowledge base, and determine the ripening parameters of the classified fruits to be processed according to the knowledge base and preset market demands; the ripening parameters Including ripening days and ripening environmental parameters; the ripening environmental parameters include temperature and humidity signals and micro-gas concentration signals;

Step 200: Set a ripening environment according to the ripening parameters, and ripen the fruit to be treated according to the ripening environment, and collect the ripeness signal of the fruit to be treated, the the temperature and humidity signal and the micro gas concentration signal of the ripening environment;

Step 300: determine the fruit maturity threshold of the fruit to be treated in the ripening process according to the maturity signal;

Step 400: Adjust the ripening environment according to the fruit maturity threshold, so as to realize adaptive dynamic adjustment of the ripening process of the fruit to be processed.

Further, another implementation manner of the control method provided in this embodiment is as follows:

Collect the ripeness signal of the fruit during the ripening process;

Collect and automatically adjust the temperature, humidity and micro-gas concentration of the ripening environment;

The fruit ripeness grade is obtained according to the collected ripeness signal, and then the temperature, humidity and micro-gas concentration of the ripening environment are dynamically adjusted.

Preferably, the step 100 specifically includes:

Constructing the knowledge base; the knowledge base is used to store the fruit varieties, fruit maturity levels and the ripening environment parameters corresponding to different ripening days;

Use the knowledge base to classify the varieties of the fruits to be treated, and obtain the classified fruits to be treated;

According to the knowledge base, the classification of the ripeness of the fruit to be treated is divided to obtain the ripeness of the classified fruit to be treated;

The ripening days are determined according to the preset market demand, and the ripening environment parameters corresponding to the ripening days are selected from the knowledge base; the temperature and humidity signals include temperature signals and humidity signals; The gas concentration signal includes oxygen concentration signal, carbon dioxide concentration signal and ethylene concentration signal;

The ripening parameters are determined according to the ripening environmental parameters and the ripening days.

Specifically, this embodiment also corresponds to the above method, and provides a modular control system, as shown in FIG. 2 , including a knowledge base module, a pre-classification module, a maturity information collection module, an environmental information collection and processing module, a mature Degree and controllable factors coupling model module, control display module, outbound module.

Wherein, the knowledge base module is used to store fruit varieties and fruit maturity grades, as well as ripening environment parameters corresponding to different ripening days. The pre-classification module is used to classify the arriving fruit varieties and perform primary classification of their maturity according to the existing knowledge. The maturity information collection and processing module is used to collect the color signal, spectral signal and sound wave signal in the fruit ripening process, and then pass through the maturity threshold conversion module (the first maturity classifier, the second maturity classifier, the first maturity Three ripeness classifiers) to obtain the ripeness thresholds of fruits under different collection methods. The environmental information collection and processing module is used to collect signals generated by temperature and humidity sensors, oxygen sensors, carbon dioxide sensors, and ethylene sensors in the ripening environment, and perform fusion and conflict processing on the signals to obtain the temperature, humidity, and oxygen concentration in the ripening process. , carbon dioxide concentration and the actual value of ethylene concentration, and transmit the data to the adjustment display module. The maturity and controllable factor coupling module is used to couple the maturity information processed by the maturity information acquisition and processing module with the controllable environmental factors adjusted in the worker's experience, and obtain the regression of the environmental controllable factors. curve, the control center automatically adjusts the environmental controllable factors according to this regression curve during the ripening process. The control and display module includes a temperature increase and decrease module, a humidity addition and deduction module, a carbon dioxide adsorption module, an oxygen application module, an ethylene adsorption module, a display module, and a manual correction module, which are used to automatically regulate the temperature and humidity in the ripening environment and the gas concentration. , and display the value. In order to increase its stability, a manual correction module is added to dynamically fine-tune the possible deviation of the regression curve, so as to realize the self-adaptive adjustment of the entire ripening process. The outgoing module includes a sales module and an air conditioning module. It is used to carry out the fruit that meets the maturity requirements. If it cannot be sold immediately, it will be transferred to the modified atmosphere module for preservation.

Further, in the present embodiment, the fruit varieties that are about to be ripened are classified by the knowledge base module, and their maturity levels are preliminarily divided; The initial value of ripening environment parameters: temperature and humidity, oxygen concentration, carbon dioxide concentration, ethylene concentration.

Preferably, the step 200 specifically includes:

A maturity acquisition device is arranged above the fruit to be processed; the maturity acquisition device includes a color sensor, a spectral sensor and a sound wave sensor; the maturity signal includes a color signal, a spectral signal and a sound wave signal; the color sensor used to collect the color signal of the fruit to be processed; the spectral sensor is used to collect the spectral signal of the fruit to be processed; the acoustic wave sensor is used to collect the acoustic wave signal of the fruit to be processed;

The temperature and humidity signal and the micro-gas concentration signal are collected by an environmental information acquisition device; the environmental information acquisition device includes a temperature and humidity sensor, an oxygen sensor, a carbon dioxide sensor and an ethylene sensor.

Specifically, in this embodiment, the ripeness information collection and processing module is used to detect the color change, spectral change and sound wave change during the ripening process of the fruit, and the ripeness threshold conversion processing is performed on these three signals, and then transmitted to the ripeness and controllable Factor coupling module.

Preferably, the setting method of the maturity collection device includes:

The color sensor, the spectral sensor and the acoustic wave sensor are placed side by side as a sensor array, and three groups of sensor arrays are arranged in total; each group of sensor arrays are placed at equal intervals along the width direction of the warehouse;

Determine the distribution positions of the maturity collection devices according to a first setting formula; the first setting formula is:

Among them, a and b are the width and length of the ripening warehouse, respectively; l is the distance between the first group of sensor arrays, the second group of sensor arrays and the third group of sensor arrays; c1, c2 and c3 are the The collection coverage radius of the color sensor, the coverage radius of the spectral sensor, and the coverage radius of the acoustic wave sensor; c is the minimum coverage radius in the three groups of sensor arrays; x is the sensor array along the ripening warehouse once The distance moved in the length direction, n is the number of times the sensor array moves from the head end to the end along the length direction of the ripening warehouse; h is the vertical distance of the sensor array above the fruit, the change of h and c have a positive correlation;

Dynamically adjust the installation height of the maturity acquisition device according to the actual size of the ripening warehouse;

The sensor array is uniformly moved along the length direction of the ripening warehouse to scan and collect the color signal, the spectral signal and the sound wave signal of the fruit to be processed by column by column.

Preferably, the setting method of the environmental information collection device includes:

Determine the distribution position of the environmental information collection device in the length direction of the ripening warehouse according to the third setting formula; the third setting formula is:

Wherein, a and b are the width and length of the ripening warehouse, respectively; s _i is the mutual distance between the sensor groups, and s is the difference between the distances between two adjacent sensor groups in the length direction of the ripening warehouse; n _y is the number of sensor groups in the length direction of the ripening warehouse; ε is a calculation parameter;

Determine the distribution position of the environmental information collection device in the width direction of the ripening warehouse according to a fourth setting formula; the fourth setting formula is:

Wherein, sx is the mutual distance between the sensors in the width direction of the ripening warehouse; _nx is the number of sensor groups in the width direction of the ripening warehouse; c4, c5, c6, c7 and c8 are the temperature and humidity, respectively The collection coverage radius of the temperature sensing unit of the sensor, the humidity sensing unit of the temperature and humidity sensor, the oxygen sensor, the carbon dioxide sensor and the ethylene sensor;

The environmental information collection devices are arranged according to the distribution positions of the environmental information collection devices in the length direction of the ripening warehouse and the distribution positions of the environmental information collection devices in the width direction of the ripening warehouse.

Specifically, the maturity acquisition module (color sensor, spectral sensor, acoustic wave sensor) of the present embodiment is placed above the fruit to initially collect the maturity information of the fruit. The specific installation and collection methods are as follows:

c=min(c1,c2,c3)

nx=b

l≤2c

c∝h

Among them, a and b are the width and length of the ripening warehouse, respectively; l is the distance between groups A, B, and C; c1, c2, and c3 are the collection coverage radius of the color sensor and the coverage of the spectrum sensor, respectively. Radius, the coverage radius of the acoustic wave sensor; c is the minimum coverage radius of the three sensors; x is the distance that the sensor array moves along the length of the warehouse at a time, and n is the sensor array moves along the length of the warehouse from the head end to the end. The number of times; h is the vertical distance of the sensor array above the fruit, which has a positive correlation with the change of c.

According to the actual size of the warehouse, by dynamically adjusting the height of the sensor installation, it is ensured that the three groups of sensors A, B, and C are distributed according to the above method so that their signals can cover the width of the warehouse. Then the three groups of sensors A, B and C are moved evenly along the length of the warehouse to scan and collect the color signal, spectral signal and acoustic wave signal of the fruit column by column, and the collected maturity signal is transmitted to the maturity information acquisition and processing module for the next step. deal with.

Further, a first maturity classifier from the color feature, a second maturity classifier from the spectral feature, and a third maturity classifier from the acoustic wave feature are established through the maturity threshold conversion module, and the collected feature signals are converted into maturity threshold. The specific methods are as follows:

According to the knowledge base, the ripened fruits are divided into seven grades, namely A, B, C, D, E, F, and G. The fruits of each grade collect different sensor signals from three different positions. That is, the signal vector collected by maturity level A is AV=[ax1,ay1,az1,ax2,ay2,az2,ax2,ay2,az2]; the signal vector collected by maturity level B is BV=[bx1,by1, bz1,bx2,by2,bz2,bx2,by2,bz2]; the signal vector collected at maturity C level is CV=[cx1,cy1,cz1,cx2,cy2,cz2,cx3,cy3,cz3]; maturity D The signal vector collected by the level is DV=[dx1,dy1,dz1,dx2,dy2,dz2,dx3,dy3,dz3]; the signal vector collected by the maturity level E is EV=[ex1,ey1,ez1,ex2, ey2, ez2, ex3, ey3, ez3]; the signal vector collected by the maturity level F is FV=[fx1, fy1, fz1, fx2, fy2, fz2, fx3, fy3, fz3]; the signal vector collected by the maturity level G The signal vector is GV=[gx1,gy1,gz1,gx2,gy2,gz2,gx3,gy3,gz3].

Further, the collected signal vectors are trained by establishing a multi-feature vector model for ripening, and cross-validation is performed to obtain a first maturity level classifier, a second maturity level classifier and a third maturity level classifier. The maturity threshold R1 is obtained by inputting the color characteristic signal to the first maturity classifier, the maturity threshold R2 is obtained by inputting the spectral characteristic signal to the second maturity classifier, and the maturity threshold R2 is obtained by inputting the acoustic characteristic signal to the third maturity classifier. The three maturity thresholds are transferred to the maturity and controllable factor coupling model module.

At the same time, the environmental information acquisition module, including temperature and humidity sensors, oxygen sensors, carbon dioxide sensors, ethylene sensors, and signal fusion conflict processing, is used to collect the temperature, humidity and micro-gas concentration in the ripening environment, and transmit the current values to the regulator. Display module. Specifically, the temperature sensor, humidity sensor, oxygen sensor, carbon dioxide sensor, and ethylene sensor are placed side by side as a controllable factor sensor group, and arranged as follows:

In the warehouse length direction, the installation positions of the sensor groups are distributed as follows:

sy _i =syn _+1-i

In the width direction of the warehouse, the installation positions of the sensor groups are distributed as follows:

where a and b are the width and length of the ripening warehouse, respectively; sy _i is the mutual distance between sensor groups in the length direction of the warehouse, s is the difference between the distances between two adjacent sensor groups in the length direction of the warehouse; _ny is the warehouse The number of sensor groups in the length direction; ε is the calculation parameter; sx is the mutual distance between the sensor groups in the warehouse width direction; n _x is the number of sensor groups in the warehouse length direction; c1, c2, c3, c4 and c5 are the acquisition coverage radius of temperature sensor, humidity sensor, oxygen sensor, carbon dioxide sensor and ethylene sensor respectively;

By placing the temperature sensor, humidity sensor, oxygen sensor, carbon dioxide sensor and ethylene sensor in the above manner, the position of the warehouse can be dynamically adjusted according to the actual size of the warehouse, so that the temperature, humidity and temperature during the ripening process can be collected comprehensively. Oxygen, carbon dioxide and ethylene gas concentrations.

Preferably, the step 300 specifically includes:

According to the knowledge base, the fruit is divided into ripeness grades to obtain multiple grades;

For the fruits corresponding to each grade, the maturity signals of different sensors at three different positions are collected respectively, and the signal vectors of each grade are constructed according to the maturity signals;

establishing a first maturity classifier based on color features, a second maturity classifier based on spectral features, and a third maturity classifier based on sonic features;

inputting the color feature signal in the signal vector into the first maturity classifier to obtain a first maturity threshold;

inputting the spectral characteristic signal in the signal vector into the second maturity classifier to obtain a second maturity threshold;

inputting the acoustic wave characteristic signal in the signal vector into the third maturity classifier to obtain a third maturity threshold;

The fruit maturity threshold is determined based on the first maturity threshold, the second maturity threshold and the third maturity threshold.

Optionally, the method described in this embodiment further includes:

Collect the color signals of fruits at different maturity levels and use them as the first training samples to obtain the first maturity classifier;

Collect the spectral signals of fruits at different degrees of maturity and use them as the second training samples to obtain the second maturity classifier;

Collect the sound wave signals of fruits at different degrees of maturity and use them as the third training samples to obtain the third degree of maturity classifier;

According to the three maturity classifiers, the corresponding maturity thresholds under different acquisition signals are calculated.

Preferably, the step 400 specifically includes:

Carry out coupled modeling according to the fruit maturity threshold and preset controllable environmental factors to obtain a regression curve of the controllable factors; the expression of the regression curve is:

Wherein, CF represents the set of controllable environmental factors, RP is the fruit maturity threshold, t is the ripening time, T is the preset ripening time period, [[f ₁ , g ₁ ], [f ₂ ,g ₂ ],[f ₃ ,g ₃ ],[f ₄ ,g ₄ ],[f ₅ ,g ₅ ]] are the functions corresponding to temperature, humidity and oxygen, respectively relationship, the functional relationship corresponding to carbon dioxide, and the functional relationship corresponding to ethylene; Y1, Y2, Y3, Y4 and Y5 are the temperature value, humidity value, oxygen concentration, carbon dioxide concentration and ethylene concentration calculated according to the regression curve respectively; R ₁ , R ₂ and R ₃ are the first maturity threshold, the second maturity threshold and the third maturity threshold respectively; w ₁ , w ₂ and w ₃ are the collected color signal and spectral signal respectively The weight of the sound wave signal in the classification of fruit ripeness grades;

The parameters of the ripening environment are adjusted according to the regression curve.

Further, through the maturity and controllable factor coupling module, the maturity information from the maturity information acquisition and processing module is coupled with the controllable environmental factors (knowledge base) adjusted in the worker's experience, and the controllable factors are obtained. Then, in the process of ripening, the environmental controllable factors are automatically adjusted according to this regression curve. The model relationship between the two can be expressed as:

Among them, CF represents the set of controllable factors, RP is the maturity threshold, t is the ripening time, T is the set ripening time period, [[f ₁ , g ₁ ], [f ₂ , g ₂ ], [ f ₃ , g ₃ ], [f ₄ , g ₄ ], [f ₅ , g ₅ ]] are the functional relationship corresponding to temperature, namely the first regression curve, the functional relationship corresponding to humidity, namely the second regression curve, oxygen The corresponding functional relationship is the third regression curve, the functional relationship corresponding to carbon dioxide is the fourth regression curve, and the functional relationship corresponding to ethylene is the fifth regression curve. Y1, Y2, Y3, Y4, Y5 are the temperature value, humidity value, oxygen concentration, carbon dioxide concentration, and ethylene concentration calculated according to the regression curve, respectively. R1, R2, and R3 are respectively the processed maturity threshold of the collected color signal, the processed threshold of the collected spectral signal, and the processed maturity threshold of the collected acoustic signal. w1, w2, and w3 are the weights of the collected color signal, spectral signal and acoustic signal in the fruit ripeness grade division respectively.

Optionally, according to the obtained first regression curve, the control center calculates the maturity threshold of the fruit under the current environment according to the maturity classifier and obtains the target temperature, and then automatically controls the temperature rise and fall device to adjust the temperature; according to the obtained second regression Curve, the control center calculates the ripeness threshold of the fruit in the current environment according to the maturity classifier and obtains the target humidity, and then automatically controls the atomization device to adjust the humidity; according to the obtained third regression curve, the control center calculates according to the maturity classifier The maturity threshold of the fruit in the current environment is obtained and the target oxygen concentration is obtained. The controller controls the oxygen supply device to adjust the oxygen concentration; according to the obtained fourth regression curve, the control center calculates the maturity threshold of the fruit in the current environment according to the maturity classifier. The target carbon dioxide concentration is obtained, and the carbon dioxide adsorption device is automatically controlled to adjust the carbon dioxide concentration; according to the obtained fifth regression curve, the control center calculates the ripeness threshold of the fruit under the current environment according to the maturity classifier and obtains the target ethylene concentration to control the ethylene concentration. The adsorption unit was used to adjust the ethylene concentration.

Further, the control center judges whether the ripened fruit meets the maturity requirement through the fruit maturity threshold from the maturity information collection and processing module, and if so, judges whether it is sold, if not, then transfers to the modified atmosphere module for freshness preservation. ; If the maturity requirement is not met, the controllable factor value is calculated through the controllable factor regression curve and transmitted to the display module for display. At the same time, the worker can judge whether the current calculated value needs to be corrected, and if necessary, the manually adjusted data Transfer to the maturity and controllable factor coupling module to establish the controllable factor regression curve again. If manual correction is not required, compare whether the calculated value is equal to the actual value of the current environment. Make automatic adjustments. Thereby, the quality of the ripened fruit is improved, and the loss and energy waste of the fruit are reduced.

Preferably, after collecting the ripeness signal of the fruit to be processed, the temperature and humidity signal and the micro gas concentration signal of the ripening environment during the ripening process, the method further includes:

Signal the color signal, the spectral signal, the acoustic wave signal, the signal collected by the temperature and humidity sensor, the signal collected by the oxygen sensor, the signal collected by the carbon dioxide sensor, and the signal collected by the ethylene sensor processing; the formula for the signal processing is:

Wherein, VT is the temperature value of the signal collected by the temperature and humidity sensor, VH is the humidity value of the signal collected by the temperature and humidity sensor, VO is the oxygen concentration value of the signal collected by the oxygen sensor, and VCO is the carbon dioxide sensor. The carbon dioxide concentration value of the collected signal, VCH is the ethylene concentration value of the signal collected by the ethylene sensor; α, β, γ, λ are weight parameters; VT _1i , VT _2i , VT _3i , VT _4i are the values of the Temperature value; VH _1i , VH _2i , VH _3i , VH _4i are the humidity values of each area respectively; VO ₁ , VO ₂ , VO ₃ , VO ₄ are the oxygen concentration of each area respectively; VCO ₁ , VCO ₂ , VCO ₃ , VCO ₄ is the carbon dioxide concentration in each area; VCH ₁ , VCH ₂ , VCH ₃ , VCH ₄ are the ethylene concentration in each area, respectively; a _i , bi , c _i , d _i are the proportional parameters occupied by each interference signal _, respectively .

Further, according to the distribution state of the fruit, the temperature, humidity, oxygen, carbon dioxide and ethylene of the fruit located in the middle of the warehouse will be very different from those at both ends. Therefore, the collected signals need to be processed to achieve the most suitable The purpose of the real situation of the fruit, the processing method is as follows:

VO=α ₃ VO ₁ +β ₃ (VO ₂ -a ₁ VCO ₂ -b ₁ VCH ₂ )+γ ₃ (VO ₃ -c ₁ VCO ₃ -d ₁ VCH ₃ )+λ ₃ VO ₄

VCO=α ₄ VCO ₁ +β ₄ (VCO ₂ -a ₂ VO ₂ -b ₂ VCH ₂ )+γ ₄ (VCO ₃ -c ₂ VO ₃ -d ₂ VCH ₃ )+λ ₄ VCO ₄

VCH=α ₅ VCH ₁ +β ₅ (VCH ₂ -a ₃ VO ₂ -b ₃ VCO ₂ )+γ ₅ (VCH ₃ -c ₃ VO ₃ -d ₃ VCO ₃ )+λ ₅ VCH ₄

Wherein, VT is the temperature value of described fruit ripening environment, VH is the humidity value of described fruit ripening environment, VO is the oxygen concentration of described fruit ripening environment, VCO is the carbon dioxide concentration of described fruit ripening environment, VCH is the ethylene concentration of the fruit ripening environment; α, β, γ, λ are the corresponding weight parameters respectively; VT _1i , VT _2i , VT _3i , VT _4i are the temperature values in each region; VH _1i , VH _2i , VH _3i and VH _4i are the humidity values in each area; VO ₁ , VO ₂ , VO ₃ , and VO ₄ are the oxygen concentrations in each area, respectively; VCO ₁ , VCO ₂ , VCO ₃ , and VCO ₄ are the carbon dioxide in each area, respectively concentration; VCH ₁ , VCH ₂ , VCH ₃ , and VCH ₄ are the ethylene concentrations in each region _, respectively; a _i , _{bi , c i ,} and di are the proportional parameters occupied by each interference signal.

Preferably, the adjustment of the parameters of the ripening environment according to the regression curve includes:

Calculate the ripeness threshold of the fruit under the current environment according to the functional relationship corresponding to the temperature and the ripeness classifier and obtain the target temperature, and adjust the ripening environment temperature according to the ripeness threshold of the fruit and the target temperature;

Calculate the maturity threshold of the fruit under the current environment according to the functional relationship corresponding to the humidity and the maturity classifier and obtain the target humidity, and adjust the humidity according to the maturity threshold of the fruit and the target humidity;

Calculate the maturity threshold of the fruit under the current environment according to the functional relationship corresponding to the oxygen and the maturity classifier to obtain the target oxygen concentration, and adjust the oxygen concentration according to the fruit maturity threshold and the target oxygen concentration;

Calculate the maturity threshold of the fruit under the current environment according to the functional relationship corresponding to carbon dioxide and the maturity classifier to obtain the target carbon dioxide concentration, and adjust the carbon dioxide concentration according to the fruit maturity threshold and the target carbon dioxide concentration;

According to the functional relationship corresponding to the ethylene and the maturity classifier, the maturity threshold of the fruit under the current environment is calculated and the target ethylene concentration is obtained, and the ethylene concentration is adjusted according to the fruit maturity threshold and the target ethylene concentration.

Optionally, the air-conditioning module in this embodiment determines the optimal fresh-keeping gas parameters by performing a series of judgments through the knowledge base. The specific method is that if the ripened fruit cannot be sold immediately, it will enter the modified atmosphere module (automatic, manual or dual mode). The judging rules for outgoing warehouse transfer into controlled atmosphere are as follows:

The steps of air-conditioning fresh-keeping control are as follows:

First, through the knowledge base module, the types of fruits are determined, and different varieties of fruits have different air-conditioning parameters. Through the first judgment rule, it is judged whether the stored fruit releases a large amount of ethylene. If a large amount of ethylene is released, it is further judged whether the current ethylene concentration exceeds the corresponding upper limit of ethylene (according to the knowledge base). Ethylene, then, determine whether the fruit is a climacteric type, if so, you need to reduce the oxygen concentration to hinder its respiration, and also need to determine whether the current carbon dioxide concentration exceeds the maximum upper limit (according to the knowledge base), if it exceeds , it is necessary to adsorb carbon dioxide to avoid carbon dioxide poisoning of fruits. Finally, after setting the gas parameters, adjust the temperature of the cold storage to the best storage temperature of the fruit through the knowledge base. Compared with the traditional method of refrigerating at a low temperature, the method can automatically adjust according to the state of the fruit, which is more pertinent, reduces the loss of the fruit, and prolongs the storage time.

Corresponding to the above method, the present embodiment also provides another automatic control system for fruit ripening, including:

A knowledge base classification unit, configured to classify the type and maturity of the fruit to be processed according to the preset knowledge base, and determine the ripening parameters of the classified fruit to be processed according to the knowledge base and the preset market demand; Described ripening parameter includes ripening days and ripening environment parameter; Described ripening environment parameter includes temperature and humidity signal and micro gas concentration signal;

A signal acquisition unit, configured to set a ripening environment according to the ripening parameters, and to ripen the fruit to be processed according to the ripening environment, and collect the ripeness signal of the fruit to be processed during the ripening process , the temperature and humidity signal and the micro gas concentration signal of the ripening environment;

Threshold calculation unit, for determining the fruit maturity threshold of the fruit to be treated in the ripening process according to the maturity signal;

An adjustment unit, configured to adjust the ripening environment and the modified atmosphere environment according to the fruit maturity threshold and the storage situation, so as to realize adaptive dynamic adjustment of the ripening process of the fruit to be processed.

Further, in order to highlight the advantages of this method over the traditional ripening method, the present embodiment also adds the comparison of the results (hardness, stickiness, chewiness and recovery) after fruit ripening. FIG. 5 to FIG. 8 are comparison diagrams of various results between the traditional method and the present method in the embodiments provided by the present invention, respectively. As shown in Figure 5 to Figure 8, under the same number of days (T1, T2), the four indicators detected by this method are better than the traditional method. Thus, it can be shown that the automatic control method for fruit ripening proposed by the present invention has obvious advantages compared with the traditional ripening method.

The invention provides an automatic control method for fruit ripening. The knowledge base module is used to pre-classify fruit varieties and maturity; the maturity information collection and processing module is used to detect the color change, spectral change and sound wave change during fruit ripening. , carry out maturity threshold conversion processing on these three signals, and transmit them to the maturity and controllable factor coupling module; and through the environmental information collection and processing module, it is used to collect temperature and humidity sensors, oxygen sensors, and carbon dioxide sensors in the ripening environment. , The signal generated by the ethylene sensor, and the fusion and conflict processing of the signal is carried out to obtain the real values of temperature and humidity, oxygen concentration, carbon dioxide concentration and ethylene concentration during the ripening process, and the data is transmitted to the adjustment display module;

Through the maturity and controllable factor coupling module, it is used to couple the maturity information processed by the maturity information acquisition module with the controllable environmental factors adjusted in the worker's experience, and obtain the regression curve of the controllable factors. During the ripening process, the center automatically adjusts the environmental controllable factors according to this regression curve; through the control and display module, it is used to control the temperature, humidity and micro-gas concentration in the ripening environment, and display the values. In order to increase its stability, add The worker correction module can dynamically fine-tune the possible deviation of the regression curve, so as to realize the self-adaptive adjustment of the whole ripening process. Through the outbound module, the fruits that meet the maturity requirements will be sold. If they cannot be sold immediately, they will be transferred to the modified atmosphere module for freshness preservation. The beneficial effects of the present invention are as follows:

The whole process provided by the invention realizes the automation of fruit ripening, and at the same time can optimize the regression curve of environmental controllable factors by self-learning according to the experience of workers, thereby improving the quality of ripening fruit and reducing fruit loss and energy waste.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant part can be referred to the description of the method.

In this paper, specific examples are used to illustrate the principles and implementations of the present invention. The descriptions of the above embodiments are only used to help understand the methods and core ideas of the present invention; meanwhile, for those skilled in the art, according to the present invention There will be changes in the specific implementation and application scope. In conclusion, the contents of this specification should not be construed as limiting the present invention.

Claims (10)

1. An automatic control method for ripening fruits is characterized by comprising the following steps:

classifying the types and the maturity of fruits to be processed according to a preset knowledge base, and determining ripening accelerating parameters of the classified fruits to be processed according to the knowledge base and preset market demands; the ripening parameters comprise ripening days and ripening environment parameters; the ripening environment parameters comprise temperature and humidity signals and micro-gas concentration signals;

setting ripening environment according to the ripening parameters, ripening the fruit to be processed according to the ripening environment, and collecting a ripening degree signal of the fruit to be processed, the temperature and humidity signal of the ripening environment and the micro-gas concentration signal in the ripening process;

determining a fruit maturity threshold of the fruit to be processed in the ripening process according to the maturity signal;

and adjusting the ripening environment according to the fruit ripeness threshold value so as to realize dynamic adjustment of the ripening process of the fruit to be processed.

2. The automatic regulating and controlling method for fruit ripening according to claim 1, wherein the classifying the types and ripeness of the fruits to be processed according to the preset knowledge base and determining the ripening parameters of the classified fruits to be processed according to the knowledge base and the preset market demand comprise:

constructing the knowledge base; the knowledge base is used for storing varieties of fruits, fruit maturity grades and ripening environment parameters corresponding to different ripening days;

classifying varieties of fruits to be processed by utilizing the knowledge base to obtain classified fruits to be processed;

dividing the maturity of the classified fruits to be processed according to the knowledge base to obtain the maturity of the classified fruits to be processed;

determining ripening days according to the preset market demands, and selecting the ripening environment parameters corresponding to the ripening days from the knowledge base; the temperature and humidity signals comprise temperature signals and humidity signals; the micro-gas concentration signals comprise an oxygen concentration signal, a carbon dioxide concentration signal and an ethylene concentration signal;

and determining the ripening parameters according to the ripening environment parameters and the ripening days.

3. The automatic regulating and controlling method for fruit ripening according to claim 1, wherein said collecting of ripeness signals of the fruit to be treated, the temperature and humidity signals of the ripening environment and the micro-gas concentration signals during ripening comprises:

arranging a ripeness collecting device above the fruit to be processed; the maturity acquisition device comprises a color sensor, a spectrum sensor and an acoustic wave sensor; the maturity signal comprises a color signal, a spectral signal and a sound wave signal; the color sensor is used for collecting the color signal of the fruit to be processed; the spectrum sensor is used for collecting the spectrum signal of the fruit to be processed; the acoustic sensor is used for acquiring the acoustic signal of the fruit to be processed;

collecting the temperature and humidity signals and the micro-gas concentration signals by using an environment information collecting device; the environment information acquisition device comprises a temperature and humidity sensor, an oxygen sensor, a carbon dioxide sensor and an ethylene sensor.

4. The automatic regulating and controlling method for fruit ripening according to claim 3, wherein the setting method of the ripeness collecting device comprises:

placing the color sensor, the spectrum sensor and the acoustic wave sensor side by side to serve as sensor arrays, and arranging three groups of sensor arrays; each group of sensor arrays are arranged at equal intervals along the width direction of the storehouse;

determining the distribution positions of the maturity acquisition devices according to a first setting formula; the first setting formula is:

wherein a and b are the width and length of the ripening storehouse respectively; l is the distance between the first group of sensor arrays, the second group of sensor arrays and the third group of sensor arrays; c1, c2 and c3 are the collection coverage radius of the color sensor, the coverage radius of the spectrum sensor and the coverage radius of the sound wave sensor, respectively; c is the minimum coverage radius in the three groups of sensor arrays; x is the distance of the sensor array moving along the length direction of the ripening warehouse once, and n is the number of times the sensor array moves from the head end to the tail end along the length direction of the ripening warehouse; h is the vertical distance of the sensor array above the fruit, and the variation of h and c has positive correlation;

the first setting formula has three-dimensional self-adaptability, the horizontal position distribution is dynamically adjusted according to the actual size of the ripening storehouse shelf, and the height position distribution is dynamically adjusted according to the specification and the placing position of the fruits;

and uniformly moving the sensor array along the length direction of the ripening storehouse to scan and collect the color signals, the spectrum signals and the sound wave signals of the fruits to be processed row by row, so that the comprehensive collection of the fruit ripening information is ensured.

5. An automatic regulating and controlling method for fruit ripening according to claim 3, wherein the setting method of the environmental information collecting device comprises:

determining the distribution position of the environmental information acquisition device in the length direction of the ripening storehouse according to a second setting formula; the second setting formula is:

wherein a and b are the width and length of the ripening storehouse respectively; sy _i The distance between the sensor groups is the mutual distance, and s is the difference value of the distances between two adjacent sensor groups in the length direction of the ripening storehouse; n is a radical of an alkyl radical _y The number of the sensor groups in the length direction of the ripening storehouse is the number of the sensor groups in the length direction of the ripening storehouse; epsilonTo calculate the parameters;

determining the distribution position of the environmental information acquisition device in the width direction of the ripening storehouse according to a third setting formula; the third setting formula is:

wherein sx is the mutual distance between the sensors in the width direction of the ripening warehouse; n is a radical of an alkyl radical _x The number of the sensor groups in the width direction of the ripening storehouse is the number of the sensor groups in the width direction of the ripening storehouse; c4, c5, c6, c7 and c8 are respectively the collection coverage radii of a temperature sensing unit of the temperature and humidity sensor, a humidity sensing unit of the temperature and humidity sensor, the oxygen sensor, the carbon dioxide sensor and the ethylene sensor;

the second setting formula has gas concentration self-applicability (dense inside and dispersed at two ends), and fewer sensors can acquire more information; the third setting formula has the advantages that the type of the sensor is self-adaptive (collection coverage radius), and incomplete gas information collection caused by collection radius change of the sensor is avoided; and arranging the environmental information acquisition devices according to the distribution positions of the environmental information acquisition devices in the length direction of the ripening storehouse and the distribution positions of the environmental information acquisition devices in the width direction of the ripening storehouse.

6. An automatic regulating and controlling method for fruit ripening according to claim 3, wherein said determining a fruit ripeness threshold of said fruit to be treated during ripening from said ripeness signal comprises:

according to the knowledge base, the ripeness grades of the fruits are classified to obtain a plurality of grades;

respectively acquiring maturity signals of different sensors at three different positions aiming at fruits corresponding to each grade, and constructing a signal vector of each grade according to the maturity signals;

establishing a first maturity classifier based on color features, a second maturity classifier based on spectral features and a third maturity classifier based on acoustic features;

inputting color characteristic signals in the signal vector into the first maturity classifier to obtain a first maturity threshold;

inputting the spectral feature signals in the signal vector into the second maturity classifier to obtain a second maturity threshold;

inputting the sound wave characteristic signals in the signal vectors into the third maturity classifier to obtain a third maturity threshold;

determining the fruit maturity threshold as a function of the first maturity threshold, the second maturity threshold, and the third maturity threshold.

7. An automatic regulating and controlling method for fruit ripening according to claim 6, wherein said adjusting the ripening environment according to the fruit ripeness threshold to achieve dynamic adjustment of the ripening process of the fruit to be treated comprises:

performing coupling modeling according to the fruit maturity threshold and preset controllable environmental factors to obtain a regression curve of the controllable factors; the expression of the regression curve is as follows:

wherein CF represents the set of the controllable environmental factors, RP is the fruit maturity threshold, T is ripening time, T is a preset ripening time limit, [ [ f [ ] ₁ ,g ₁ ]，[f ₂ ,g ₂ ]，[f ₃ ,g ₃ ]，[f ₄ ,g ₄ ]，[f ₅ ,g ₅ ]]Respectively a functional relationship corresponding to temperature, a functional relationship corresponding to humidity, a functional relationship corresponding to oxygen, a functional relationship corresponding to carbon dioxide and a functional relationship corresponding to ethylene; y1, Y2, Y3, Y4 and Y5 are respectively temperature value, humidity value, oxygen concentration, II calculated according to regression curveCarbon oxide concentration and ethylene concentration; r ₁ 、R ₂ And R ₃ The first maturity threshold, the second maturity threshold, and the third maturity threshold, respectively; w is a ₁ 、w ₂ And w ₃ Respectively weighing the collected color signals, spectrum signals and sound wave signals in the fruit maturity grade division;

the regression curve has time sequence updating property, f _i ,g _i The dynamic updating is carried out before each ripening, so that the change of various factors can be better adapted; and adjusting the parameters of the ripening environment according to the regression curve.

8. The automatic regulating and controlling method for fruit ripening according to claim 3, wherein after collecting the ripeness signal of the fruit to be treated, the temperature and humidity signal of the ripening environment and the micro-gas concentration signal during the ripening process, further comprising:

processing the color signal, the spectrum signal, the sound wave signal, the signal collected by the temperature and humidity sensor, the signal collected by the oxygen sensor, the signal collected by the carbon dioxide sensor and the signal collected by the ethylene sensor; the formula of the signal processing is as follows:

wherein VT is a temperature value of a signal acquired by the temperature and humidity sensor, VH is a humidity value of a signal acquired by the temperature and humidity sensor, VO is an oxygen concentration value of a signal acquired by the oxygen sensor, VCO is a carbon dioxide concentration value of a signal acquired by the carbon dioxide sensor, and VCH is an ethylene concentration value of a signal acquired by the ethylene sensor; alpha, beta, gamma and lambda are all weight parameters; VT _1i 、VT _2i 、VT _3i 、VT _4i Respectively the temperature value of each area; VH _1i 、VH _2i 、VH _3i 、VH _4i Respectively for each zoneA humidity value; VO (vacuum vapor volume) ₁ 、VO ₂ 、VO ₃ 、VO ₄ The oxygen concentration of each region is respectively; VCO ₁ 、VCO ₂ 、VCO ₃ 、VCO ₄ The carbon dioxide concentration of each region is respectively; VCH ₁ 、VCH ₂ 、VCH ₃ 、VCH ₄ Ethylene concentration for each zone; a is _i 、b _i 、c _i 、d _i Respectively, the ratio parameters of each interference signal.

9. An automatic control method for fruit ripening according to claim 7, wherein said adjusting the parameters of the ripening environment according to the regression curve comprises:

calculating the ripeness threshold of the fruit in the current environment according to the functional relation corresponding to the temperature and the ripeness classifier, obtaining a target temperature, and adjusting the temperature of the ripening environment according to the ripeness threshold of the fruit and the target temperature;

calculating the ripeness threshold of the fruit in the current environment according to the functional relation corresponding to the humidity and the ripeness classifier, obtaining target humidity, and adjusting the humidity according to the ripeness threshold of the fruit and the target humidity;

calculating the ripeness threshold of the fruit under the current environment according to the functional relation corresponding to the oxygen and the ripeness classifier, obtaining a target oxygen concentration, and adjusting the oxygen concentration according to the ripeness threshold of the fruit and the target oxygen concentration;

calculating a maturity threshold of the fruit in the current environment according to a functional relation corresponding to the carbon dioxide and a maturity classifier, obtaining a target carbon dioxide concentration, and adjusting the carbon dioxide concentration according to the maturity threshold of the fruit and the target carbon dioxide concentration;

and calculating the maturity threshold of the fruit under the current environment according to the functional relation corresponding to the ethylene and the maturity classifier to obtain a target ethylene concentration, and adjusting the ethylene concentration according to the maturity threshold of the fruit and the target ethylene concentration.

10. An automatic regulation and control system for fruit ripening, comprising:

the knowledge base classification unit is used for classifying the types and the maturity of the fruits to be processed according to a preset knowledge base and determining the ripening accelerating parameters of the classified fruits to be processed according to the knowledge base and preset market demands; the ripening parameters comprise ripening days and ripening environment parameters; the ripening environment parameters comprise temperature and humidity signals and micro-gas concentration signals;

the signal acquisition unit is used for setting a ripening environment according to the ripening parameters, ripening the fruit to be processed according to the ripening environment, and acquiring a ripeness signal of the fruit to be processed, the temperature and humidity signal of the ripening environment and the micro-gas concentration signal in the ripening process;

the threshold value calculating unit is used for determining a fruit maturity threshold value of the fruit to be processed in the ripening process according to the maturity signal;

and the adjusting unit is used for adjusting the ripening environment and the controlled atmosphere environment according to the fruit ripening degree threshold and the delivery condition so as to realize the self-adaptive dynamic adjustment of the ripening process of the fruits to be processed.

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