CN113399344B - Technological parameter optimization method and calculation device for high-pressure jet cleaning machine - Google Patents
Technological parameter optimization method and calculation device for high-pressure jet cleaning machine Download PDFInfo
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- 230000003749 cleanliness Effects 0.000 claims abstract description 88
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B08—CLEANING
- B08B—CLEANING IN GENERAL; PREVENTION OF FOULING IN GENERAL
- B08B3/00—Cleaning by methods involving the use or presence of liquid or steam
- B08B3/02—Cleaning by the force of jets or sprays
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B08—CLEANING
- B08B—CLEANING IN GENERAL; PREVENTION OF FOULING IN GENERAL
- B08B13/00—Accessories or details of general applicability for machines or apparatus for cleaning
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F30/20—Design optimisation, verification or simulation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B08—CLEANING
- B08B—CLEANING IN GENERAL; PREVENTION OF FOULING IN GENERAL
- B08B2203/00—Details of cleaning machines or methods involving the use or presence of liquid or steam
- B08B2203/007—Heating the liquid
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B08—CLEANING
- B08B—CLEANING IN GENERAL; PREVENTION OF FOULING IN GENERAL
- B08B2203/00—Details of cleaning machines or methods involving the use or presence of liquid or steam
- B08B2203/02—Details of machines or methods for cleaning by the force of jets or sprays
- B08B2203/0217—Use of a detergent in high pressure cleaners; arrangements for supplying the same
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Abstract
The invention discloses a technological parameter optimization method and a calculation device for a high-pressure jet cleaning machine. The method for optimizing the technological parameters of the high-pressure jet cleaning machine comprises the steps of obtaining control factors, first technological parameters of the control factors and first cleaning cleanliness formed by the first technological parameters of the control factors; obtaining a significant factor from the control factors according to the control factors, the first process parameters and the first cleaning cleanliness; calculating a preliminary optimized value of each significant factor according to the first process parameter of each significant factor and the first cleaning cleanliness corresponding to the first process parameter of each significant factor; and calculating second process parameters of the significant factors according to the preliminary optimization value, obtaining second cleaning cleanliness formed by the second process parameters of the significant factors, and calculating an optimal process parameter combination according to the second process parameters and the second cleaning cleanliness.
Description
Technical Field
The invention relates to the field of cleaning, in particular to a method for optimizing process parameters of a high-pressure jet cleaning machine and a computing device.
Background
In the production and life process, objects are often required to be cleaned, the traditional cleaning technology comprises steam cleaning, chemical cleaning, ultrasonic cleaning, high-pressure jet cleaning and the like, and the high-pressure jet cleaning is the mainstream in the cleaning field at present. High-pressure jet cleaning is widely applied to surfaces of large-scale equipment or parts, pressure vessels, industrial vessels, pipelines and the like due to the advantages of high efficiency, low cost, no damage to workpieces, convenience in operation, safety and the like. The types of soils that can be cleaned by high pressure jet cleaning include: various saline-alkali dirt, iron oxide, metal rust, grease and oil stain coagula thereof, paint, dust, marine organisms attached to the ship body and the like.
In the prior art, high pressure jet cleaning is generally performed by a high pressure jet cleaning machine comprising: an upper and lower cleaning moving means for controlling a pressure of the cleaning liquid sprayed onto the surface of the cleaning object; the heating system is used for heating and controlling the constant temperature of the cleaning liquid; a cleaning solution filtration system for collecting and filtering cleaning solution. These systems can control the control factors affecting the cleaning effect, such as the pressure of the cleaning liquid sprayed onto the surface of the cleaning object, the cleaning temperature, the concentration of the cleaning liquid, etc., but there is no study on these control factors in the prior art, and the high-pressure spray cleaning machine cannot efficiently clean various objects, resulting in waste of resources.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a technological parameter optimization method and a calculation device for a high-pressure jet cleaning machine, which can enable the high-pressure jet cleaning machine to quickly obtain the optimal technological parameters, improve the working efficiency of the high-pressure jet cleaning machine under the condition of ensuring the cleaning effect, and are energy-saving and environment-friendly.
According to the first aspect of the invention, the method for optimizing the process parameters of the high-pressure jet cleaning machine comprises the following steps:
acquiring control factors, first process parameters of the control factors and first cleaning cleanliness formed by the first process parameters of the control factors;
obtaining a significant factor from the control factor according to the control factor, the first process parameter and the first cleaning cleanliness;
calculating a preliminary optimized value of each significant factor according to the first process parameter of each significant factor and the first cleaning cleanliness corresponding to the first process parameter of each significant factor;
and calculating a second process parameter of each significant factor according to the preliminary optimization value, obtaining a second cleaning cleanliness formed by the second process parameters of each significant factor, and calculating an optimal process parameter combination according to the second process parameter and the second cleaning cleanliness.
The method for optimizing the process parameters of the high-pressure jet cleaning machine according to the embodiment of the first aspect of the invention has at least the following beneficial effects:
the first cleaning cleanliness is used as a preliminary reference standard for evaluating the cleaning effect of the high-pressure jet cleaning machine, main control factors influencing the first cleaning cleanliness are selected as significant factors according to the first cleaning cleanliness obtained by different first process parameter combinations of different control factors, the significant factors are further analyzed, the control factors influencing the first cleanliness less can be quickly eliminated, the complexity of data analysis is reduced, and the efficiency of calculating the optimal process parameter combination is improved. And calculating the initial optimized value of each significant factor to obtain the initial optimal process parameter value of each significant factor on the premise of ensuring the cleaning effect. And calculating second process parameters of the significant factors according to the preliminary optimization values, and obtaining second cleaning cleanliness according to the combination of the second process parameters of the significant factors. And taking the second cleaning cleanliness as a final reference standard for evaluating the cleaning effect of the high-pressure jet cleaning machine, constructing a relation model of the significant factors and the second cleaning cleanliness according to the corresponding relation between the second cleaning cleanliness and the second process parameters, and obtaining the optimal process parameter combination of the significant factors from the model on the premise of ensuring the cleaning effect. Therefore, the method firstly screens the significant factors from all the control factors to serve as an analysis object, obtains the optimal process parameter combination of the significant factors on the premise of ensuring the cleaning effect, enables the high-pressure jet cleaning machine to rapidly obtain the optimal process parameters, and improves the working efficiency of the high-pressure jet cleaning machine under the condition of ensuring the cleaning effect.
According to some embodiments of the invention, the first cleaning cleanliness and the second cleaning cleanliness are the number of particles on the surface of the object after cleaning.
According to some embodiments of the present invention, the number of the control factors is at least two, and the number of the first process parameters of each of the control factors is at least two.
According to some embodiments of the invention, the control factors include a spray surface pressure, a cleaning time, a cleaning liquid temperature, and a cleaning liquid concentration.
According to some embodiments of the invention, said deriving a significant factor from said control factors based on said control factors, said first process parameter and said first cleaning cleanliness comprises:
constructing an orthogonal model of the control factor, the first process parameter, and the first cleaning cleanliness;
calculating the range value of each control factor in the orthogonal model through a range analysis algorithm;
and sequencing the control factors according to the range values and obtaining the significant factors.
According to some embodiments of the invention, the range analysis algorithm is:
R＝max[k1，…，ki]-min[k1…，ki]
wherein R represents a range value of each control factor, i represents the number of different first process parameters of the same control factor, and k representsiA sum of said first cleaning cleanliness, said max k, for the same said first process parameter representing the same said control factor in said orthogonal model1，…，ki]Represents obtaining the k1To the kiMaximum value of, said min [ k ]1…，ki]Represents obtaining the k1To the kiMinimum value of (1).
According to some embodiments of the present invention, the calculating a preliminary optimized value of each of the significant factors according to the first process parameter of each of the significant factors and the first cleaning cleanliness corresponding to the first process parameter of each of the significant factors includes:
respectively performing curve fitting on the first process parameters of the significant factors and the first cleaning cleanliness corresponding to the first process parameters of the significant factors through a least square algorithm to obtain a curve function of each significant factor;
and calculating the minimum value of each curve function through a steepest descent algorithm, wherein the minimum value of each curve function forms a preliminary optimization value.
According to some embodiments of the present invention, the number of the significant factors is at least two, the calculating a second process parameter of each significant factor according to the preliminary optimization value and obtaining a second cleaning cleanliness formed by the second process parameter of each significant factor together, and the calculating an optimal process parameter combination according to the second process parameter and the second cleaning cleanliness includes:
calculating a second process parameter of each significant factor according to a central composite design method with the equal-diameter factor being an equilateral octagon and the central point being the primary optimization value;
acquiring a second cleaning cleanliness formed by the second process parameters of the significant factors;
performing surface fitting on the second process parameters and the second cleaning cleanliness by a least square method to obtain a second-order response surface function;
and calculating the minimum value of the second order response surface function through a Levenberg-Marquardt algorithm, wherein the minimum value of the second order response surface function is the optimal process parameter combination.
According to some embodiments of the invention, the second order response surface function is:
wherein y represents the second cleaning cleanliness, and xiAnd said xjRepresenting the second process parameters corresponding to the ith and jth significant factors, wherein n represents the number of significant factors, and deltayThe error between the regression value and the true value, the beta0Beta of the formulaiBeta of the formulaiiAnd said betaijAnd the undetermined coefficients of all terms in the second-order response surface function are obtained.
The computing device according to an embodiment of the second aspect of the invention, applied to a high pressure jet washer, comprises:
a number of processors is at least one;
and a storage medium for storing at least one program, the number of the storage medium is at least one, the storage medium is in communication connection with the processor, and when the program is executed by the processor, the processor is enabled to implement the method for optimizing the process parameters of the high pressure jet cleaning machine according to the embodiment of the first aspect.
The computing device according to the embodiment of the second aspect of the present invention has at least the following beneficial effects:
the calculation device of the first aspect embodiment can quickly screen the significant factors from all the control factors to serve as an analysis object, and obtains the optimal technological parameter combination of the significant factors on the premise of ensuring the cleaning effect, so that the high-pressure jet cleaning machine can quickly obtain the optimal technological parameters, the working efficiency of the high-pressure jet cleaning machine is improved under the condition of ensuring the cleaning effect of the high-pressure jet cleaning machine, the configuration and the effective utilization rate of the high-pressure jet cleaning machine on resources are optimized, the waste of energy is avoided, and the purposes of energy conservation and environmental protection are achieved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of a method for optimizing process parameters of a high pressure jet cleaning machine according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a method for optimizing process parameters of a high pressure jet cleaning machine according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of a level table of control factors provided by one embodiment of the present invention;
FIG. 4 is a schematic diagram of an orthogonal model of the control factor provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram of a method for optimizing process parameters of a high pressure jet cleaning machine according to another embodiment of the present invention;
FIG. 6 is a graph of a first curve function of spray surface pressure and first cleaning cleanliness provided by one embodiment of the present invention;
FIG. 7 is a schematic diagram of a method for optimizing process parameters of a high pressure jet cleaning machine according to another embodiment of the present invention;
FIG. 8 is a schematic diagram of an equilateral octagonal constant radius factor according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of a central composite design model provided in accordance with an embodiment of the present invention;
FIG. 10 is a plot of a second order response surface function of spray surface pressure, cleaning time, and second cleaning cleanliness provided by an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If there is a description of the first, second, third and fourth only for the purpose of distinguishing between technical features, this is not to be understood as indicating or implying a relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly defined, terms such as arrangement, connection and the like should be broadly construed, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the detailed contents of the technical solutions.
The method for optimizing the process parameters of the high pressure jet cleaning machine according to the embodiment of the first aspect of the present invention is described in detail below with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the present invention provides a method for optimizing process parameters of a high pressure jet cleaning machine, which is applied to the high pressure jet cleaning machine, and includes, but is not limited to, the following steps:
s100, acquiring control factors, first process parameters of the control factors and first cleaning cleanliness formed by the first process parameters of the control factors;
s200, obtaining significant factors from the control factors according to the control factors, the first process parameters and the first cleaning cleanliness;
s300, calculating a primary optimized value of each significant factor according to the first process parameter of each significant factor and the first cleaning cleanliness corresponding to the first process parameter of each significant factor;
and S400, calculating second process parameters of the significant factors according to the preliminary optimization values, obtaining second cleaning cleanliness formed by the second process parameters of the significant factors, and calculating an optimal process parameter combination according to the second process parameters and the second cleaning cleanliness.
According to the method for optimizing the process parameters of the high-pressure jet cleaning machine, the first cleaning cleanliness is used as a preliminary reference standard for evaluating the cleaning effect of the high-pressure jet cleaning machine, main control factors influencing the first cleaning cleanliness are selected as significant factors according to the first cleaning cleanliness obtained by different first process parameter combinations of different control factors, the significant factors are further analyzed, the control factors influencing the first cleanliness less can be quickly eliminated, the complexity of data analysis is reduced, and the efficiency of calculating the optimal process parameter combination is improved. And calculating the initial optimized value of each significant factor to obtain the initial optimal process parameter value of each significant factor on the premise of ensuring the cleaning effect. And calculating second process parameters of the significant factors according to the preliminary optimization values, and obtaining second cleaning cleanliness according to the combination of the second process parameters of the significant factors. And taking the second cleaning cleanliness as a final reference standard for evaluating the cleaning effect of the high-pressure jet cleaning machine, constructing a relation model of the significant factors and the second cleaning cleanliness according to the corresponding relation between the second cleaning cleanliness and the second process parameters, and obtaining the optimal process parameter combination of the significant factors from the model on the premise of ensuring the cleaning effect. Therefore, the method firstly screens the significant factors from all the control factors to serve as an analysis object, obtains the optimal process parameter combination of the significant factors on the premise of ensuring the cleaning effect, enables the high-pressure jet cleaning machine to rapidly obtain the optimal process parameters, and improves the working efficiency of the high-pressure jet cleaning machine under the condition of ensuring the cleaning effect.
Further, the first cleaning cleanliness and the second cleaning cleanliness are the number of particles remaining on the surface of the cleaned object, and the cleaning effect of the high-pressure jet cleaning machine can be quantified by counting the number of particles remaining on the surface of the cleaned object, so that the optimal process parameter combination can be obtained through calculation.
Referring to fig. 2, fig. 3 and fig. 4, another embodiment of the invention provides a method for optimizing process parameters of a high pressure jet cleaning machine, and based on the above embodiment, the method shown in fig. 2 is a specific flow of step S200 in fig. 1, and includes, but is not limited to, the following steps:
s210, constructing an orthogonal model of control factors, first process parameters and first cleaning cleanliness;
s220, calculating the range value of each control factor in the orthogonal model through a range analysis algorithm;
and S230, sequencing the control factors according to the range values and obtaining the significant factors.
Specifically, in the embodiment, the number of the control factors is four, wherein the control factors comprise the spray surface pressure, the cleaning time, the temperature of the cleaning liquid and the concentration of the cleaning liquid, and the value range of a first process parameter (A) of the temperature of the cleaning liquid is more than or equal to 20 ℃ and less than or equal to 80 ℃; the value range of the first process parameter (B) of the pressure of the spraying surface is that B is more than or equal to 0.2MP and less than or equal to 0.5 MP; the value range of the first process parameter (C) of the cleaning liquid concentration is more than or equal to 0.05 and less than or equal to 0.1 (the ratio of the cleaning liquid to the water); the value range of the first process parameter (D) of the cleaning time is more than or equal to 10min and less than or equal to 20 min. As shown in fig. 3, four level values are selected from the first process parameters corresponding to the control factors, and each level value corresponds to a level number. And (4) testing the combination of different level values of the four control factors to obtain the first cleaning cleanliness. As shown in fig. 4, sixteen first cleaning cleaness values and horizontal values of the first process parameters corresponding to the first cleaning cleanability values are selected to construct an orthogonal model of the control factors in step S210.
In step S220, the range values of the jet surface pressure, the cleaning time, the cleaning liquid temperature and the cleaning liquid concentration in the orthogonal model are calculated by the range analysis algorithm, specifically, the range values are calculated by the formula:
R＝max[k1，…，ki]-min[k1…，ki]
where R denotes the range of the respective control factor, i denotes the number of different first process parameters of the same control factor, i.e. the number of level values of the same control factor, i being 4, k in this exampleiThe sum of the first cleaning cleannesses corresponding to level values of the same level number representing the same control factor in the orthogonal model, for example, with reference to FIG. 4, for the ejection surface pressure, k1＝S1+S5+S9+S13,k2＝S2+S6+S10+S14， k3＝S3+S7+S11+S15,k4＝S4+S8+S12+S16，max[k1，…，ki]Representation acquisition k1To k isiMaximum value of (1), min [ k ]1…，ki]Representation acquisition k1To k is4The minimum value of (d). The change of the first process parameter of the row of the control factors with the largest range has the largest influence on the first cleaning cleanliness, so the control factor with the largest influence on the first cleaning cleanliness can be obtained by comparing the range values of the control factors in step S230. In this embodiment, RPressure of the jet surface>RTime of cleaning>RConcentration of cleaning solution>RTemperature of cleaning liquidThe most significant factors affecting the first cleaning cleanliness are the spray surface pressure, followed by the cleaning time, the cleaning liquid concentration, and finally the cleaning liquid temperature, and thus the spray surface pressure and the cleaning time are selected as the significant factors in step S230. By the method for optimizing the technological parameters of the high-pressure jet cleaning machine, the control factors which have less influence on the first cleanliness can be quickly eliminated, the complexity of subsequent data analysis is reduced, and the efficiency of calculating the optimal technological parameter combination is improved.
Referring to fig. 4, fig. 5 and fig. 6, another embodiment of the invention provides a method for optimizing process parameters of a high pressure jet cleaning machine, and based on the above embodiment, the method shown in fig. 5 is a specific flow of step S300 in fig. 1, and includes, but is not limited to, the following steps:
s310, respectively performing curve fitting on the first process parameters of the significant factors and the first cleaning cleanliness corresponding to the first process parameters of the significant factors through a least square algorithm to obtain curve functions of the significant factors;
and S320, calculating the minimum value of each curve function through the steepest descent algorithm, wherein the minimum value of each curve function forms a primary optimization value.
Specifically, in step S310, curve fitting is performed by a least square method using the first process parameters (B1 to B4) of the ejection surface pressure in fig. 4 and the first cleaning cleanliness (S1 to S16) corresponding to the first process parameters, to obtain a first curve function with respect to the ejection surface pressure as shown in fig. 6; the first process parameters (D1 to D4) of the cleaning time in fig. 4 and the first cleaning cleanliness (S1 to S16) corresponding to the first process parameters are used to perform curve fitting by a least square method, and a second curve function with respect to the cleaning time is obtained.
In step S310, a first minimum value of the first curve function and a second minimum value of the second curve function are calculated by a steepest descent algorithm, and a preliminary optimized value is formed by the first minimum value and the second minimum value, which is the minimum value that can be obtained by the injection surface pressure and the cleaning time on the premise of ensuring the cleaning effect. The parameters obtained by the method reduce the pressure of the spraying surface and the cleaning time on the premise of meeting the cleaning effect, thereby saving the use of water and electricity and achieving the effect of environmental protection; in addition, the optimization of the cleaning time can improve the operation speed and the work efficiency of the high-pressure jet cleaning machine.
Specifically, in step S310, the fastest iteration formula x is used for the first curve function and the second curve function respectively(k +1)＝xk+λkdk(k +1) iterating when the condition is satisfied
Respectively obtaining a first minimum value and a second minimum value. Wherein f (x) is a first curve function or a second curveLine function, ε represents the computational accuracy requirement, k represents the number of iterations, dkDenotes the search direction, λ, of the kth iterationkThe step size of the k-th iteration is indicated,
is f (x) at xkGradient at position, xkRepresenting the value of the kth iteration of the first process parameter.
Referring to fig. 7, 8, 9 and 10, another embodiment of the invention provides a method for optimizing process parameters of a high pressure jet cleaning machine, and based on the above embodiment, the method shown in fig. 7 is a specific flow of step S400 in fig. 1, and includes, but is not limited to, the following steps:
s410, calculating second process parameters of each significant factor according to a center composite design method with the equal-diameter factor being equilateral octagon and the central point being a primary optimization value;
s420, obtaining a second cleaning cleanliness formed by the second process parameters of all the significant factors;
s430, performing surface fitting on the second process parameters and the second cleaning cleanliness by a least square method to obtain a second-order response surface function;
and S440, calculating the minimum value of the second-order response surface function through the Levenberg-Marquardt algorithm, wherein the minimum value of the second-order response surface function is the optimal process parameter combination.
Specifically, referring to fig. 8 and 9, step S410 calculates a second process parameter of the spray surface pressure and a second process parameter of the cleaning time for the experiment with the preliminary optimized values, i.e., the first minimum value and the cleaning time and the second minimum value of the spray surface pressure as center points, and with the selection rule of the equilateral octagonal isodiametric factor, using the spray surface pressure and the cleaning time as study objects according to the central composite design model. Step 420 derives the second cleaning cleanliness of each combination by combining and experimenting each second process parameter of the spray surface pressure and each second process parameter of the cleaning time. Step S430 fits the second cleaning cleanliness, the second process parameter of the spray surface pressure, and the second process parameter of the cleaning time by least two multiplications to derive a second order response surface function characterizing the relationship between the second cleaning cleanliness and the spray surface pressure and the cleaning time. In this embodiment, a surface map of the second order response surface function is shown in fig. 10, where the second order response surface function is:
wherein y represents the second cleaning cleanliness, xiAnd xjRepresenting the second process parameters corresponding to the ith and jth significant factors, n representing the number of significant factors, deltayError of the regression value from the true value, beta0、βi、βiiAnd betaijTo be undetermined coefficients, beta, of terms in the second order response surface function0、βi、βii、βijAnd deltayThe value of (A) is determined by the least square method, in this example xiAnd xjAnd n is 2, the second process parameter representing the pressure of the ejection surface and the second process parameter representing the cleaning time. Step S440 calculates a most stable point of the second order response surface function by an LM (Levenberg-Marquardt ) algorithm, and a third minimum value of the ejection surface pressure and a fourth minimum value of the cleaning time at the most stable point constitute an optimal process parameter combination, which represents minimum values that the ejection surface pressure and the cleaning time can take in the case of satisfying the cleaning effect. In this embodiment, an LM algorithm is used to find the most stable point of the second-order response surface function, and the iterative formula of the LM algorithm is as follows:
wherein k represents the number of iterations, JkJacobian matrix over k iterations, g, representing a second order response surface functionkRepresenting a second order response surface function at xkDirection of negative gradient at location, xkSecond process parameter and cleaning time representing pressure to spray surfaceAnd the two process parameters form a matrix after the kth iteration, wherein I represents an identity matrix, and mu represents an iteration step. When the condition is satisfied
Then, the optimal process parameter combination is obtained, epsilon represents the calculation precision requirement,
representing a second order response surface function at xkThe gradient at the location. According to the method for optimizing the process parameters of the high-pressure jet cleaning machine, the relation between the second cleaning cleanliness and the jet surface pressure and the cleaning time is fitted through the second-order response surface function, the second-order response surface function can visually reflect the influence of the combined action of the jet surface pressure and the cleaning time on the second cleaning cleanliness, the third minimum value of the jet surface pressure and the fourth minimum value of the cleaning time can be determined on the premise that the cleaning effect is met by searching the local minimum value point of the second-order response surface function, and the optimal process parameter combination of the jet surface pressure and the cleaning time can be obtained more accurately under the constraint of the second cleaning cleanliness.
In conclusion, the method of the invention firstly predicts the significant factors influencing the cleaning effect by the orthogonal experiment method, calculates the initial optimized values of the significant factors, then optimizes the initial optimized values by combining the response surface analysis method and calculates the optimal process parameter combination of the significant factors under the condition of meeting the cleaning effect, thereby effectively improving the calculation speed of obtaining the optimal process parameter combination, improving the efficiency and the precision of the high-pressure jet cleaning machine for optimizing the process parameters, and improving the working efficiency and saving energy and protecting environment of the high-pressure jet cleaning machine working under the optimal process parameter combination.
The computing device of the second aspect of the present invention is described in detail below with reference to the accompanying drawings.
An embodiment of the present invention further provides a computing device, which is applied to a high pressure jet cleaning machine, and includes at least one processor and at least one storage medium, where the storage medium is used to store at least one program, and the processor is connected in communication with the storage medium, and when the program is executed by the processor, the processor is enabled to implement the method for optimizing the process parameters of the high pressure jet cleaning machine according to the embodiment of the first aspect. For example, the above-described method steps S100, S200, S300 and S400 in fig. 1, the method steps S210, S220 and S230 in fig. 2, the method steps S310 and S320 in fig. 5, and the method steps S410, S420, S430 and S440 in fig. 7 are performed.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on storage media, which may include computer-readable storage media (or non-transitory media) and communication media (or transitory media). The term computer readable storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as integrated circuit readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other storage media technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
It should be further noted that the computing device of this embodiment may be integrated inside the high-pressure spray cleaning machine, and the design and execution of the orthogonal experiment method and the response surface analysis method in the above first aspect embodiment, that is, the setting of the first process parameter and the second process parameter, the measurement and acquisition of the first cleaning cleanliness and the second cleaning cleanliness, and the calculation of the combination of the initial optimized value and the optimal process parameter obtained by the range analysis algorithm, the least square method, the steepest descent algorithm, and the LM algorithm, may be cooperatively completed by the computing device integrated inside the high-pressure spray cleaning machine and a functional module of the high-pressure spray cleaning machine controlled by the computing device, that is, independently completed by the high-pressure spray cleaning machine; the calculation device can also be equipment independent of the high-pressure spray cleaning machine, the calculation device is in communication connection with the high-pressure spray cleaning machine in a wired or wireless mode, the measurement of the first cleaning cleanliness and the second cleaning cleanliness can be executed by the high-pressure spray cleaning machine according to a control instruction sent by the calculation device, the calculation device is used for setting the first process parameter and the second process parameter in an orthogonal experiment method and a response surface analysis method, obtaining the first cleaning cleanliness and the second cleaning cleanliness from the high-pressure spray cleaning machine or other measurement instruments, calculating a preliminary optimization value and an optimal process parameter combination by adopting a range analysis algorithm, a least square method, a steepest descent algorithm and an LM algorithm, and finally sending the optimal process parameter combination to the high-pressure spray cleaning machine and completing the configuration of the high-pressure spray cleaning machine.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. A method for optimizing technological parameters of a high-pressure jet cleaning machine is characterized by comprising the following steps:
acquiring control factors, first process parameters of the control factors and first cleaning cleanliness formed by the first process parameters of the control factors;
obtaining a significant factor from the control factor according to the control factor, the first process parameter and the first cleaning cleanliness;
calculating a preliminary optimized value of each significant factor according to the first process parameter of each significant factor and the first cleaning cleanliness corresponding to the first process parameter of each significant factor;
and calculating a second process parameter of each significant factor according to the preliminary optimization value, obtaining a second cleaning cleanliness formed by the second process parameters of each significant factor, and calculating an optimal process parameter combination according to the second process parameter and the second cleaning cleanliness.
2. The method for optimizing process parameters of a high pressure jet cleaner according to claim 1, wherein the first cleaning cleanliness and the second cleaning cleanliness are the number of particles on the surface of the object after cleaning.
3. The method of claim 2, wherein the number of the control factors is at least two, and the number of the first process parameters of each of the control factors is at least two.
4. The method of claim 3, wherein the control factors include spray surface pressure, cleaning time, cleaning liquid temperature, and cleaning liquid concentration.
5. The method for optimizing process parameters of a high pressure jet cleaning machine according to claim 1, wherein the obtaining of significant factors from the control factors according to the control factors, the first process parameters and the first cleaning cleanliness comprises:
constructing an orthogonal model of the control factor, the first process parameter, and the first cleaning cleanliness;
calculating the range value of each control factor in the orthogonal model through a range analysis algorithm;
and sequencing the control factors according to the range values and obtaining the significant factors.
6. The method for optimizing process parameters of a high pressure jet washer according to claim 5, wherein the range analysis algorithm is:
R＝max[k1，…，ki]-min[k1…，kt]
wherein R represents a range value of each control factor, i represents the number of different first process parameters of the same control factor, and k representsiA sum of said first cleaning cleanliness, said max k, for the same said first process parameter representing the same said control factor in said orthogonal model1，…，ki]Represents obtaining the k1To the kiMaximum value of, said min [ k ]1…，ki]Represents obtaining the k1To the kiMinimum value of (1).
7. The method for optimizing process parameters of a high pressure jet cleaning machine according to claim 1, wherein the calculating a preliminary optimized value of each significant factor according to the first process parameter of each significant factor and the first cleaning cleanliness corresponding to the first process parameter of each significant factor comprises:
respectively performing curve fitting on the first process parameters of the significant factors and the first cleaning cleanliness corresponding to the first process parameters of the significant factors through a least square algorithm to obtain a curve function of each significant factor;
and calculating the minimum value of each curve function through a steepest descent algorithm, wherein the minimum value of each curve function forms a preliminary optimization value.
8. The method for optimizing process parameters of a high pressure jet cleaning machine according to claim 1, wherein the number of the significant factors is at least two, a second process parameter of each significant factor is calculated according to the preliminary optimization value, a second cleaning cleanliness jointly formed by the second process parameters of each significant factor is obtained, and an optimal process parameter combination is calculated according to the second process parameter and the second cleaning cleanliness, and the method comprises the following steps:
calculating a second process parameter of each significant factor according to a central composite design method with the equal-diameter factor being an equilateral octagon and the central point being the primary optimization value;
acquiring a second cleaning cleanliness formed by the second process parameters of the significant factors;
performing surface fitting on the second process parameters and the second cleaning cleanliness by a least square method to obtain a second-order response surface function;
and calculating the minimum value of the second-order response surface function through a Levenberg-Marquardt algorithm, wherein the minimum value of the second-order response surface function is the optimal process parameter combination.
9. The method of claim 8, wherein the second order response surface function is:
wherein y represents the second cleaning cleanliness, and xiAnd said xjRepresenting the second process parameters corresponding to the ith and jth significant factors, wherein n represents the number of significant factors, and deltayThe error between the regression value and the true value, the beta0Beta of the formulaiBeta of the formulaiiAnd said betaijAnd the undetermined coefficients of all terms in the second-order response surface function are obtained.
10. A computing device for use in a high pressure jet washer, comprising:
a number of processors is at least one;
a storage medium for storing at least one program, the storage medium being at least one in number and being in communication with the processor, the program, when executed by the processor, causing the processor to implement the method for optimizing process parameters of a high pressure jet washer according to any one of claims 1 to 9.
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