CN114941893B - Air conditioning device - Google Patents
Air conditioning device Download PDFInfo
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- CN114941893B CN114941893B CN202210666377.5A CN202210666377A CN114941893B CN 114941893 B CN114941893 B CN 114941893B CN 202210666377 A CN202210666377 A CN 202210666377A CN 114941893 B CN114941893 B CN 114941893B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2120/00—Control inputs relating to users or occupants
- F24F2120/10—Occupancy
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Abstract
The air conditioning device includes: an infrared imaging section configured to generate an infrared thermal image in an indoor environment; a human body recognition part configured to recognize and select a human body target in the infrared thermal image and generate a human body infrared thermal image; a human body infrared thermal image temperature detection part configured to determine a target temperature of each pixel point in the human body infrared thermal image, screen a maximum pixel temperature value in the target temperature, and calculate an average pixel temperature value of the human body infrared thermal image; and a dressing amount confirmation unit configured to confirm that the dressing amount of the human body target is a dressing level corresponding to the dressing amount ratio threshold condition when the proportional relation between the average pixel temperature value and the maximum pixel temperature value satisfies one of a plurality of preset dressing amount ratio threshold conditions. The clothes amount estimating process does not depend on physical addresses, weather parameters, video monitoring or manual input, the intelligent degree of the product can be ensured not to be influenced, and meanwhile, the user is prevented from generating concerns related to privacy.
Description
Technical Field
The invention relates to the technical field of air conditioning, in particular to an air conditioning device.
Background
The indoor environment in which the user is in a better comfort level is a research and development hot spot in recent years of air conditioner manufacturers by correcting the control parameters of the air conditioner through the dressing index of the user.
For example, patent document 1 (publication No. CN109425075 a) describes: "a comfort level determining method of an air conditioning apparatus, comprising the steps of: and acquiring outdoor environment parameters, acquiring dressing indexes in the working space of the air conditioning device according to the outdoor environment parameters, and adjusting the operation parameters of the air conditioning device according to the dressing indexes. I.e. generating a corresponding dressing index according to the current geographical location and weather conditions.
Patent document 2 (publication No. CN110030699 a) describes: "an air conditioning apparatus control method, comprising: acquiring clothing condition data of a user, matching to obtain clothing warmth retention indexes according to the clothing condition data, and adjusting operation parameters of air conditioning equipment according to the clothing warmth retention indexes; wherein the acquiring of the dressing condition data of the user comprises: and receiving wearing condition data input by a user through an input function preset by the remote controller. "
Patent document 3 (publication No. CN107576022 a) describes: the method comprises the steps of carrying out video monitoring on the indoor through a camera arranged on an air conditioner or a video monitor arranged at other indoor positions, extracting a human body image … in a video frame by … to pretreat the human body image to obtain a clothes ROI of the human body image, extracting feature vectors in the clothes ROI to be fused into clothes features, judging whether a training model matched with the clothes features exists in a preset clothes classifier, and acquiring a warmth retention index of clothes worn by a human body currently according to the type and the material of the clothes corresponding to the training model. "
However, the error of generating the corresponding dressing index according to the current geographic position and weather conditions is large, and the individual difference cannot be accurately reflected; the intelligent degree of the product can be reduced by manually inputting the wearing condition by a user; the warmth retention index of the worn clothes is judged by utilizing the human body images extracted by video monitoring, on one hand, the risk of privacy leakage exists, and on the other hand, the judgment precision cannot reach an ideal level because the clothes are different in self-texture and different in cutting.
The above information disclosed in this background section is only for enhancement of understanding of the background section of the application and therefore it may not form the prior art that is already known to those of ordinary skill in the art.
Disclosure of Invention
Accordingly, an object of the present invention is to provide an air conditioning apparatus that can accurately estimate the amount of clothing worn by a person to achieve comfortable air conditioning, wherein the estimation process does not depend on physical addresses, weather parameters, video monitoring, or manual inputs, and can ensure that the degree of intelligence of the product is not affected, while avoiding privacy-related concerns from the user.
In order to achieve the aim of the invention, the invention is realized by adopting the following technical scheme:
in some embodiments of the present invention, an air conditioning apparatus includes an infrared imaging part, a human body recognition part, a human body infrared thermal image temperature detection part, and a dressing amount confirmation part; the infrared imaging part is configured to generate an infrared thermal image in the indoor environment, the human body recognition part is configured to recognize and select a human body target in the infrared thermal image, a human body infrared thermal image is generated, the human body infrared thermal image temperature detection part is configured to determine the target temperature of each pixel point in the human body infrared thermal image, and the maximum pixel temperature value in the target temperature is screened and the average pixel temperature value of the human body infrared thermal image is calculated; the dressing amount confirmation part is configured to confirm that the dressing amount of the human body target is a dressing grade corresponding to the dressing amount proportion threshold value condition when the proportion relation between the average pixel temperature value and the maximum pixel temperature value meets one of a plurality of preset dressing amount proportion threshold value conditions; the validation process is not dependent on manual operation by the user or external data.
In some embodiments of the present invention, the dressing level is divided into four levels, namely a first dressing level, a second dressing level, a third dressing level and a fourth dressing level. The first dressing grade corresponds to the wearing of exposed limbs such as a T-shirt, shorts and the like; the second dressing grade corresponds to a single layer of wearing of the shirt, trousers and the like which wrap the limbs; the third dressing grade corresponds to double-layer dressing of long sleeves, trousers and the like for wrapping the limbs; the fourth dressing grade corresponds to multi-layer dressing of the down jackets, sweaters, trousers and the like which wrap the limbs.
The infrared imaging part is configured to optimize the original image from two aspects of hardware defects and the image, so as to avoid forming ghost or pan cover effect, and the infrared imaging part is configured to restore the original level data received by the uncooled infrared focal plane detector into the original image with equal resolution according to the resolution of the uncooled infrared focal plane detector; detecting and replacing bad points in an original image; carrying out non-uniformity correction on the original image after the dead pixel replacement; carrying out noise reduction and filtering treatment on the original image after the non-uniformity correction; carrying out histogram processing on the original image subjected to noise reduction and filtering processing; and generating the original image after the histogram processing into an infrared thermal image in the indoor environment.
In some embodiments of the present invention, the non-uniformity correction may employ a one-point correction, a two-point correction, or a multi-point correction.
In some embodiments of the present invention, performing non-uniformity correction on an original image after replacing a dead pixel includes: the correction output Y satisfies: y=a× (X-B), where X represents the original output of the uncooled infrared focal plane detector when the shutter is open, B represents the original output of the detector when the shutter is closed, and a is the sensitivity correction coefficient of the uncooled infrared focal plane detector.
In some embodiments of the present invention, the human body recognition part is configured to recognize and select a human body target in the infrared thermal image using a convolutional neural network; the training sample of the convolutional neural network comprises a plurality of training thermal images, wherein any one training thermal image comprises a combination of one or more of a plurality of distance elements, angle elements, posture elements and dressing elements; the distance element is the relative distance of the training human body target, the angle element is the relative angle of the training human body target, the posture element is the posture of the training human body target, and the dressing element is the dress of the training human body target.
On the basis of the steven boltzmann's law, while considering the influence of the ambient temperature and the baffle, the human body infrared thermal image temperature detecting section is configured to determine the target temperature of each pixel point in the human body infrared thermal image in the following manner: target temperature T 0 The method meets the following conditions: Δraw14=a×t 0 4 -b×T 1 4 Wherein: Δraw14=raw14' -raw14″; in the above formula, T 1 The temperature of the baffle plate of the uncooled infrared focal plane detector is the target temperature T 0 And a baffle temperature T 1 The thermodynamic temperature is recorded, raw14' is the original output of the detector when the baffle of the uncooled infrared focal plane detector is opened, raw14″ is the original output of the detector when the baffle of the uncooled infrared focal plane detector is closed, a is a first coefficient, and b is a second coefficient.
In some embodiments of the invention, the first coefficient a and the second coefficient b are determined by linear fitting. The first coefficient a and the second coefficient b are obtained by: an uncooled infrared focal plane detector is adopted to collect infrared thermal images of a plurality of test radiation sources, and any test radiation source has a corresponding set surface temperature; respectively acquiring the display temperature of the uncooled infrared focal plane detector when the baffle of each test radiation source is opened and the display temperature of the uncooled infrared focal plane detector when the baffle of the uncooled infrared focal plane detector is closed, and calculating the temperature difference between the display temperature when the test radiation source is opened and the display temperature when the test radiation source is closed; one of the temperature difference and the set surface temperature is taken as an abscissa, and the other is taken as an ordinate to establish a coordinate system fitting calibration curve; and reversely solving a first coefficient a and a second coefficient b according to the calibration curve.
In some embodiments of the invention, the clothing amount ratio threshold condition may be obtained by simulating a scene. The method specifically comprises the following steps: setting a plurality of preset clothes scenes, wherein each preset clothes scene corresponds to a dressing amount grade; respectively sampling a plurality of test infrared thermal images; identifying and selecting a test human body target meeting a preset clothing scene in the test infrared thermal image, and generating a test human body infrared thermal image; determining a target temperature of each pixel point in the human body infrared thermal image, screening a maximum pixel temperature value in the target temperature, and calculating an average pixel temperature value of the human body infrared thermal image; calculating the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the human body to be tested; and establishing a one-to-one correspondence relation between the average pixel temperature value and the maximum pixel temperature value in the tested human body infrared thermal image and the preset clothing scene, wherein the ratio between the average pixel temperature value and the maximum pixel temperature value in the tested human body infrared thermal image is the clothing amount proportion threshold value of the corresponding preset clothing scene.
In some embodiments of the present invention, the air in the indoor environment is more precisely adjusted using the dressing level, and the air-conditioning apparatus further includes a dressing amount control part configured to perform air-conditioning control based on the confirmed dressing level and the real-time environmental temperature.
In some embodiments of the present invention, the clothing amount ratio threshold condition is obtained by determining the clothing level with optimal efficiency, improving the intelligence of the product, and specifically comprising the steps of: setting a plurality of preset clothes scenes, wherein each preset clothes scene corresponds to a dressing amount grade; setting a plurality of preset environmental temperatures; sampling a plurality of test infrared thermal images at each predetermined ambient temperature respectively; identifying and selecting a test human body target meeting one of the preset clothes scenes in the test infrared thermal image, and generating a test human body infrared thermal image; determining a target temperature of each pixel point in the human body infrared thermal image, screening a maximum pixel temperature value in the target temperature, and calculating an average pixel temperature value of the human body infrared thermal image; calculating the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the human body to be tested; establishing a coordinate system to fit a threshold fitting curve corresponding to a preset clothing scene by taking one of the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the tested human body and the preset environmental temperature as an abscissa and the other as an ordinate; inverse solving a threshold fitting function corresponding to a predetermined clothing scene according to the threshold fitting curve; acquiring a real-time environment temperature; substituting the real-time environment temperature into a threshold fitting function to obtain a dressing amount proportion threshold corresponding to a preset clothing scene.
Compared with the prior art, the invention has the advantages and positive effects that: the invention is an air-conditioning device which can accurately estimate the wearing capacity of a human body to realize comfortable air-conditioning, the estimation process does not depend on physical addresses, weather parameters, video monitoring or manual input, the intelligent degree of products can be ensured not to be influenced, and meanwhile, the user is prevented from generating concerns related to privacy.
Other features and advantages of the present invention will become apparent upon review of the detailed description of the invention in conjunction with the drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it will be obvious that the drawings in the following description are some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic block diagram showing the structure of an embodiment of an air conditioning apparatus according to the present invention;
FIG. 2 is a flow chart showing a controller in one embodiment of an air conditioning apparatus provided by the present invention;
FIG. 3 is a flow chart showing a controller in one embodiment of an air conditioning apparatus provided by the present invention;
FIG. 4 is a flow chart of the controller when performing part of the functions of the infrared imaging section shown in FIG. 1;
FIG. 5 is a flow chart of the controller when performing non-uniformity correction;
fig. 6 is a flowchart of a controller when performing a part of the functions of the human body imaging part shown in fig. 1;
FIG. 7 is a flowchart of the controller when performing part of the functions of the human body IR thermal image temperature detecting section shown in FIG. 1;
FIG. 8 is a flow chart of the controller in determining the first coefficient and the second coefficient;
FIG. 9 is a flow chart of the controller in determining a cut-size ratio threshold;
fig. 10 is a schematic block diagram showing the construction of another embodiment of the air conditioning apparatus provided by the present invention;
FIG. 11 is another flow chart of the controller in determining the cut-size ratio threshold.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
In the description of the present application, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate description of the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present application.
The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art in a specific context.
In the present invention, unless expressly stated or limited otherwise, a first feature "above" or "below" a second feature may include both the first and second features being in direct contact, as well as the first and second features not being in direct contact but being in contact with each other through additional features therebetween. Moreover, a first feature being "above," "over" and "on" a second feature includes the first feature being directly above and obliquely above the second feature, or simply indicating that the first feature is higher in level than the second feature. The first feature being "under", "below" and "beneath" the second feature includes the first feature being directly under and obliquely below the second feature, or simply means that the first feature is less level than the second feature.
The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. In order to simplify the present disclosure, components and arrangements of specific examples are described below. They are, of course, merely examples and are not intended to limit the invention. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples, which are for the purpose of brevity and clarity, and which do not themselves indicate the relationship between the various embodiments and/or arrangements discussed. In addition, the present invention provides examples of various specific processes and materials, but one of ordinary skill in the art will recognize the application of other processes and/or the use of other materials.
The air conditioning device in the present application performs a refrigeration cycle of the air conditioning device by using a compressor, a condenser, an expansion valve, and an evaporator. The refrigeration cycle includes a series of processes involving compression, condensation, expansion, and evaporation, and supplies a refrigerant to the air that has been conditioned and heat exchanged.
The compressor compresses a refrigerant gas in a high-temperature and high-pressure state and discharges the compressed refrigerant gas. The discharged refrigerant gas flows into the condenser. The condenser condenses the compressed refrigerant into a liquid phase, and heat is released to the surrounding environment through the condensation process.
The expansion valve expands the liquid-phase refrigerant in a high-temperature and high-pressure state condensed in the condenser into a low-pressure liquid-phase refrigerant. The evaporator evaporates the refrigerant expanded in the expansion valve and returns the refrigerant gas in a low-temperature and low-pressure state to the compressor. The evaporator may achieve a cooling effect by exchanging heat with a material to be cooled using latent heat of evaporation of a refrigerant. The air conditioning device may adjust the temperature of the indoor space throughout the cycle.
The outdoor unit of the air conditioning apparatus refers to a portion of the refrigeration cycle including a compressor and an outdoor heat exchanger, the indoor unit of the air conditioning apparatus includes an indoor heat exchanger, and an expansion valve may be provided in the indoor unit or the outdoor unit.
The indoor heat exchanger and the outdoor heat exchanger function as a condenser or an evaporator. When the indoor heat exchanger is used as a condenser, the air-conditioning apparatus is used as a heater for the heating mode, and when the indoor heat exchanger is used as an evaporator, the air-conditioning apparatus is used as a cooler for the cooling mode.
The mode of converting the indoor heat exchanger and the outdoor heat exchanger into a condenser or an evaporator generally adopts a four-way valve, and the arrangement of the conventional air conditioning device is specifically referred to and will not be described herein.
The refrigeration working principle of the air conditioning device is as follows: the compressor works to enable the interior of an indoor heat exchanger (in an indoor unit, an evaporator at the moment) to be in an ultralow pressure state, liquid refrigerant in the indoor heat exchanger is rapidly evaporated to absorb heat, air blown out by an indoor fan is cooled by an indoor heat exchanger coil and then changed into cold air to be blown into the indoor, the evaporated refrigerant is pressurized by the compressor and then condensed into liquid state in a high-pressure environment in an outdoor heat exchanger (in an outdoor unit, a condenser at the moment), heat is released, the heat is emitted to the atmosphere by the outdoor fan, and the refrigerating effect is achieved through circulation.
The heating working principle of the air conditioning device is as follows: the gaseous refrigerant is pressurized by the compressor to become high-temperature high-pressure gas, and enters the indoor heat exchanger (a condenser at the moment), so that the gaseous refrigerant is condensed, liquefied and released heat to become liquid, and meanwhile, the indoor air is heated, so that the aim of improving the indoor temperature is fulfilled. The liquid refrigerant is decompressed by the throttling device, enters the outdoor heat exchanger (an evaporator at the moment), evaporates, gasifies and absorbs heat to become gas, and simultaneously absorbs heat of outdoor air (the outdoor air becomes colder) to become gaseous refrigerant, and enters the compressor again to start the next cycle.
The indoor unit may be selectively provided at a wall, a ceiling, or placed on the floor of the room. The outdoor unit is installed outdoors, and the indoor unit is connected to the outdoor unit through a refrigerant pipe and a cable. A control terminal for a user to operate the air conditioning device is communicatively connected to the indoor unit. The control terminal may be a remote control, a line controller or other intelligent terminal. The indoor unit has an uncooled infrared focal plane detector with a viewing angle covering an indoor environment.
Referring to fig. 1 and 2, the indoor unit further has a controller. The controller is provided with:
and the infrared imaging part is configured to display and output the temperature distribution of each part in the indoor environment captured by the uncooled infrared focal plane detector in a non-contact mode in an infrared thermal image mode, namely, generate an infrared thermal image in the indoor environment.
And the human body identification part is configured to identify and select a human body target in the infrared thermal image of the indoor environment and generate a human body infrared thermal image.
And the human body infrared thermal image temperature detection part is configured to determine the target temperature of each pixel point in the human body infrared thermal image, screen the maximum pixel temperature value in the target temperature and calculate the average pixel temperature value of the human body infrared thermal image.
And a dressing amount confirmation unit configured to confirm that the target dressing amount of the human body is a dressing level corresponding to the dressing amount ratio threshold condition when the proportional relation between the average pixel temperature value and the maximum pixel temperature value satisfies one of a plurality of preset dressing amount ratio threshold conditions.
In nature, as long as the temperature of an object exceeds absolute zero, corresponding infrared waves can be emitted to the outside at all times. Since humans are warm-blooded animals, body temperature is typically between 36 and 37 degrees celsius, with body surface temperature being substantially 34 degrees celsius in steady state. Considering common materials such as cotton, hemp, wool, artificial fiber and the like for making clothing, the infrared radiation of the exposed part of the human body is strongest. Infrared radiation is different when a person wears a coat and a thick coat. The intensity of infrared radiation generated by a human body when penetrating through the coat is obviously higher than that when penetrating through the coat, and further, the difference between the average infrared radiation intensity of the body surface and the highest infrared radiation intensity of the body surface is smaller when the human body wears the coat; when a human body wears the thick clothes, the difference between the average infrared radiation intensity of the body surface and the highest infrared radiation intensity of the body surface is relatively large; meanwhile, as the thickness increases, the difference also increases; similarly, as the thickness decreases, the variance decreases.
On the physical level, the infrared imaging part can also be integrated with a non-refrigeration infrared focal plane detector, the detector converts received heat radiation infrared signals with different intensity into corresponding electric signals to be output, and the electric signals are amplified by a thermal imaging algorithm to obtain imaging data and then are communicated to the controller.
After the dressing grade is obtained, the refrigerating and heating temperature of the air conditioning device can be automatically adjusted, the indoor environment temperature is intelligently adjusted, and the comfort level of indoor personnel is maximized.
In another alternative embodiment, as shown in fig. 10, the controller further includes a dressing amount control part configured to perform air conditioning control based on the confirmed dressing level and the real-time ambient temperature. Such as adjusting wind speed, wind direction, compressor operating frequency, set temperature, supply air temperature, etc.
In an alternative embodiment of the present invention, the dressing grades are divided into four grades, namely a first dressing grade, a second dressing grade, a third dressing grade and a fourth dressing grade. The first dressing grade corresponds to the wearing of exposed limbs such as a T-shirt, shorts and the like; the second dressing grade corresponds to a single layer of wearing of the shirt, trousers and the like which wrap the limbs; the third dressing grade corresponds to double-layer dressing of long sleeves, trousers and the like for wrapping the limbs; the fourth dressing grade corresponds to multi-layer dressing of the down jackets, sweaters, trousers and the like which wrap the limbs. In a scene with higher control accuracy requirements, more dressing grades can be set.
As shown in fig. 3, after the maximum pixel temperature value in the target temperature is screened and the average pixel temperature value of the human body infrared thermal image is calculated, whether the ratio of the average pixel temperature value to the maximum pixel temperature value is greater than the first dressing level ratio threshold is first determined, and if so, the dressing level of the human body target is confirmed to be the first dressing level. If the ratio of the average pixel temperature value to the maximum pixel temperature value is not greater than the first dressing amount ratio threshold, judging whether the ratio of the average pixel temperature value to the maximum pixel temperature value is greater than the second dressing amount ratio threshold, and if the ratio of the average pixel temperature value to the maximum pixel temperature value is greater than the second dressing amount ratio threshold, confirming that the dressing amount of the human body target is the second dressing grade. If the ratio of the average pixel temperature value to the maximum pixel temperature value is not greater than the second dressing amount ratio threshold, judging whether the ratio of the average pixel temperature value to the maximum pixel temperature value is greater than the third dressing amount ratio threshold, if so, confirming that the dressing amount of the human body target is the third dressing level, otherwise, the fourth dressing level.
After the dressing level is judged, the air conditioner control may be performed according to the dressing level.
As shown in fig. 4, in some embodiments of the present invention, the infrared imaging section is configured to generate an infrared thermal image using the following method.
And restoring the original level data received by the uncooled infrared focal plane detector into an original image with equal resolution according to the resolution of the uncooled infrared focal plane detector. The raw level data may be 14-bit or 16-bit data.
And detecting and replacing bad points in the original image.
The dead pixel refers to a bright-dark spot whose coordinates are not transformed with the target in the infrared image. If the dead pixel is screened, replacing the dead pixel by adopting an average value of 8 surrounding adjacent non-dead pixels, or replacing the dead pixel by one of the left and right 2 non-dead pixels, or replacing the dead pixel by one of the upper and lower 2 non-dead pixels.
And carrying out non-uniformity correction on the original image after the dead pixel replacement.
The non-uniformity correction may optionally employ a one-point correction, a two-point correction, or a multi-point correction. Due to the limitation of the manufacturing process of the detector, the imaging quality can be affected due to different response rates of each detecting microcell of the detector to infrared radiation, and the influence of the limitation of hardware on the imaging quality can be reduced due to non-uniformity correction.
As shown in fig. 5, in some embodiments of the present invention, performing non-uniformity correction on an original image after replacing a dead pixel includes:
acquiring the original output of the uncooled infrared focal plane detector when the baffle of the uncooled infrared focal plane detector is opened, and marking the original output as X;
acquiring the original output of the uncooled infrared focal plane detector when the baffle of the uncooled infrared focal plane detector is closed, and marking the original output as B;
invoking a sensitivity correction coefficient of the uncooled infrared focal plane detector, and recording the sensitivity correction coefficient as A; the sensitivity correction coefficient is obtained by testing and stored when the uncooled infrared focal plane detector leaves a factory or is used for the first time so as to be called at any time;
calculating a correction output Y, wherein the correction output Y satisfies:
Y＝A×(X-B)
the non-uniformity corrected original image is generated.
And further carrying out noise reduction and filtering processing on the original image after the non-uniformity correction.
Noise reduction filtering is to reduce noise in time and space, and to process the image itself. In some embodiments of the present invention, the temporal noise reduction adopts a multi-frame filtering mode, and continuous multi-frames perform low-pass filtering on pixel points at the same position to realize noise reduction; the spatial noise reduction adopts a Gaussian filtering mode, so that the smoothness of an original image is ensured, vertical stripes are removed, and the noise reduction filtering can achieve an ideal filtering effect by adjusting a corresponding filtering threshold. The filtering threshold is preferably set according to the scene with the highest probability of occurrence to obtain a processed image with a higher signal-to-noise ratio.
And further carrying out histogram processing on the original image after noise reduction and filtering.
And the core part of the infrared imaging part is used for processing the contrast of the original image during histogram processing. In the above steps, the infrared imaging unit has made the original image uniform and low-noise, but the details of the image cannot be visually observed, and a problem that a weak target cannot be recognized easily occurs. The histogram processing can solve the problem, and the histogram processing can stretch the gray-scale information of interest and compress the gray-scale information of no interest, so that the contrast ratio is improved.
Preferably, the main peak smoothing parameter is added simultaneously when the histogram processing is performed, the original image tensile strength is changed by changing the main peak constant width, smoothing and multi-frame processing are adopted when the original image main peak is acquired, and image oscillation caused by severe main peak change is avoided, so that the contrast ratio can be improved, and the problems of uniform picture and image flickering are simultaneously considered.
And generating the original image after the histogram processing into an infrared thermal image in the indoor environment.
As shown in fig. 6, in some embodiments of the present invention, the human body recognition part is configured to recognize and select a human body target in the infrared thermal image using a convolutional neural network.
The training samples of the convolutional neural network include a plurality of training thermal images. Training thermal images based on a combination of one or more of a plurality of distance elements, angle elements, gesture elements, and dressing elements; wherein the distance element is the relative distance of the training human body target, the angle element is the relative angle of the training human body target, the posture element is the posture of the training human body target, and the dressing element is the dress of the training human body target. For example, in a plurality of training thermal images, the training human targets stand at different relative distances and at different relative angles, maintain a standing posture, sitting posture or prone posture, and wear garments corresponding to the first through fourth wear levels.
In an alternative embodiment, the convolutional neural network may include two convolutional pooling units, one flat layer, and two connection layers. The output layer is composed of a plurality of nodes or neurons, and the neurons or the nodes correspond to a plurality of gestures. The input of the convolutional neural network is unified into a 32 x 32 gray image through normalization and size adjustment, and the output of the convolutional neural network is a plurality of scores (action class of each output node corresponding to a feature) output by each output node. The score corresponds to the probability of occurrence of a certain action class, and the node with the highest probability represents the action in the input image.
More specifically, the first layer of the convolutional neural network is a single channel input image of size 32×32. Setting a convolution kernel as 3*3 and a step length as 2 in a first convolution pooling unit, and generating 32 characteristic graphs of 15 x 15 after the first layer convolution; further downsampling at the pooling layer by 2 x 2 reduces the size of each feature map to 7*7. Inputting the data into a second convolution pooling unit, setting a convolution kernel as 3*3 and a step length as 1, and generating 32 5*5 feature maps; further downsampling by 2 x 2 is performed at the pooling layer, reducing the size of each feature map to 2 x 2. After this, the neurons were flattened, eventually forming 128 neurons. The full-connection layer is composed of 128 neurons, and an output layer corresponding to at least six types of actions is further output. The total number of parameters to be learned in the convolutional neural network is 26854.
Training the convolutional neural network by using a training thermal image and a yolo v5 model. After model training, the model can be transplanted to a controller for operation. Other structures of convolutional neural networks may also be employed, and are not illustrated herein.
The trained convolutional neural network can identify and output the framed human body target to generate a human body infrared thermal image.
As shown in fig. 7, the human body infrared thermal image temperature detection section is configured to determine a target temperature of each pixel point in the human body infrared thermal image in the following manner.
The original output of the detector when the baffle of the uncooled infrared focal plane detector is opened is sampled, and is recorded as Raw14' by taking a 14-bit detector as an example. In an alternative embodiment, raw14' is the output of the detector pixel level readout circuit, such as one or more of the outputs.
The original output of the uncooled infrared focal plane detector when the shutter is closed is sampled, denoted by Raw14 "for the example of a 14-bit detector. In an alternative embodiment, raw14 "is the output of the detector pixel level readout circuit when the flap is closed, such as one or more of the outputs.
Baffle temperature T of sampling uncooled infrared focal plane detector 1 Baffle temperature T 1 Recorded by thermodynamic temperatureThe current ambient temperature is shown.
Invoking the first coefficient a and the second coefficient a
Determining a target temperature T of each pixel point in the human body infrared thermal image 0 Target temperature T 0 Recorded as thermodynamic temperature.
Target temperature T 0 Satisfy the following requirements
Δraw14＝a×T 0 4 -b×T 1 4
Wherein:
Δraw14＝Raw14′-Raw14″
the above formula is generated according to the steven boltzmann law: i.e. the radiance of the black body, i.e. the total radiated power of the various wavelengths emitted per unit area of the surface of the black body is proportional to the fourth power of its thermodynamic temperature T, while correcting the ambient temperature (in terms of the baffle temperature T 1 Record) and a shutter (i.e., detector shutter).
The manner in which the first coefficient a and the second coefficient b are generated will be described below with reference to fig. 8.
An uncooled infrared focal plane detector is used for collecting infrared thermal images of a plurality of test radiation sources, and any test radiation source has a corresponding set surface temperature.
The display temperature of the uncooled infrared focal plane detector when the baffle of each test radiation source is started and the display temperature of the uncooled infrared focal plane detector when the baffle of the uncooled infrared focal plane detector is closed are respectively acquired, and the temperature difference between the display temperature when the test radiation source is started and the display temperature when the test radiation source is closed is calculated. The one-to-one correspondence between the plurality of groups of set surface temperatures and the display temperature difference values can be obtained.
Considering the monomer blackness of the test radiation source, the temperature difference value is a linear relation with one-to-one correspondence between the original output difference values of the detectors. One of the temperature difference and the set surface temperature is taken as an abscissa, the other is taken as an ordinate, a coordinate system is established, the set surface temperature and the display temperature difference can be represented in the form of a plurality of points, and a calibration curve can be further obtained through linear fitting.
Inverse solution of the first step according to the calibration curveA coefficient a and a second coefficient b, the display temperature of the detector in the sampling process can be recorded as T 2 The first coefficient a and the second coefficient b of the inverse solution exist and are equal to the display temperature T of the detector in the sampling process 2 Satisfies a corresponding relationship of a=f (T 2 ) And b=f (T 2 ) The method comprises the steps of carrying out a first treatment on the surface of the Both fitting and inverse solution can be done by software, e.g. MatLab, etc. The solved first coefficient a and second coefficient b are constants.
As shown in fig. 9, in some embodiments of the present invention, the clothing amount ratio threshold condition may be obtained in the following manner.
A plurality of preset clothes scenes are set, and each preset clothes scene corresponds to one dressing amount grade. For example, four predetermined clothing scenes, namely, four predetermined clothing scenes corresponding to the first dressing level, the second dressing level, the third dressing level and the fourth dressing level respectively, are set, each of the four predetermined clothing scenes is pre-dressed by a tester according to the set dressing level, and the four predetermined clothing scenes can be represented by a, b, c and d.
A plurality of test infrared thermal images are sampled respectively.
And identifying and selecting a test human body target meeting a preset clothing scene in the test infrared thermal image, and generating the test human body infrared thermal image.
Determining a target temperature of each pixel point in the infrared thermal image of the human body to be tested, and screening a maximum pixel temperature value A in the target temperature t And calculates the average pixel temperature value B of the human body infrared thermal image t 。
Calculating the ratio C of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the human body t ,C t ＝B t /A t Thus, the clothing amount proportion threshold value corresponding to four preset clothing scenes can be obtained: c (C) ta ,C tb ,C tc And C td 。
And establishing a one-to-one correspondence relation between the average pixel temperature value and the maximum pixel temperature value in the tested human body infrared thermal image and the preset clothing scene, wherein the ratio between the average pixel temperature value and the maximum pixel temperature value in the tested human body infrared thermal image is the clothing amount proportion threshold value of the corresponding preset clothing scene.
As shown in fig. 11, in a preferred embodiment,
the dressing amount ratio threshold condition is obtained by:
a plurality of preset clothes scenes are set, and each preset clothes scene corresponds to one dressing amount grade. For example, four predetermined clothing scenes, that is, four predetermined clothing scenes corresponding to the first dressing level, the second dressing level, the third dressing level, and the fourth dressing level, respectively, are set, and each of the predetermined clothing scenes is pre-dressed by a tester according to the set dressing level.
A number of predetermined ambient temperatures are set, for example, four predetermined ambient temperatures 15 ℃, 20 ℃, 25 ℃ and 30 ℃ are set correspondingly.
A plurality of test infrared thermal images at each predetermined ambient temperature are sampled separately.
And identifying and selecting a test human body target meeting one of the preset clothes scenes in the test infrared thermal image, and generating the test human body infrared thermal image.
Determining the target temperature of each pixel point in the infrared thermal image of the human body, screening the maximum pixel temperature value in the target temperature, and calculating the average pixel temperature value of the infrared thermal image of the human body.
Calculating the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the human body to be tested, and marking as:
C 15a ；C 15b ；C 15c ；C 15d
C 20a ；C 20b ；C 20c ；C 20d
C 25a ；C 25b ；C 25c ；C 25d
C 30a ；C 30b ；C 30c ；C 30d
thus, a plurality of groups of one-to-one correspondence relation between the preset environment temperature and the specific value can be obtained.
And establishing a coordinate system by taking one of the average pixel temperature value and the maximum pixel temperature value in the infrared thermal image of the human body to be tested and the preset environment temperature as an abscissa and the other as an ordinate, wherein a plurality of groups of one-to-one correspondence relation between the preset environment temperature and the ratio can be represented by a plurality of points in the coordinate system.
Fitting corresponds to a threshold fitting curve in a predetermined clothing scene.
Inverse solving a threshold fitting function corresponding to a predetermined clothing scene according to a threshold fitting curve, more specifically, an inverse solution constant K a ；B a ；K b ；B b ；K c ；B c ；K d ；B d The method comprises the steps of carrying out a first treatment on the surface of the And obtaining a corresponding threshold fitting function:
C ta ＝K a ×t+B a ；
C tb ＝K b ×t+B b ；
C tc ＝K c ×t+B c ；
C td ＝K d ×t+B d ；
where t is the real-time ambient temperature.
When confirming the dressing grade, the dressing amount confirming part is preferably configured to firstly obtain the real-time environment temperature, and respectively substitute the real-time environment temperature into the four threshold fitting functions to obtain the dressing amount proportion threshold corresponding to the preset dressing scene so as to generate the preset dressing amount proportion threshold condition corresponding to the real-time environment temperature, thereby determining the dressing grade with optimal efficiency and improving the intelligence of the product.
In the description of the above embodiments, particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any changes or substitutions easily contemplated by those skilled in the art within the scope of the present invention should be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. An air conditioning device is characterized by comprising:
an infrared imaging section configured to generate an infrared thermal image in an indoor environment;
a human body recognition part configured to recognize and select a human body target in the infrared thermal image, and generate a human body infrared thermal image;
a human body infrared thermal image temperature detection part configured to determine a target temperature of each pixel point in the human body infrared thermal image, screen a maximum pixel temperature value in the target temperature, and calculate an average pixel temperature value of the human body infrared thermal image; and
and a dressing amount confirmation unit configured to confirm that the target dressing amount of the human body is a dressing level corresponding to the dressing amount ratio threshold condition when the ratio of the average pixel temperature value to the maximum pixel temperature value satisfies one of a plurality of preset dressing amount ratio threshold conditions.
2. An air conditioning unit according to claim 1, wherein,
the infrared imaging section configured to:
the original level data received by the uncooled infrared focal plane detector is restored into an original image with equal resolution according to the resolution of the uncooled infrared focal plane detector;
detecting and replacing bad points in the original image;
carrying out non-uniformity correction on the original image after the dead pixel replacement;
carrying out noise reduction and filtering treatment on the original image after the non-uniformity correction;
carrying out histogram processing on the original image subjected to noise reduction and filtering processing;
and generating the original image after the histogram processing into an infrared thermal image in the indoor environment.
3. An air conditioning unit according to claim 2, characterized in that,
the non-uniformity correction of the original image after the dead pixel replacement comprises the following steps:
the correction output Y satisfies:
Y＝A×(X-B)
wherein X represents the original output of the detector when the baffle of the uncooled infrared focal plane detector is opened, B represents the original output of the detector when the baffle of the uncooled infrared focal plane detector is closed, and A is the sensitivity correction coefficient of the uncooled infrared focal plane detector.
4. An air conditioning unit according to claim 1, wherein,
the human body identification part is configured to identify and select a human body target in the infrared thermal image by utilizing a convolutional neural network; the training sample of the convolutional neural network comprises a plurality of training thermal images, wherein any one training thermal image comprises a combination of one or more of a plurality of distance elements, angle elements, posture elements and dressing elements; the distance elements are the relative distance and the angle elements are the relative angles of the training human body targets, the posture elements are the postures of the training human body targets, and the dressing elements are the clothes of the training human body targets.
5. An air conditioning unit according to claim 1, wherein,
the human body infrared thermal image temperature detection section is configured to determine a target temperature of each pixel point in the human body infrared thermal image in the following manner:
the target temperature T 0 The method meets the following conditions:
Δraw14＝a×T 0 4 -b×T 1 4
wherein:
Δraw14＝Raw14′-Raw14″
in the above formula, T 1 The temperature of the baffle plate of the uncooled infrared focal plane detector is the target temperature T 0 And a baffle temperature T 1 The thermodynamic temperature is recorded, raw14 'is the original output of the uncooled infrared focal plane detector when the baffle of the uncooled infrared focal plane detector is opened, and Raw14' is the uncooled infrared focal plane detectorThe original output of the detector when the baffle is closed, a is a first coefficient, and b is a second coefficient.
6. An air conditioning unit according to claim 5, characterized in that,
the first coefficient a and the second coefficient b are obtained by:
an uncooled infrared focal plane detector is adopted to collect infrared thermal images of a plurality of test radiation sources, and any test radiation source has a corresponding set surface temperature;
respectively acquiring the display temperature of the uncooled infrared focal plane detector when the baffle of each test radiation source is opened and the display temperature of the uncooled infrared focal plane detector when the baffle of the uncooled infrared focal plane detector is closed, and calculating the temperature difference between the display temperature when the test radiation source is opened and the display temperature when the test radiation source is closed;
one of the temperature difference and the set surface temperature is taken as an abscissa, and the other is taken as an ordinate to establish a coordinate system fitting calibration curve;
and reversely solving a first coefficient a and a second coefficient b according to the calibration curve.
7. An air conditioning unit according to any of claims 1 to 6, characterized in that,
the dressing amount proportion threshold condition is obtained by the following steps:
setting a plurality of preset clothes scenes, wherein each preset clothes scene corresponds to a dressing amount grade;
respectively sampling a plurality of test infrared thermal images;
identifying and selecting a test human body target meeting a preset clothing scene in the test infrared thermal image, and generating a test human body infrared thermal image;
determining a target temperature of each pixel point in the human body infrared thermal image, screening a maximum pixel temperature value in the target temperature, and calculating an average pixel temperature value of the human body infrared thermal image;
calculating the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the human body to be tested;
and establishing a one-to-one correspondence relation between the average pixel temperature value and the maximum pixel temperature value in the tested human body infrared thermal image and the preset clothing scene, wherein the ratio between the average pixel temperature value and the maximum pixel temperature value in the tested human body infrared thermal image is the clothing amount proportion threshold value of the corresponding preset clothing scene.
8. An air conditioning unit according to claim 7, characterized in that,
further comprises:
and a dressing amount control section configured to perform air conditioning control based on the confirmed dressing level and the real-time ambient temperature.
9. An air conditioning unit according to any of claims 1 to 6, characterized in that,
the dressing amount proportion threshold condition is obtained by the following steps:
setting a plurality of preset clothes scenes, wherein each preset clothes scene corresponds to a dressing amount grade;
setting a plurality of preset environmental temperatures;
sampling a plurality of test infrared thermal images at each predetermined ambient temperature respectively;
identifying and selecting a test human body target meeting one of the preset clothes scenes in the test infrared thermal image, and generating a test human body infrared thermal image;
determining a target temperature of each pixel point in the human body infrared thermal image, screening a maximum pixel temperature value in the target temperature, and calculating an average pixel temperature value of the human body infrared thermal image;
calculating the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the human body to be tested;
establishing a coordinate system to fit a threshold fitting curve corresponding to a preset clothing scene by taking one of the ratio of the average pixel temperature value to the maximum pixel temperature value in the infrared thermal image of the tested human body and the preset environmental temperature as an abscissa and the other as an ordinate;
reversely solving a threshold fitting function corresponding to a preset clothing scene according to the threshold fitting curve;
acquiring a real-time environment temperature;
substituting the real-time environment temperature into a threshold fitting function to obtain a dressing amount proportion threshold corresponding to a preset clothing scene.
10. An air conditioning unit according to claim 9, characterized in that:
further comprises:
and a dressing amount control section configured to perform air conditioning control based on the confirmed dressing level and the real-time ambient temperature.
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