Intelligent light heating method and device

Abstract

The application relates to the technical field of illumination heating, and discloses an intelligent illumination heating method and device, which comprises the following steps: according to a pre-acquired target object surface thermal spot image, the temperature gradient and the optical characteristics of the target object surface are analyzed through a preset stage recognition model, and a first stage in which the target object is located is recognized; the light-heat demand and the energy state of the target object are analyzed through a preset illumination heating matching mechanism to perform light-heat coupling, corresponding illumination heating parameters are calculated; the illumination heating device is controlled to perform illumination heating on the target object, and the real-time state change of the target object is analyzed; the illumination heating parameters are optimized in real time through a preset parameter optimization model, and the illumination heating device is adjusted in real time; the application can improve the accuracy of the calculated illumination heating parameters, controls the illumination heating process by adjusting the illumination heating parameters in real time, and improves the illumination heating effect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of light heating, and more particularly to an intelligent light heating method and device. BACKGROUND

[0002] In the process of hatching poultry eggs, light heating technology is needed to regulate the hatching process of the eggs and improve the hatching effect. The current hatching equipment uses fixed temperature and light intensity, without considering the different needs of the embryo in the egg at different development stages for temperature and light intensity, resulting in poor hatching effect.

[0003] The prior art has the following problems: according to a single data and a fixed method to analyze the hatching stage of the eggs, the obtained hatching stage cannot reflect the current actual state of the eggs, resulting in inaccurate light heating parameter setting and affecting the light heating effect; in the light heating process, the light and heating parameters are set respectively, ignoring the correlation between light and heating, resulting in inaccurate light and heating parameters; in the light heating process, the state in the egg changes constantly, and the existing light heating control method lacks real-time adjustment of the light heating parameters according to the real-time state, resulting in poor light heating effect; to solve at least one of the above problems, the present application provides an intelligent light heating method and device. SUMMARY

[0004] In view of the deficiencies of the prior art, the purpose of the present application is to provide an intelligent light heating method and device, which can effectively solve the problems in the background art. The specific technical solution of the present application is as follows:

[0005] An intelligent light heating method, comprising:

[0006] According to the pre-acquired target object surface thermal spot image, the temperature gradient and optical properties of the target object surface are analyzed by a pre-set stage recognition model to identify the first stage in which the target object is located;

[0007] Based on the first stage, the light-heat demand and energy state of the target object are analyzed by a pre-set light heating matching mechanism for light-heat coupling to calculate corresponding light heating parameters;

[0008] The light heating parameters are used to control the light heating device to perform light heating on the target object, and the real-time state change of the target object is analyzed;

[0009] According to the real-time state change, the light heating parameters are optimized in real time by a pre-set parameter optimization model, and the light heating device is adjusted in real time to perform intelligent light heating on the target object.

[0010] Specifically, the first stage in which the target object is located is identified according to a pre-acquired thermal spot image of a surface of the target object, by analyzing temperature gradient and optical characteristics of the surface of the target object through a preset stage recognition model, and the first stage includes:

[0011] The temperature and light transmittance of the surface of the target object are collected by a preset sensor group, and a thermal spot image of the surface of the target object is obtained;

[0012] According to the thermal spot image, the temperature gradient and optical characteristics of the surface of the target object are analyzed through a preset stage recognition model to obtain fusion features;

[0013] Based on the fusion features, the first stage in which the target object is located is identified.

[0014] Specifically, according to the thermal spot image, the temperature gradient and optical characteristics of the surface of the target object are analyzed through a preset stage recognition model to obtain fusion features, and the fusion features include:

[0015] The temperature gradient field in the thermal spot image is calculated through a preset stage recognition model, and a temperature feature set is extracted from the temperature gradient field;

[0016] The thermal spot image is analyzed for optical characteristics, and an optical feature set is extracted;

[0017] The thermal spot image is subjected to wavelet transform, and a biological feature set is extracted;

[0018] The temperature feature set, the optical feature set, and the biological feature set are fused according to different channels to obtain fusion features.

[0019] Specifically, based on the first stage, the light-heat demand and energy state of the target object are analyzed through a preset light-heat matching mechanism to perform light-heat coupling, and corresponding light-heat parameters are calculated, and the light-heat coupling includes:

[0020] The first stage is analyzed according to a preset stage parameter mapping rule, and a corresponding first parameter is matched;

[0021] The light-heat demand and energy state of the target object are analyzed through a preset light-heat matching mechanism, and light-heat coupling is performed to generate a coupling matrix;

[0022] The real-time state of the target object is analyzed, the first parameter is compensated and corrected according to the real-time state, and a second parameter is obtained;

[0023] The coupling matrix and the second parameter are combined to generate corresponding light-heat parameters.

[0024] Specifically, the light-heat demand and energy state of the target object are analyzed through a preset light-heat matching mechanism, and light-heat coupling is performed to generate a coupling matrix, and the light-heat coupling includes:

[0025] construct a parameter coordinate system according to the first parameter, the preset light and heat matching mechanism analyzes the parameters and parameter weights of the target object, and obtains light and heat demand parameters and energy state parameters corresponding to the target object;

[0026] The light and heat demand parameters are split according to a plurality of preset dimensions, and the plurality of split light and heat demand parameters are weighted and fused according to the corresponding parameter weights to obtain a first fused parameter vector;

[0027] The energy state parameters are split according to a plurality of preset dimensions, and the plurality of split energy state parameters are weighted and fused according to the corresponding parameter weights to obtain a second fused parameter vector;

[0028] The first fused parameter vector and the second fused parameter vector are combined to perform matrix coupling operation to generate a coupling matrix.

[0029] Specifically, the coupling matrix and the second parameter are combined to generate corresponding light and heat parameters, including:

[0030] The coupling matrix is analyzed to construct a light and heat constraint;

[0031] A plurality of features are parsed from the second parameter, and the parsed feature dimensions are mapped to be consistent with the vector dimensions in the coupling matrix to obtain a second parameter feature vector;

[0032] The second parameter feature vector is optimized by the light and heat constraint to generate corresponding light and heat parameters.

[0033] Specifically, the light and heat parameters are used to control the light and heat device to perform light and heat on the target object, and the real-time state change of the target object is analyzed, including:

[0034] The light and heat device is controlled according to the light and heat parameters to perform light and heat on the target object;

[0035] The state data of the target object is collected in real time by a preset sensor group to obtain real-time state data;

[0036] According to the real-time state data, the temperature change and energy absorption of the target object are analyzed to obtain the real-time state change.

[0037] Specifically, according to the real-time state change, the light and heat parameters are optimized in real time by a preset parameter optimization model, and the light and heat device is adjusted in real time to intelligently perform light and heat on the target object, including:

[0038] The real-time state change is compared with the preset state to obtain a state deviation degree;

[0039] According to the state deviation degree, the illumination heating parameters are optimized in real time through a preset parameter optimization model to obtain updated illumination heating parameters;

[0040] The illumination heating device is adjusted in real time by using the updated illumination heating parameters to intelligently illuminate and heat the target object.

[0041] Specifically, according to the state deviation degree, the illumination heating parameters are optimized in real time through a preset parameter optimization model to obtain updated illumination heating parameters, including:

[0042] According to the state deviation degree, a candidate optimization parameter set for optimizing the illumination heating parameters is calculated through a preset parameter optimization model;

[0043] By analyzing the adjustment of the candidate optimization parameters on the state deviation degree, key optimization parameters are selected from the candidate optimization parameter set;

[0044] According to the key optimization parameters, the illumination heating parameters are optimized in real time to obtain updated illumination heating parameters.

[0045] An intelligent illumination heating device for implementing the intelligent illumination heating method, comprising:

[0046] A stage identification module analyzes the temperature gradient and optical properties of the target object surface based on a pre-acquired target object surface thermal spot image through a preset stage identification model to identify the first stage in which the target object is located;

[0047] A parameter calculation module analyzes the light-heat demand and energy state of the target object based on the first stage through a preset light-heat matching mechanism to perform light-heat coupling and calculate corresponding illumination heating parameters;

[0048] An illumination heating module controls the illumination heating device to illuminate and heat the target object by using the illumination heating parameters and analyzes the real-time state change of the target object;

[0049] An illumination heating optimization module optimizes the illumination heating parameters in real time through a preset parameter optimization model according to the real-time state change and adjusts the illumination heating device in real time to intelligently illuminate and heat the target object.

[0050] The beneficial effects of the present application: according to the target object surface thermal spot image analysis temperature characteristics and optical characteristics, identify the target object current stage, and analyze the light and heat demand and energy state of the target object current stage, through the correlation matching of light and heat coupling combined with light and heating parameters Corresponding light and heating parameters, improve the pertinence and effectiveness of light and heating parameter matching, at the same time, according to the real-time state change of the target object, the light and heating parameters are adjusted in real time, the light and heating process of the target object is controlled, the intelligent light and heating of the target object is realized, the accuracy of the calculated light and heating parameters is improved, and the light and heating process is controlled by adjusting the light and heating parameters in real time, and the light and heating effect is improved. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 The working flow chart of an intelligent light and heating method in an embodiment of the present application is shown in the figure.

[0052] Figure 2 The schematic diagram of the parameter coordinate system in the embodiment of the present application is shown in the figure.

[0053] Figure 3 The schematic diagram of the coupling matrix in the embodiment of the present application is shown in the figure.

[0054] Figure 4 The structural schematic diagram of an intelligent light and heating device in an embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0055] The present application will be further described in detail below in combination with the drawings and embodiments. Wherein the same parts are denoted by the same reference numerals. It should be noted that the words "front", "back", "left", "right", "up" and "down" used in the following description refer to the directions in the drawings, and the words "bottom surface" and "top surface", "inner" and "outer" refer to the directions towards or away from the geometric center of a particular part.

[0056] In the embodiments of the present application, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design presented as "exemplary" or "for example" in the embodiments of the present application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the words "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0057] Hereinafter, the terms "first", "second", etc. are used for the purpose of description only, and should not be construed as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise specified.

[0058] Reference Figure 1 As shown, the specific embodiment of the intelligent illumination heating method of the application includes:

[0059] S101, according to the pre-acquired target object surface thermal spot image, the temperature gradient and the optical characteristics of the target object surface are analyzed by the pre-set stage recognition model, and the first stage of the target object is recognized;

[0060] S102, based on the first stage, the light-heat demand and energy state of the target object are analyzed by the pre-set illumination heating matching mechanism to perform light-heat coupling, and the corresponding illumination heating parameters are calculated;

[0061] S103, the illumination heating device is controlled by the illumination heating parameters to perform illumination heating on the target object, and the real-time state change of the target object is analyzed;

[0062] S104, according to the real-time state change, the illumination heating parameters are optimized in real time by the pre-set parameter optimization model, and the illumination heating device is adjusted in real time to perform intelligent illumination heating on the target object.

[0063] In this embodiment, the thermal spot image of the egg surface is collected, the thermal spot image is analyzed, the temperature gradient is extracted, the optical characteristics of the egg are analyzed, the first stage of the egg is recognized, the light-heat demand required by the egg is determined based on the first stage, the initial energy state of the egg is combined, the light-heat coupling analysis is performed by the illumination heating matching mechanism, and the illumination heating parameters such as illumination intensity, heating time and illumination wavelength are calculated. The illumination heating device is controlled according to the calculated parameters to perform illumination heating on the egg, and the state change of the egg is collected in real time. The illumination heating parameters are optimized in real time, including adjusting the illumination intensity and the heating time, continuously monitoring and optimizing until the egg reaches the expected illumination heating effect. Compared with the traditional single illumination heating method for the egg, the illumination heating parameters are calculated simultaneously according to the current stage and the real-time state of the egg, and the illumination heating parameters are adjusted and optimized in real time, which can accurately illuminate and heat the egg, and improve the illumination heating effect.

[0064] In the embodiment, according to the pre-acquired target object surface thermal spot image, the temperature gradient and the optical characteristics of the target object surface are analyzed by a preset stage recognition model. The temperature gradient reflects the temperature difference of different positions on the object surface, and the optical characteristics include reflectivity, absorptivity and other characteristic parameters. The temperature gradient and the optical characteristics change with the growth stage of the object. The stage recognition model includes but is not limited to a random forest model. A large number of historical thermal spot images and corresponding growth stages of the target object are used to train the random forest model to obtain a pre-trained random forest model. The target object surface thermal spot image is input into the pre-trained random forest model, and the model outputs the first stage in which the target object is currently located. By identifying the current stage of the target object, the initial state of the target object can be accurately grasped, which provides a basis for the calculation of the light heating parameters, avoids improper light heating due to inaccurate judgment of the initial state of the object, and affects the normal growth process of the target object.

[0065] After determining the first stage in which the target object is located, a preset light heating matching mechanism is used to analyze the light quantity and heat required for the target object to achieve the expected light heating effect, to obtain light and heat requirements, analyze the energy level currently possessed by the target object to obtain an energy state, and perform light and heat coupling analysis based on the correlation between the light and heat requirements and the energy state, to calculate corresponding light heating parameters, including light intensity, heating time, light wavelength and other parameters. The light heating parameters calculated by the light and heat coupling are more in line with the actual needs of the target object, which can improve the efficiency and accuracy of light heating and avoid energy waste.

[0066] According to the calculated light heating parameters, the light heating device is controlled to perform light heating on the target object, and a detection device is used to monitor the state change of the target object in real time, including temperature change, surface optical characteristic change and the like. By monitoring the state change of the target object in the light heating process in real time, problems occurring in the light heating process can be found in time, which provides a state reference for optimization of the light heating parameters. If it is found that the temperature of the egg rises too fast, the heating parameters can be adjusted in time to prevent the egg from being overheated and affect the normal growth process of the egg.

[0067] Further, according to the real-time state change of the target object, the current light heating parameter is analyzed and optimized through a preset parameter optimization model, which includes but is not limited to a particle swarm optimization model. A large amount of historical state data is used to train the particle swarm optimization model to obtain a pre-trained particle swarm optimization model. The real-time state change of the target object and the expected light heating effect are input into the pre-trained particle swarm optimization model, and the model outputs the optimized light heating parameter. The light heating parameter is dynamically adjusted according to the real-time state of the target object, which can ensure that the light heating process is always in the best state, improve the quality and stability of the light heating, and avoid the situation of local over-illumination or uneven heating of the eggs during the light heating process of the eggs.

[0068] The present application analyzes the temperature characteristics and optical characteristics of the target object surface thermal spot image according to the target object, identifies the current stage of the target object, analyzes the light and heat demand and energy state of the current stage of the target object, matches the corresponding light heating parameter through the correlation of the light and heat coupling and the light heating parameter, improves the pertinence and effectiveness of the light heating parameter matching, and simultaneously adjusts the light heating parameter in real time according to the real-time state change of the target object, controls the light heating process of the target object, realizes the intelligent light heating of the target object, improves the accuracy of the calculated light heating parameter, controls the light heating process through real-time adjustment of the light heating parameter, and improves the light heating effect.

[0069] Further, according to the pre-acquired target object surface thermal spot image, the temperature gradient and optical characteristics of the target object surface are analyzed through a preset stage recognition model to identify the first stage of the target object, including:

[0070] S201, the temperature and transmittance of the target object surface are collected through a preset sensor group to obtain a thermal spot image of the target object surface;

[0071] S202, according to the thermal spot image, the temperature gradient and optical characteristics of the target object surface are analyzed through a preset stage recognition model to obtain a fusion feature;

[0072] S203, based on the fusion feature, the first stage of the target object is identified.

[0073] The embodiment collects temperature data and light transmittance data of the egg surface through a preset sensor group, generates a thermal spot image of the egg surface, inputs the thermal spot image into a preset stage recognition model, the model extracts temperature gradient features and optical property features from the thermal spot image, performs feature fusion processing on the temperature gradient features and the optical property features to obtain fusion features, and recognizes the first stage in which the target object is located according to the fusion features. Different types of features are fused to provide a more comprehensive feature basis for stage recognition of the target object, avoid one-sidedness of single feature data, and perform stage recognition on the target object based on the fusion features, which can improve the accuracy of the first stage recognition result of the egg and provide an initial basis for calculation of light heating parameters to ensure effectiveness of the light heating process.

[0074] In the embodiment, for light heating of the egg, the sensor group includes an infrared temperature sensor and a light transmittance sensor, the infrared temperature sensor collects the temperature of the egg surface, and the light transmittance sensor collects the light transmittance of different positions of the egg surface. The sensor group is installed at a position that can comprehensively cover the egg surface to collect data of each region of the egg. The collected temperature data and light transmittance data are superimposed and fused to convert the temperature data into different colors, the region with high temperature is red, and the region with low temperature is blue to generate a temperature image. The light transmittance data is set, the gray value of the high light transmittance is large, the gray value of the low light transmittance is small, and the gray values are superimposed on the temperature image to generate a thermal spot image of the egg surface. The temperature and light transmittance information of the egg surface can be obtained through cooperative collection of multiple sensors to generate a more complete thermal spot image and provide accurate data for stage recognition of the target object.

[0075] Specifically, according to the generated thermal spot image, a preset stage recognition model is used to analyze the temperature change rate in the thermal spot image to obtain temperature gradient information, analyze the light transmittance to obtain optical property information, extract features related to the temperature gradient and the optical property, and perform feature fusion on the temperature gradient features and the optical property features to obtain fusion features that can reflect the state of the target object. Through feature fusion, the temperature information and the optical information can be combined, compared with single temperature features or optical features, the fused features can more comprehensively reflect the state of the target object, and the accuracy of stage recognition of the target object is improved.

[0076] After obtaining the fusion features, the fusion features are compared with a preset feature template. Through analysis of the growth stage of the target object, corresponding feature templates are set according to different feature performances of different growth stages, the fusion features are compared with each feature template and the similarity is calculated, the stage corresponding to the feature template with the highest similarity is selected as the first stage in which the target object is located. The stage in which the target object is located is recognized through the fusion features, the current stage of the target object can be more accurately determined, and an initial state basis is provided for the light heating process of the target object.

[0077] Further, according to the thermal spot image, the temperature gradient and the optical characteristics of the target object surface are analyzed by a preset stage recognition model to obtain fusion features, including:

[0078] S301, calculating a temperature gradient field in the thermal spot image by a preset stage recognition model, and extracting a temperature feature set from the temperature gradient field;

[0079] S302, performing optical characteristic analysis on the thermal spot image to extract an optical feature set;

[0080] S303, extracting a biological feature set by wavelet transform on the thermal spot image;

[0081] S304, fusing the temperature feature set, the optical feature set and the biological feature set according to different channels to obtain fusion features.

[0082] In the embodiment, according to the thermal spot image, the temperature gradient field in the thermal spot image is calculated by a preset stage recognition model, the stage recognition model includes but is not limited to a neural network model, a large number of thermal spot images are used to train the neural network model to obtain a pre-trained neural network model, the thermal spot image is input into the pre-trained neural network model, the model calculates the temperature difference and the spatial distance between each pixel point and the surrounding pixel points in the thermal spot image to obtain the temperature gradient of the corresponding pixel point, and a temperature gradient field is constructed according to the temperature gradient distribution of each pixel point. A plurality of features are extracted from the temperature gradient field, including the maximum value, the minimum value, the average value, the variance of the temperature gradient, etc., and the plurality of extracted features are combined to form a temperature feature set. By constructing the temperature gradient field and extracting the corresponding temperature features, the temperature state of the target object can be analyzed in combination with the change degree and distribution trend of the temperature of the target object surface, and corresponding heating parameters can be set.

[0083] Specifically, by analyzing the reflection and absorption of different light rays on the surface of the target object, the optical characteristics of the target object are analyzed, the thermal spot image of the egg is converted into a format that can be analyzed for optical characteristics, including but not limited to RGB format, the optical characteristics of the converted RGB format image are analyzed, including statistical analysis of the gray value of different regions of the egg surface, calculation of the average value of different color channels, etc., and the corresponding optical features are extracted, including the maximum value, the minimum value, the average value of the gray value, the average value of each color channel, the standard deviation of the gray value, etc. The optical features are combined to form an optical feature set. The optical characteristics of the egg are related to the internal structure of the egg shell thickness, egg membrane state, etc. By analyzing the optical characteristics of the egg, the internal situation of the egg can be obtained, which provides data support for the stage recognition of the egg.

[0084] Further, the thermal spot image is subjected to wavelet transform to decompose into components of different frequencies, and the thermal distribution and optical characteristics of the egg surface will exhibit different biological features at different frequencies, including frequency characteristics corresponding to the eggshell texture, local frequency changes caused by the internal embryo, etc. In this embodiment, the thermal spot image of the egg is subjected to two-level wavelet decomposition using a db4 wavelet basis function to obtain low-frequency components and high-frequency components. The low-frequency components reflect the overall profile of the thermal spot image, and the high-frequency components reflect the detailed features of the thermal spot image. The energy value of the high-frequency components, the entropy value of different high-frequency components, the peak value, etc. are extracted to form a biological feature set. The extracted biological features can be used to obtain the characteristics of the egg as a biological object, and the biological features can be used to analyze the biological state of the egg to improve the accuracy of the egg stage recognition. The extracted temperature feature set, optical feature set and biological feature set are subjected to standardization processing, and the importance of each feature set for egg stage recognition is assigned a weight. The temperature features, optical features and biological features are fused according to different channels and corresponding weights to calculate the corresponding fusion features. By fusing the temperature information, optical information and biological information, the limitations of single feature analysis are avoided, and the fused features can more comprehensively and accurately reflect the state of the egg to improve the accuracy of the stage recognition result and provide an accurate state reference for the light heating parameter setting of the target object.

[0085] Further, based on the first stage, the light-heat demand and energy state of the target object are analyzed through a preset light-heat matching mechanism to perform light-heat coupling, and the corresponding light-heat parameters are calculated, including:

[0086] S401. Analyzing the first stage according to a preset stage parameter mapping rule to match a corresponding first parameter;

[0087] S402. Analyzing the light-heat demand and energy state of the target object through a preset light-heat matching mechanism and performing light-heat coupling to generate a coupling matrix;

[0088] S403. Analyzing the real-time state of the target object, compensating and correcting the first parameter according to the real-time state to obtain a second parameter;

[0089] S404. Generating corresponding light-heat parameters in combination with the coupling matrix and the second parameter.

[0090] The embodiment maps and matches to the corresponding first parameter according to the preset stage parameter mapping rule according to the first stage in which the identified target object is located, analyzes the light-heat demand and energy state in the egg growth stage, and performs light-heat coupling analysis in combination with the association of the light parameter and the heat parameter to generate a coupling matrix; meanwhile, the real-time state of the egg is analyzed, the first parameter is compensated and corrected in combination with the real-time state, the second parameter is obtained, the coupling coefficient in the coupling matrix is used to adjust and optimize the second parameter, and the light-heat parameter is obtained; by associating and coupling the light parameter and the heat parameter, more accurate light-heat parameters can be calculated in combination with the associated influence between light and heat, the parameters are corrected based on the real-time state of the target object, the flexibility of the light-heat process can be improved, and the light-heat effect is enhanced.

[0091] In the embodiment, the first parameter of the corresponding stage is matched according to the preset stage parameter mapping rule according to the first stage of the identified target object; the basic light-heat parameters required by the target object in different growth stages are different, the stage parameter mapping rule is set according to a large amount of historical parameter data of the target object in different stages, the corresponding basic light-heat parameters are set for each growth stage, the first parameter of the corresponding stage is obtained by matching the first stage of the target object in the stage parameter mapping rule; the basic light-heat parameters suitable for the current stage can be quickly matched for the target object through stage and parameter mapping, the efficiency of parameter determination is improved, and a basis is provided for parameter optimization.

[0092] Specifically, the light energy and heat energy required for the target object to achieve the expected heating effect are analyzed to obtain the light-heat demand, the energy level currently possessed by the target object is analyzed to obtain the energy state, the light-heat coupling is performed on the light-heat demand and the energy state through the preset light-heat matching mechanism in combination with the association between the light energy and the heat energy and the absorption and conversion efficiency of the target object to light and heat, and a coupling matrix is obtained, wherein the elements in the coupling matrix represent the association degree and the conversion efficiency between different light parameters and heat parameters; by analyzing the light-heat demand and the energy state, the light-heat energy required by the egg and the initial energy condition can be determined, the coupling matrix generated analyzes and quantifies the association of the light parameter and the heat parameter, and the light-heat parameter calculated in combination with the coupling matrix is more accurate.

[0093] Meanwhile, the real-time state of the target object is monitored, the state of the target object is monitored in real time by using a sensor group, real-time state data is obtained, the real-time state is analyzed in combination with the influence degree of the parameters on the state, the state difference between the real-time state and the expected state is corrected according to the corresponding compensation rule, a compensation correction amount is calculated, and the compensation correction amount is superimposed with the first parameter to obtain a second parameter; the first parameter is corrected in combination with the real-time state change of the target object, the light heating parameter is prevented from being inappropriate due to the real-time state difference, the parameter is more in line with the actual state of the target object, and the light heating effect is improved.

[0094] Specifically, the coupling matrix and the second parameter are combined, the coupling matrix reflects the correlation degree and conversion efficiency between the light parameter and the heat parameter, and the second parameter is a parameter corrected in real time, the information in the coupling matrix and the second parameter is combined to obtain a light heating parameter of the comprehensive light-heat coupling relationship and the real-time state, and the stability and reliability of the light heating effect are improved.

[0095] Further, the light-heat coupling of the light-heat demand and the energy state of the target object is analyzed by using the preset light heating matching mechanism, and the coupling matrix is generated, including:

[0096] S501, constructing a parameter coordinate system according to the first parameter, the preset light heating matching mechanism analyzes the parameters and parameter weights of the target object, and obtains the light-heat demand parameters and the energy state parameters corresponding to the target object;

[0097] S502, the light-heat demand parameters are split according to a plurality of preset dimensions, and the plurality of light-heat demand parameters after splitting are weighted and fused according to the corresponding parameter weights to obtain a first fusion parameter vector;

[0098] S503, the energy state parameters are split according to a plurality of preset dimensions, and the plurality of energy state parameters after splitting are weighted and fused according to the corresponding parameter weights to obtain a second fusion parameter vector;

[0099] S504, the first fusion parameter vector and the second fusion parameter vector are combined to perform matrix coupling operation to generate a coupling matrix.

[0100] As Figure 2As shown, a parameter coordinate system is constructed according to three dimensions of illumination intensity, heating time and illumination wavelength, the position of the first parameter in the parameter coordinate system is determined according to the corresponding parameter value in the first parameter, in the preset illumination and heating matching mechanism, the influence degree of each parameter on the light and heat demand and the energy state is analyzed, the parameter weight corresponding to the light and heat demand and the energy state is determined respectively, each parameter value is extracted from the first parameter, and the light and heat demand parameter and the energy state parameter are calculated according to the corresponding parameter weight; by constructing the parameter coordinate system and calculating the corresponding parameter weight, the corresponding parameter can be accurately extracted, which provides a basis for parameter coupling.

[0101] For the light and heat demand parameter, the light and heat demand parameter is split according to the preset multiple dimensions, the light and heat demand parameter is split according to the total energy, energy density and energy conversion efficiency, the corresponding weight is set for each dimension according to the calculation accuracy requirement of the light and heat demand parameter, the split light and heat demand parameter is weighted with the corresponding weight, and the light and heat demand parameter of each dimension after weighting calculation is combined to obtain a first fusion parameter vector; by splitting the light and heat demand parameter, the split parameter can reflect different aspects of the light and heat demand, and the first fusion parameter vector obtained after weighted fusion combines the information of each dimension, which is convenient for matrix operation in the coupling process.

[0102] For the energy state parameter, the energy state parameter is split according to the preset multiple dimensions, the energy state parameter is split according to the total energy, energy density and energy conversion efficiency, the corresponding weight is set for each dimension according to the calculation accuracy requirement of the energy state parameter, the split energy state parameter is weighted with the corresponding weight, and the energy state parameter of each dimension after weighting calculation is combined to obtain a second fusion parameter vector; by splitting the energy state parameter, the split parameter can reflect different aspects of the energy state, and the second fusion parameter vector obtained after weighted fusion combines the information of each dimension, which is convenient for matrix operation in the coupling process.

[0103] As shown in Figure 3 After the first fusion parameter vector and the second fusion parameter vector are calculated, the first fusion parameter vector is taken as a column vector and the second fusion parameter vector is taken as a row vector by vector outer product operation, and then multiplied to obtain a coupling matrix, the element value in the coupling matrix reflects the coupling degree of the light and heat demand and the energy state in different dimensions; by coupling operation, the light and heat demand and the energy state are associated and coupled, which provides a basis for analyzing the association between the illumination parameter and the heating parameter, and calculates more accurate illumination and heating parameters.

[0104] Further, the corresponding illumination and heating parameters are generated in combination with the coupling matrix and the second parameter, including:

[0105] S601, analyze the correlation strength of the light-heat demand parameters in the coupling matrix, and construct a light-heat constraint;

[0106] S602, parse a plurality of features from the second parameters, and map the parsed feature dimensions into a vector dimension consistent with the coupling matrix, to obtain a second parameter feature vector;

[0107] S603, optimize the second parameter feature vector by the light-heat constraint, and generate a corresponding light-heat parameter.

[0108] In this embodiment, the correlation strength of the light-heat demand parameters in the coupling matrix is analyzed, the element value in the coupling matrix reflects the correlation strength between the light-heat demand parameters, the larger the element value, the closer the correlation between the light-heat demand parameters. The mean and standard deviation of the element value are calculated by analyzing the element value in the coupling matrix, to determine the relationship range between the light-heat demand parameters, including the proportional limit of the light intensity and the heating time, and the corresponding relationship limit of the wavelength and the energy conversion efficiency. The determined relationship range is used as the light-heat constraint; the light-heat constraint is constructed to define the range for parameter optimization, to avoid unreasonable parameter calculation results, and to improve the accuracy and effectiveness of the calculated parameter results.

[0109] Specifically, the second parameters include a plurality of feature information, including but not limited to light intensity, heating time, and light wavelength. The second parameters are parsed according to the vector dimension of the coupling matrix, and mapped into three dimensions of energy total amount, energy density, and energy conversion efficiency. The mapped parameters are combined to obtain a second parameter feature vector; through dimension mapping, the second parameter feature vector is consistent with the dimension of the coupling matrix, which facilitates the optimization operation of the coupling matrix and speeds up the parameter optimization process.

[0110] The light-heat constraint limits the range of the parameters, and the second parameter feature vector is optimized by using the light-heat constraint. If it does not meet the requirements, the second parameter feature vector is adjusted according to the constraint condition, including but not limited to improving the wavelength to improve the corresponding energy conversion efficiency, so that the egg energy absorption is more efficient. After optimization by the light-heat constraint, the final light-heat parameter is obtained; the optimized light-heat parameter meets the initial characteristics of the second parameter and also meets the correlation relationship of the light-heat demand parameters, avoiding unreasonable parameter settings. The final obtained parameter can meet the heating demand of the egg and ensure the heating effect.

[0111] Further, the light-heat parameter is used to control the light-heat device to perform light-heat on the target object, and the real-time state change of the target object is analyzed, including:

[0112] S701, control the light-heat device to perform light-heat on the target object according to the light-heat parameter;

[0113] S702, real-time state data of the target object is collected by the preset sensor group, to obtain real-time state data;

[0114] S703, temperature change and energy absorption of the target object are analyzed according to the real-time state data, to obtain real-time state change.

[0115] In this embodiment, the light heating device is controlled to perform light heating on the target object according to the calculated light heating parameters, and the state of the target object is collected in real time by the sensor group, the temperature change and energy absorption of the target object are analyzed, and the real-time state change is obtained. By monitoring the real-time state change of the target object, heating abnormalities can be quickly found, and the light heating effect can be improved.

[0116] Specifically, the light heating parameters include light intensity, heating time, light wavelength, etc. The light heating device is controlled to perform light heating and heating on the target object by using the light heating parameters. The surface temperature and surface reflectivity of the target object during the heating process are collected in real time by using multiple sensors in the sensor group. The temperature change reflects the heating effect, and the reflectivity change reflects the energy absorption. The surface temperature and surface reflectivity are analyzed to obtain the real-time state change of the target object, which provides a state basis for subsequent parameter optimization.

[0117] Further, the light heating parameters are optimized in real time by a preset parameter optimization model according to the real-time state change, and the light heating device is adjusted in real time to intelligently heat the target object, including:

[0118] S801, the real-time state change is compared with a preset state to obtain a state deviation degree;

[0119] S802, the light heating parameters are optimized in real time by a preset parameter optimization model according to the state deviation degree, to obtain updated light heating parameters;

[0120] S803, the light heating device is adjusted in real time by using the updated light heating parameters to intelligently heat the target object.

[0121] In this embodiment, the real-time state change of the target object is compared with a preset state to obtain a state deviation degree. The preset state is a standard state parameter set according to the ideal heating process of the target object, including an expected temperature change curve, an energy absorption rate range, etc. The state data in the real-time state change is compared with the standard state parameter, and the difference is calculated to obtain the state deviation degree. By analyzing the state deviation degree, the difference between the actual heating process and the ideal heating state is quantitatively analyzed, which provides a basis for parameter optimization.

[0122] Specifically, according to the calculated state deviation degree, the light heating parameters are optimized in real time through a preset parameter optimization model, the parameter optimization model includes but is not limited to a multi-objective optimization model, a large number of historical light heating parameters are used to train the multi-objective optimization model to obtain a pre-trained multi-objective optimization model, the light heating parameters are optimized according to the calculated state deviation degree and the light heating parameters, the model outputs the optimized light heating parameters, and the updated light heating parameters are obtained; the light heating parameters are optimized according to the state deviation degree, the accuracy of the parameter optimization result can be improved, and the optimized parameters can improve the light heating effect.

[0123] Further, the running state of the light heating device is adjusted according to the updated light heating parameters, so that the light heating device operates according to the updated light heating parameters. The state change of the target object can be responded in real time by adjusting the device in real time, the accumulation of light heating deviation caused by fixed parameters is avoided, the light heating process is ensured to be in the optimal state at all times, and the adaptability and effectiveness of intelligent light heating are improved.

[0124] Further, the light heating parameters are optimized in real time through a preset parameter optimization model according to the state deviation degree to obtain updated light heating parameters, including:

[0125] S901, according to the state deviation degree, a candidate optimization parameter set for optimizing the light heating parameters is calculated through a preset parameter optimization model;

[0126] S902, the key optimization parameters are selected from the candidate optimization parameter set by analyzing the adjustment of the candidate optimization parameters to the state deviation degree;

[0127] S903, the light heating parameters are optimized in real time according to the key optimization parameters to obtain updated light heating parameters.

[0128] In this embodiment, the state deviation degree of the target object reflects the gap between the actual state of the target object and the preset state. According to the state deviation degree, the light heating parameters are optimized through a preset parameter optimization model, the parameter optimization model is a multi-objective optimization model, and the optimization target is set to include a 3%~5% increase in light intensity and a 10 minutes~30 minutes increase in heating time. According to the set optimization target, the light heating parameters are optimized to generate a plurality of parameter combinations in the set range to obtain a candidate optimization parameter set. By optimizing the parameters, the limitations of a single adjustment scheme can be avoided, more choices are provided for the selection of optimal parameters, the flexibility and reliability of parameter optimization are improved, and it is ensured that the most suitable adjustment scheme for the current state can be found.

[0129] Specifically, candidate optimization parameters in a candidate optimization parameter set are analyzed, each candidate optimization parameter has different adjustment effects on the state deviation degree, by analyzing the adjustment and improvement of the state deviation degree of each candidate optimization parameter in the simulated light heating environment, the parameter that can minimize the state deviation degree and has less energy consumption is screened out to obtain the key optimization parameter; by screening out the key optimization parameter, the state deviation can be improved to the greatest extent, unnecessary energy consumption can be reduced, and the effectiveness of the parameter optimization process can be improved. The original light heating parameter is replaced by the key optimization parameter to optimize the light heating parameter in real time to obtain an updated light heating parameter; by updating and optimizing the light heating parameter, the effectiveness of the updated parameter can be improved, the target object can quickly reach the preset state in the light heating process, and the effectiveness and stability of the light heating can be improved.

[0130] As shown in Figure 4 An intelligent light heating device for implementing an intelligent light heating method, comprising:

[0131] A stage identification module analyzes the temperature gradient and optical properties of the target object surface according to the pre-acquired target object surface thermal spot image, identifies the first stage of the target object through a preset stage identification model, and identifies the first stage of the target object.

[0132] A parameter calculation module analyzes the light-heat demand and energy state of the target object through a preset light heating matching mechanism based on the first stage, performs light-heat coupling, and calculates the corresponding light heating parameter.

[0133] A light heating module uses the light heating parameter to control the light heating device to perform light heating on the target object, and analyzes the real-time state change of the target object.

[0134] A light heating optimization module optimizes the light heating parameter in real time through a preset parameter optimization model according to the real-time state change, and adjusts the light heating device in real time to intelligently light heat the target object.

[0135] In this embodiment, the stage recognition module analyzes the pre-acquired target object surface thermal spot image through a preset stage recognition model, extracts the temperature gradient and optical characteristic information in the thermal spot image, and thus recognizes the first stage in which the target object is currently located; the stage in which the target object is located provides a basis for calculation of the light heating parameter, and reasonable initial parameters are set according to the current state of the target object; the parameter calculation module, based on the first stage determined by the stage recognition module, analyzes the light-heat demand and energy state of the target object through a preset light heating matching mechanism, calculates the corresponding light heating parameter through light-heat coupling, and the parameter calculated in combination with the current state of the target object can meet the actual demand of the target object, thereby improving the pertinence and efficiency of light heating of the target object.

[0136] Specifically, the light heating module controls the light heating device to perform light heating on the target object according to the light heating parameter obtained by the parameter calculation module, and analyzes the state change of the target object in the heating process in real time, including temperature change, energy absorption, etc.; the light heating device is controlled through the light heating parameter, which can ensure that the heating process is performed according to the preset parameter, and the state change of the target object is monitored in real time, which facilitates real-time adjustment of the light heating state of the light heating device and improves the light heating effect of the target object. The light heating optimization module optimizes the light heating parameter in real time through a preset parameter optimization model according to the real-time state change of the target object analyzed by the light heating module, and adjusts the heating state of the light heating device in real time, thereby realizing intelligent light heating of the target object. Through dynamic adaptation to the state change of the target object, it can ensure that the heating process is always in the best state, improve the heating quality and stability, and in the heating process of eggs, if the temperature rises too fast, the parameters can be optimized in time, the device can be adjusted, and the expected effect can be ensured to ensure uniform heating of the eggs.

[0137] The above is only the preferred embodiment of the present application, and the protection scope of the present application is not limited to the above-mentioned embodiments. Any technical solution falling within the scope of the present application shall be considered as falling within the protection scope of the present application. It should be noted that, for ordinary skilled persons in the art, some improvements and refinements without departing from the principles of the present application shall also be considered as falling within the protection scope of the present application.

Claims

1. A method of intelligent light and heat, characterized in that, The method comprises the following steps: According to the pre-acquired target object surface thermal spot image, the temperature gradient and optical characteristics of the target object surface are analyzed by a pre-set stage recognition model to identify the first stage in which the target object is located; According to the pre-set stage parameter mapping rule, the first stage is analyzed, and the corresponding first parameter is matched; According to the first parameter, a parameter coordinate system is constructed, and a pre-set light heating matching mechanism is used to analyze the parameters and parameter weights of the target object to obtain the light-heat demand parameters and energy state parameters corresponding to the target object; The light-heat demand parameters are split according to the pre-set multiple dimensions, and the split multiple light-heat demand parameters are weighted and fused according to the corresponding parameter weights to obtain a first fusion parameter vector; The energy state parameters are split according to the pre-set multiple dimensions, and the split multiple energy state parameters are weighted and fused according to the corresponding parameter weights to obtain a second fusion parameter vector; The first fusion parameter vector and the second fusion parameter vector are combined for matrix coupling operation, and a coupling matrix is generated by combining the correlation between light energy and heat energy and the absorption and conversion efficiency of the target object to light-heat; The real-time state of the target object is analyzed, and the first parameter is compensated and corrected according to the real-time state to obtain a second parameter; The correlation strength of the light-heat demand parameters in the coupling matrix is analyzed, and a light-heat constraint is constructed; From the second parameter, multiple features are parsed, and the parsed feature dimensions are mapped to be consistent with the vector dimensions in the coupling matrix to obtain a second parameter feature vector; The second parameter feature vector is optimized by the light-heat constraint to generate corresponding light heating parameters; The light heating parameters are used to control the light heating device to perform light heating on the target object, and the real-time state change of the target object is analyzed; According to the real-time state change, the light heating parameters are optimized in real time by a pre-set parameter optimization model, and the light heating device is adjusted in real time to intelligently light heat the target object.

2. The method of claim 1, wherein the method further comprises: According to the pre-acquired target object surface thermal spot image, the temperature gradient and optical characteristics of the target object surface are analyzed by a pre-set stage recognition model to identify the first stage in which the target object is located, which comprises: The temperature and transmittance of the target object surface are collected by a pre-set sensor group to obtain a thermal spot image of the target object surface; According to the thermal spot image, the temperature gradient and optical characteristics of the target object surface are analyzed by a pre-set stage recognition model to obtain a fusion feature; Based on the fusion feature, the first stage in which the target object is located is identified.

3. The method of claim 2, wherein the method further comprises: According to the thermal spot image, the temperature gradient and optical characteristics of the target object surface are analyzed by a pre-set stage recognition model to obtain a fusion feature, which comprises: The temperature gradient field in the thermal spot image is calculated by a pre-set stage recognition model, and a temperature feature set is extracted from the temperature gradient field; The optical characteristics of the thermal spot image are analyzed, and an optical feature set is extracted; The biological feature set is extracted by wavelet transform on the thermal spot image; The temperature feature set, the optical feature set and the biological feature set are fused according to different channels to obtain fused features.

4. The method of claim 1, wherein the method further comprises: The illumination heating device is controlled to perform illumination heating on the target object according to the illumination heating parameters, and real-time state change of the target object is analyzed, including: The illumination heating device is controlled to perform illumination heating on the target object according to the illumination heating parameters; Real-time state data of the target object is collected through a preset sensor group to obtain real-time state data; According to the real-time state data, temperature change and energy absorption of the target object are analyzed to obtain real-time state change.

5. The method of claim 1, wherein the method further comprises: According to the real-time state change, the illumination heating parameters are optimized in real time through a preset parameter optimization model, and the illumination heating device is adjusted in real time to intelligently perform illumination heating on the target object, including: The real-time state change is compared with a preset state to obtain a state deviation degree; According to the state deviation degree, the illumination heating parameters are optimized in real time through a preset parameter optimization model to obtain updated illumination heating parameters; The illumination heating device is adjusted in real time according to the updated illumination heating parameters to intelligently perform illumination heating on the target object.

6. The method of claim 5, wherein the method further comprises: According to the state deviation degree, the illumination heating parameters are optimized in real time through a preset parameter optimization model to obtain updated illumination heating parameters, including: According to the state deviation degree, a candidate optimization parameter set for optimizing the illumination heating parameters is calculated through a preset parameter optimization model; By analyzing adjustment of the candidate optimization parameters on the state deviation degree, key optimization parameters are selected from the candidate optimization parameter set; According to the key optimization parameters, the illumination heating parameters are optimized in real time to obtain updated illumination heating parameters.

7. A smart light heating device, characterized in that, An intelligent illumination heating method is used to implement any one of claims 1-6, including: A stage identification module analyzes temperature gradient and optical characteristics of the target object surface through a preset stage identification model according to a pre-acquired target object surface thermal spot image to identify a first stage in which the target object is located. The parameter calculation module analyzes the first stage according to a preset stage parameter mapping rule, and matches a corresponding first parameter; a parameter coordinate system is constructed according to the first parameter; a preset light and heat matching mechanism analyzes the parameters and parameter weights of the target object, and obtains light and heat demand parameters and energy state parameters corresponding to the target object; the light and heat demand parameters are split according to a plurality of preset dimensions, the split light and heat demand parameters are weighted and fused according to corresponding parameter weights, and a first fused parameter vector is obtained; the energy state parameters are split according to a plurality of preset dimensions, the split energy state parameters are weighted and fused according to corresponding parameter weights, and a second fused parameter vector is obtained; matrix coupling operation is performed in combination with the first fused parameter vector and the second fused parameter vector, a coupling matrix is generated in combination with the correlation between light energy and heat energy and the absorption and conversion efficiency of the target object to light and heat; the real-time state of the target object is analyzed, the first parameter is compensated and corrected according to the real-time state, and a second parameter is obtained; the correlation strength of the light and heat demand parameters in the coupling matrix is analyzed, and a light and heat constraint is constructed; a plurality of features are parsed from the second parameter, and the parsed feature dimensions are mapped to be consistent with the vector dimensions in the coupling matrix, and a second parameter feature vector is obtained; the second parameter feature vector is optimized through the light and heat constraint, and corresponding light and heat parameters are generated; The light and heat module controls the light and heat device to perform light and heat on the target object by using the light and heat parameters, and analyzes the real-time state change of the target object; The light and heat optimization module optimizes the light and heat parameters in real time through a preset parameter optimization model according to the real-time state change, and adjusts the light and heat device in real time to intelligently perform light and heat on the target object.

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