An Internet of Things control method and system for the operating parameters of a cremator

Abstract

The present invention relates to the field of artificial intelligence control, and proposes an Internet of Things regulation method and system for the operating parameters of a cremator. By establishing an Internet of Things architecture around the cremator equipment, the operating data of the cremator is visualized at the Internet of Things central end to achieve more intuitive data feedback. A parameter steady-state analysis algorithm and a thermal image analysis algorithm are designed for the Internet of Things central end to respectively judge the operating states of different types of cremator operating data, enhancing the correlation between the data of the Internet of Things central end and the user terminal during regulation, and further improving the operating and regulation efficiency of the cremator. Then, a user terminal comprehensive regulation algorithm is designed for the user terminal, enhancing the data connection between user terminal nodes and within user terminal nodes in the Internet of Things architecture, and improving the parameter fine-tuning and steady-state maintenance performance of all devices in the user terminal nodes. The present invention improves the operating stability and balance of the cremator.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence control, and particularly to an Internet of Things regulation method and system for the operating parameters of a cremator. Background Art

[0002] With the rapid development of industrial technology, the requirements for mechanical equipment have gradually increased. As an important part of the funeral industry, cremators naturally need to meet higher performance requirements, especially in the field of control and regulation of cremators.

[0003] In the prior art, for the control and regulation of cremators, after being collected by a single sensor, manual operation is often used for operation control and parameter adjustment. This control and regulation method not only has huge costs, but also has too low precision and response efficiency in control and regulation, and cannot meet the requirements of automation and intelligence. The existing automatic control only performs prefabricated adjustment according to a single data parameter, ignoring the correlation between data, and it is difficult to cope with the complex situations during the operation of the cremator, resulting in continuous fluctuations in the working state of the cremator, which is difficult to maintain stably. While causing low performance efficiency, it will also damage the machine and pose a safety hazard to the staff.

[0004] Therefore, how to design a regulation method for a cremator to cope with the complex situations during the operation of the cremator and maintain the stable operation of the cremator has become an urgent problem to be solved. Summary of the Invention

[0005] Based on this, the Internet of Things regulation method and system for the operating parameters of a cremator provided by the present invention establish an Internet of Things architecture around the cremator equipment, visualize the operating data of the cremator at the Internet of Things central end to achieve more intuitive data feedback, design a parameter steady-state analysis algorithm and a thermographic image analysis algorithm for the Internet of Things central end, respectively judge the operating states of different types of cremator operating data. The parameter steady-state analysis algorithm analyzes and judges the stability of the cremator operation from the numerical orientation to quickly cope with the problem that the working state of the cremator is prone to continuous fluctuations during operation and improve the operating performance of the cremator. The thermographic image analysis algorithm analyzes the balance of the cremator operation from the spatial orientation to quickly cope with the complex internal situations during the operation of the cremator. The Internet of Things central end associates and regulates different guiding cremator adjustment schemes to strengthen the correlation between data during regulation between the Internet of Things central end and the user terminal, further improve the operation and regulation efficiency of the cremator, and then design a user terminal comprehensive regulation algorithm at the user terminal to enhance the data connection between user terminal nodes and within user terminal nodes in the Internet of Things architecture, improve the parameter fine-tuning and steady-state maintenance performance of all devices in the user terminal nodes, and the present invention improves the operating stability and balance of the cremator.

[0006] An Internet of Things control method for the operating parameters of a cremator, comprising:

[0007] Collecting the operating data of the cremator and performing preprocessing;

[0008] Performing visual image conversion based on the preprocessed operating data of the cremator to obtain a cremator operating status image, where the visual image conversion includes operating data function image conversion and operating data thermography conversion, and the cremator operating status image includes a cremator operating status function image and a cremator operating status thermography image;

[0009] Performing an operating status judgment on the cremator operating status image according to a parameter steady-state analysis algorithm and a thermography analysis algorithm to obtain a cremator operating status analysis report, and then retrieving a solution from a control strategy database according to the cremator operating status analysis report to obtain a central regulation solution. The parameter steady-state analysis algorithm is used to eliminate function image noise and analyze and judge the fluctuation state of the function image, and the thermography analysis algorithm is used to locate different thermography regions and analyze and judge the distribution state of the thermography regions;

[0010] Performing cremator operation control according to the central regulation solution and feeding back the execution result of the cremator operation control to a cloud database.

[0011] In summary, the above-mentioned Internet of Things (IoT) regulation method for the operating parameters of a cremator establishes an IoT architecture around the cremator equipment, visualizes the operating data of the cremator at the IoT central end to achieve more intuitive data feedback, designs a parameter steady-state analysis algorithm and a thermal image analysis algorithm for the IoT central end to respectively judge the operating states of the operating data of different types of cremators. The parameter steady-state analysis algorithm analyzes and judges the stability of the cremator operation from the numerical orientation to quickly address the problem that the working state of the cremator is prone to continuous fluctuations during operation, improving the operating performance of the cremator. The thermal image analysis algorithm analyzes the balance of the cremator operation from the spatial orientation to quickly address the complex internal conditions during the cremator operation. The IoT central end correlates and regulates the cremator adjustment schemes with different orientations to strengthen the data correlation between the IoT central end and the user terminal during regulation, further improving the operation and regulation efficiency of the cremator. Then, a user terminal comprehensive regulation algorithm is designed for the user terminal to enhance the data connection between the user terminal nodes and within the user terminal nodes in the IoT architecture, improving the parameter fine-tuning and steady-state maintenance performance of all devices in the user terminal nodes. The present invention improves the operating stability and balance of the cremator. Specifically, the operating data of the cremator is collected and preprocessed to improve the reliability of the parameters. According to the preprocessed operating data of the cremator, a visual image conversion is performed to obtain the cremator operating state image. The visual image conversion includes the conversion of the operating data function image and the conversion of the operating data thermal image. The cremator operating state image includes the cremator operating state function image and the cremator operating state thermal image, realizing visual feedback and making the feedback of the cremator operating state more intuitive. According to the parameter steady-state analysis algorithm and the thermal image analysis algorithm, the operating state of the cremator operating state image is judged to obtain the cremator operating state analysis report. Then, according to the cremator operating state analysis report, a scheme search is performed on the regulation strategy database to obtain the central regulation scheme. The parameter steady-state analysis algorithm is used to eliminate the noise of the function image and analyze and judge the fluctuation state of the function image. The thermal image analysis algorithm is used to locate different thermal regions and analyze and judge the distribution state of the thermal regions to analyze the balance of the cremator operation to quickly address the complex internal conditions during the cremator operation. The IoT central end correlates and regulates the cremator adjustment schemes with different orientations to strengthen the data correlation between the IoT central end and the user terminal during regulation, further improving the operation and regulation efficiency of the cremator. According to the central regulation scheme, the operation of the cremator is regulated, and the execution result of the cremator operation regulation is fed back to the cloud database. The present invention improves the operating stability and balance of the cremator.

[0012] Further, the step of performing a visual image conversion according to the preprocessed operating data of the cremator to obtain the cremator operating state image specifically includes:

[0013] Divide the pre - processed operation data of the cremator into parametric operation data and image - type operation data;

[0014] Retrieve the corresponding function expression in the preset function database according to the parameter type, so as to generate a function image for the parametric operation data according to the function expression to obtain the function image of the operation state of the cremator. The function image generation includes generating the function image of the temperature parametric operation data. The specific algorithm for generating the function image of the temperature parametric operation data is as follows:

[0015] ,

[0016] Among them, represents the temperature parametric operation data, represents the time data, represents the internal heat conduction coefficient of the cremator furnace, represents the Laplace operator;

[0017] Extract the channel images from the image - type operation data according to the color channels. The color channels include the red channel, the green channel and the blue channel. Extract the pixel channel values of each corresponding channel image and perform pixel value weighting processing to obtain the thermal image of the operation state of the cremator. The specific formula for the pixel value weighting processing is as follows:

[0018] ,

[0019] Among them, represents the pixel value of a single pixel point, and respectively represent the pixel weights of the minimum value and the maximum value, and respectively represent the minimum - value and maximum - value functions, respectively represent the pixel channel values of a single pixel point on the three color channels.

[0020] Furthermore, the steps of judging the operation state of the cremator according to the parameter steady - state analysis algorithm and the thermal image analysis algorithm for the operation state image of the cremator to obtain the operation state analysis report of the cremator specifically include:

[0021] Denoise the function image of the operation state of the cremator according to the denoising algorithm. The specific formula of the denoising algorithm is as follows:

[0022] ,

[0023] Among them, represents the function value after denoising the function image of the operation state of the cremator, and respectively represent the width and height of the denoising window size and respectively represent the discrete values of the abscissa and ordinate of the function value and respectively represent the abscissa and ordinate of the function value

[0024] Then, according to the parameter steady-state analysis algorithm, the operating state of the cremator operating state function image is judged to obtain a first operating state analysis report of the cremator. The specific formula of the parameter steady-state analysis algorithm is as follows:

[0025] ,

[0026] ,

[0027] ,

[0028] wherein represents the function value after denoising of the cremator operating state function image represents the mean value of the function value after denoising of the cremator operating state function image represents the function fluctuation value of the cremator operating state function image represents the number of function points represents the ordinal number of the function point

[0029] Furthermore, the steps of judging the operating state of the cremator operating state image according to the parameter steady-state analysis algorithm and the thermal image analysis algorithm to obtain a cremator operating state analysis report further include:

[0030] Calculate the temperature values of all pixel points in the thermal image of the cremator operating state, and then calibrate the temperature values according to the pixel values of the pixel points after grayscale processing, so as to divide the area of the thermal image of the cremator operating state into a high temperature area, a rated temperature area, and a low temperature area. The specific algorithm for the area division is as follows:

[0031] ,

[0032] wherein represents the pixel area of the thermal image of the cremator operating state , , respectively represent the high temperature area, the rated temperature area, and the low temperature area represents the temperature value of the pixel points in the area and respectively represent the lowest temperature threshold and the highest temperature threshold of the rated temperature of the cremator;

[0033] Judging the operating state of a single area in the high-temperature area, the rated-temperature area, and the low-temperature area respectively according to the thermal image analysis algorithm, and the specific thermal image analysis algorithm is as follows:

[0034] ,

[0035] ,

[0036] ,

[0037] Among them, represents the basic prediction value of the temperature fluctuation change in a single area, represents the correction value of the temperature fluctuation change in a single area, represents the pixel area change value, represents the area temperature change value, represents the deviation value, represents the correction slope parameter, represents the standard rated temperature value of the cremator operation, represents the edge temperature value of a single area, represents the air temperature value inside the cremator, represents the air thermal conductivity inside the cremator, represents the correction weight, represents the refined prediction value of the temperature fluctuation change in a single area;

[0038] Obtain the refined prediction values of the temperature fluctuation changes in all areas to obtain the second operating state analysis report of the cremator.

[0039] Furthermore, after the steps of obtaining the first operating state analysis report of the cremator and obtaining the second operating state analysis report of the cremator, the following steps are also included:

[0040] Perform key-value matching operations according to the keywords in the first operating state analysis report of the cremator, and pair the parameter adjustment values in the control strategy database according to the retrieval keys corresponding to the keywords to screen the adjustment operation instruction set with the largest number of parameter adjustment items;

[0041] Generate a parameter adjustment plan according to the adjustment operation instruction set;

[0042] Or, according to the positioning information and temperature fluctuation change information of all pixel points in the second operating state analysis report of the cremator, locate the spatial area inside the cremator to be temperature-controlled to obtain the distribution information of the area to be controlled;

[0043] Then retrieve the relevant control instructions for the area to be controlled in the control strategy database according to the distribution information of the area to be controlled;

[0044] After obtaining the relevant control instruction set, set the control distribution value corresponding to the area to be controlled according to the refined prediction value of the regional temperature fluctuation change in the second operating state analysis report of the cremator, so as to obtain the distribution adjustment plan.

[0045] Further, the step of performing cremator operation control according to the central adjustment plan and feeding back the execution result of the cremator operation control to the cloud database specifically includes:

[0046] According to the central adjustment plan, obtain the control instructions for the temperature parameters and temperature control parameters, so as to perform cremator operation control according to the adaptive fuzzy adjustment network. The optimization adjustment algorithm of the adaptive fuzzy adjustment network is as follows:

[0047] ,

[0048] ,

[0049] Among them, represents the error cost value, represents the control predetermined output value, represents the control actual output value, represents the time step, represents the membership function center value, represents the learning rate parameter;

[0050] Feed back the execution result of the cremator operation control to the cloud database;

[0051] If it is determined that the cremator is in a dangerous operating state, perform emergency control of the cremator according to the preset safety emergency rules, and perform multi-terminal alarms and record the backup of the dangerous operating information.

[0052] Further, after the step of performing visual image conversion on the preprocessed cremator operation data to obtain the cremator operation status image, it further includes:

[0053] Perform user terminal adjustment judgment according to the cremator operation status image;

[0054] If it is determined that the current cremator operation status is in a non-adjustable state of the user terminal, the user terminal database generates a central adjustment request report according to the non-adjustable type to wake up the control strategy database of the Internet of Things central hub and perform operation status judgment;

[0055] If it is determined that the current cremator operation status is in an adjustable state of the user terminal, the user terminal database performs comprehensive control on the target cremator according to the user terminal comprehensive control algorithm. The specific user terminal comprehensive control algorithm is as follows:

[0056] ,

[0057] wherein, represents the velocity field, represents the scalar pressure, represents the external force, represents the number of components, = (1, 2, 3), represents the spatial variable, represents the time data.

[0058] An Internet of Things control system for the operating parameters of a cremator proposed by the present invention includes:

[0059] An acquisition module, configured to acquire the operating data of the cremator and perform preprocessing;

[0060] A visualization conversion module, configured to perform visualization image conversion according to the preprocessed operating data of the cremator to obtain a cremator operating state image, where the visualization image conversion includes operating data function image conversion and operating data thermal image conversion, and the cremator operating state image includes a cremator operating state function image and a cremator operating state thermal image;

[0061] A central analysis module, configured to perform operating state judgment on the cremator operating state image according to a parameter steady-state analysis algorithm and a thermal image analysis algorithm to obtain a cremator operating state analysis report, and then retrieve a solution from a control strategy database according to the cremator operating state analysis report to obtain a central adjustment solution, where the parameter steady-state analysis algorithm is used to eliminate function image noise and analyze and judge the fluctuation state of the function image, and the thermal image analysis algorithm is used to locate different thermal regions and analyze and judge the distribution state of the thermal regions;

[0062] A control module, configured to perform cremator operation control according to the central adjustment solution and feedback the execution result of the cremator operation control to a cloud database.

[0063] The present invention also provides a storage medium storing one or more programs, and when the programs are executed by a processor, the Internet of Things control method for the operating parameters of a cremator as described above is implemented.

[0064] The present invention also provides a computer device, where the computer device includes a memory and a processor, and:

[0065] The memory is used to store a computer program;

[0066] The processor is configured to implement the Internet of Things control method for the operating parameters of a cremator as described above when executing the computer program stored in the memory. Brief Description of the Drawings

[0067] Figure 1 The flowchart of the Internet of Things control method for the operating parameters of the cremator proposed in the first embodiment of the present invention;

[0068] Figure 2 The flowchart of the Internet of Things control method for the operating parameters of the cremator proposed in the second embodiment of the present invention;

[0069] Figure 3 The structural schematic diagram of the Internet of Things control method for the operating parameters of the cremator proposed in the third embodiment of the present invention.

[0070] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. Specific Embodiments

[0071] For the convenience of understanding the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0072] It should be noted that when an element is referred to as being "fixedly installed on" another element, it can be directly on the other element or there may also be an intermediate element. When an element is considered to be "connected to" another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration.

[0073] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0074] Please refer to Figure 1 , which shows the flowchart of the Internet of Things control method for the operating parameters of the cremator proposed in the first embodiment of the present invention. This Internet of Things control method for the operating parameters of the cremator includes steps S01 to S04, where:

[0075] Step S01: Collect the operating data of the cremator and perform preprocessing;

[0076] Step S02: Perform visual image conversion based on the preprocessed operating data of the cremator to obtain the operating state image of the cremator;

[0077] It should be noted that in this embodiment, the preprocessed operation data of the cremator is divided into parameter-based operation data and image-based operation data;

[0078] Retrieve the corresponding function expression in the preset function database according to the parameter type, so as to generate a function image for the parameter-based operation data according to the function expression, and obtain the operation state function image of the cremator. The function image generation includes generating a function image of the temperature parameter-based operation data. The specific algorithm for generating the function image of the temperature parameter-based operation data is as follows:

[0079] ,

[0080] Among them, represents the temperature parameter-based operation data, represents the time data, represents the internal heat conduction coefficient of the cremator furnace, represents the Laplace operator;

[0081] Extract the channel images from the image-based operation data according to the color channels. The color channels include the red channel, the green channel, and the blue channel. Extract the pixel channel values of the channel images corresponding to each channel and perform pixel value weighting processing to obtain the thermal image of the operation state of the cremator. The specific formula for the pixel value weighting processing is as follows:

[0082] ,

[0083] Among them, represents the pixel value of a single pixel point, and respectively represent the pixel weights of the minimum value and the maximum value, and respectively represent the minimum value function and the maximum value function, respectively represent the pixel channel values of a single pixel point on the three color channels;

[0084] After the step of performing visual image conversion on the preprocessed operation data of the cremator to obtain the operation state image of the cremator, it further includes:

[0085] Judge the adjustment of the user terminal according to the operation state image of the cremator;

[0086] If it is determined that the current operation state of the cremator is in a state where the user terminal cannot be adjusted, the user terminal database generates a central adjustment request report according to the non-adjustable type to wake up the control strategy database of the Internet of Things center for operation state judgment;

[0087] If it is determined that the current operating state of the cremator is in an adjustable state of the user terminal, the user terminal database performs comprehensive regulation on the target cremator according to the user terminal comprehensive regulation algorithm. The specific content of the user terminal comprehensive regulation algorithm is as follows:

[0088] ,

[0089] Among them, represents the velocity field, represents the scalar pressure, represents the external force, represents the number of components, =(1, 2, 3), represents the spatial variable, represents the time data.

[0090] Step S03: Perform an operating state judgment on the operating state image of the cremator according to the parameter steady-state analysis algorithm and the thermal image analysis algorithm to obtain an operating state analysis report of the cremator, and then retrieve a solution from the regulation strategy database according to the operating state analysis report of the cremator to obtain a central regulation solution;

[0091] It should be noted that in this embodiment, the operating state function image of the cremator is denoised according to the denoising algorithm. The specific formula of the denoising algorithm is as follows:

[0092] ,

[0093] Among them, represents the function value after denoising the operating state function image of the cremator, and respectively represent the width and height of the denoising window size, and respectively represent the discrete values of the abscissa and ordinate of the function value, and respectively represent the abscissa and ordinate of the function value;

[0094] Then, perform an operating state judgment on the operating state function image of the cremator according to the parameter steady-state analysis algorithm to obtain a first operating state analysis report of the cremator. The specific formula of the parameter steady-state analysis algorithm is as follows:

[0095] ,

[0096] ,

[0097] ,

[0098] Among them, represents the function value after denoising the operating state function image of the cremator, Represents the mean value of the function after denoising the function image of the cremator's operating state, Represents the function fluctuation value of the function image of the cremator's operating state, Represents the number of function points, Represents the ordinal number of the function point;

[0099] Calculate the temperature values of all pixel points in the thermal image of the cremator's operating state, and then calibrate the temperature values according to the pixel values of the pixel points after grayscale processing, so as to divide the area of the thermal image of the cremator's operating state into a high-temperature area, a rated-temperature area, and a low-temperature area. The specific algorithm for the area division is as follows:

[0100] ,

[0101] Among them, Represents the pixel area of the thermal image of the cremator's operating state, , , Represent the high-temperature area, the rated-temperature area, and the low-temperature area respectively, Represents the temperature value of the pixel points in the area, and Represent the lowest temperature threshold and the highest temperature threshold of the rated operating temperature of the cremator respectively;

[0102] Judge the operating state of a single area in the high-temperature area, the rated-temperature area, and the low-temperature area respectively according to the thermal image analysis algorithm. The specific thermal image analysis algorithm is as follows:

[0103] ,

[0104] ,

[0105] ,

[0106] Among them, Represents the basic prediction value of the temperature fluctuation change in a single area, Represents the correction value of the temperature fluctuation change in a single area, Represents the pixel area change value, Represents the area temperature change value, Represents the deviation value, Represents the correction slope parameter, Represents the standard rated temperature value of the cremator's operation, Represents the edge temperature value of a single area, Represents the air temperature value inside the cremator, Represents the air thermal conductivity inside the cremator, Represents the correction weight, Represents the refined predicted value of the temperature fluctuation in a single area;

[0107] Obtain the refined predicted values of the temperature fluctuations in all areas to obtain the analysis report on the second operating state of the cremator;

[0108] Perform key-value matching operations according to the keywords in the analysis report on the first operating state of the cremator, and pair the parameter adjustment values in the regulation strategy database according to the retrieval keys corresponding to the keywords, so as to screen out the regulation operation instruction set with the largest number of parameter adjustment items;

[0109] Generate a parameter adjustment plan according to the regulation operation instruction set;

[0110] Alternatively, according to the positioning information and temperature fluctuation information of all pixel points in the analysis report on the second operating state of the cremator, locate the spatial area inside the cremator to be temperature-regulated to obtain the distribution information of the areas to be regulated;

[0111] Then retrieve the relevant regulation instructions for the areas to be regulated in the regulation strategy database according to the distribution information of the areas to be regulated;

[0112] After obtaining the relevant regulation instruction set, set the regulation distribution values corresponding to the areas to be regulated according to the refined predicted values of the temperature fluctuations in the areas in the analysis report on the second operating state of the cremator to obtain a distribution adjustment plan.

[0113] Step S04: Regulate the operation of the cremator according to the central regulation plan, and feedback the execution result of the cremator operation regulation to the cloud database;

[0114] It should be noted that in this embodiment, according to the central regulation plan, obtain the regulation instructions for the temperature parameters and temperature regulation parameters, so as to regulate the operation of the cremator according to the adaptive fuzzy regulation network. The optimization regulation algorithm of the adaptive fuzzy regulation network is as follows:

[0115] ,

[0116] ,

[0117] Among them, Represents the error cost value, Represents the regulation predetermined output value, Represents the regulation actual output value, Represents the time step, Represents the center value of the membership function, Represents the learning rate parameter;

[0118] Feedback the execution result of the cremator operation regulation to the cloud database;

[0119] If it is determined that the cremator is in a dangerous operating state, the cremator shall be emergently controlled according to the preset safety emergency rules, multi-terminal alarms shall be given, and the backup of dangerous operating information shall be recorded.

[0120] In summary, the proposed IoT-based control method for the operating parameters of a cremator establishes an IoT architecture around the cremator equipment, visualizes the operating data of the cremator at the IoT central end to achieve more intuitive data feedback, designs a parameter steady-state analysis algorithm and a thermal image analysis algorithm for the IoT central end to respectively judge the operating states of different types of cremator operating data. The parameter steady-state analysis algorithm analyzes and judges the stability of the cremator operation from the numerical orientation to quickly address the problem that the working state of the cremator is prone to continuous fluctuations during operation, improving the operating performance of the cremator. The thermal image analysis algorithm analyzes the balance of the cremator operation from the spatial orientation to quickly address the complex internal conditions during the cremator operation. The IoT central end associates and controls different-oriented cremator adjustment schemes to strengthen the data correlation between the IoT central end and the user terminal during control, further improving the operation and control efficiency of the cremator. Then, a user terminal comprehensive control algorithm is designed at the user terminal to enhance the data connection between user terminal nodes and within user terminal nodes in the IoT architecture, improving the parameter fine-tuning and steady-state maintenance performance of all devices in the user terminal nodes. The present invention improves the operating stability and balance of the cremator. Specifically, the operating data of the cremator is collected and preprocessed to improve the reliability of the parameters. Visual image conversion is performed based on the preprocessed operating data of the cremator to obtain the cremator operating state image. The visual image conversion includes operating data function image conversion and operating data thermal image conversion. The cremator operating state image includes the cremator operating state function image and the cremator operating state thermal image, realizing visual feedback and making the cremator operating state feedback more intuitive. The operating state of the cremator operating state image is judged according to the parameter steady-state analysis algorithm and the thermal image analysis algorithm to obtain the cremator operating state analysis report. Then, a scheme search is performed on the control strategy database according to the cremator operating state analysis report to obtain the central adjustment scheme. The parameter steady-state analysis algorithm is used to eliminate function image noise and analyze and judge the fluctuation state of the function image. The thermal image analysis algorithm is used to locate different thermal regions and analyze and judge the distribution state of the thermal regions to analyze the balance of the cremator operation to quickly address the complex internal conditions during the cremator operation. The IoT central end associates and controls different-oriented cremator adjustment schemes to strengthen the data correlation between the IoT central end and the user terminal during control, further improving the operation and control efficiency of the cremator. The cremator operation is controlled according to the central adjustment scheme, and the execution result of the cremator operation control is fed back to the cloud database. The present invention improves the operating stability and balance of the cremator.

[0121] Please refer to Figure 2, which shows the flowchart of the Internet of Things control method for the operating parameters of the cremator proposed in the second embodiment of the present invention. This Internet of Things control method for the operating parameters of the cremator includes steps S11 to S16, where:

[0122] Step S11: Collect the operating data of the cremator and perform preprocessing. Divide the preprocessed operating data of the cremator into parameter-type operating data and image-type operating data. Retrieve the corresponding function expressions in the preset function database according to the parameter type, and generate function images for the parameter-type operating data according to the function expressions to obtain the operating state function image of the cremator. Extract channel images from the image-type operating data according to the color channels, extract the pixel channel values of the channel images corresponding to each channel, and perform pixel value weighting processing to obtain the thermal image of the operating state of the cremator;

[0123] Step S12: Denoise the operating state function image of the cremator according to the denoising algorithm, and then judge the operating state of the operating state function image of the cremator according to the parameter steady-state analysis algorithm to obtain the first operating state analysis report of the cremator. Calculate the temperature values of all pixel points in the thermal image of the operating state of the cremator, and then calibrate the temperature values according to the pixel values of the grayscale-processed pixel points to divide the thermal image of the operating state of the cremator into regions. Judge the operating state of each single region respectively according to the thermal image analysis algorithm, and obtain the refined prediction values of the temperature fluctuations in all regions to obtain the second operating state analysis report of the cremator;

[0124] Step S13: Perform key-value matching operations according to the keywords in the first operating state analysis report of the cremator. According to the retrieval keys corresponding to the keywords, perform parameter adjustment value pairing in the control strategy database to screen the adjustment operation instruction set with the largest number of parameter adjustment items, and generate a parameter adjustment plan according to the adjustment operation instruction set;

[0125] Step S14: Locate the spatial regions inside the cremator that need to be temperature-controlled according to the positioning information and temperature fluctuation change information of all pixel points in the second operating state analysis report of the cremator to obtain the distribution information of the regions to be controlled. Then, retrieve the relevant control instructions for the regions to be controlled in the control strategy database according to the distribution information of the regions to be controlled. After obtaining the relevant control instruction set, set the control distribution values corresponding to the regions to be controlled according to the refined prediction values of the temperature fluctuations in the regions in the second operating state analysis report of the cremator to obtain a distribution adjustment plan;

[0126] Step S15: According to the central regulation scheme, obtain the regulation instructions for the temperature parameters and temperature regulation parameters, so as to regulate the operation of the cremator according to the adaptive fuzzy regulation network, and feedback the execution result of the cremator operation regulation to the cloud database. If it is determined that the cremator is in a dangerous operation state, conduct emergency control of the cremator according to the preset safety emergency rules, issue multi-terminal alarms and record the backup of dangerous operation information;

[0127] Step S16: Make a user terminal adjustment judgment based on the operation state image of the cremator. If it is determined that the current operation state of the cremator is in a state where the user terminal cannot be adjusted, the user terminal database generates a central regulation request report according to the non-adjustable type to wake up the regulation strategy database of the Internet of Things central, and make an operation state judgment. If it is determined that the current operation state of the cremator is in a state where the user terminal can be adjusted, the user terminal database conducts comprehensive regulation on the target cremator according to the user terminal comprehensive regulation algorithm.

[0128] In summary, for the proposed IoT-based control method for cremator operating parameters, by establishing an IoT architecture around the cremator equipment, the operating data of the cremator is visualized at the IoT central end to achieve more intuitive data feedback. A parameter steady-state analysis algorithm and a thermal image analysis algorithm are designed for the IoT central end to respectively judge the operating states of different types of cremator operating data. The parameter steady-state analysis algorithm analyzes and judges the stability of the cremator operation from the numerical orientation to quickly address the problem that the working state of the cremator is prone to continuous fluctuations during operation, improving the operating performance of the cremator. The thermal image analysis algorithm analyzes the balance of the cremator operation from the spatial orientation to quickly address the complex internal conditions during the cremator operation. The IoT central end correlates and controls different-oriented cremator adjustment schemes to strengthen the data correlation between the IoT central end and the user terminal during control, further improving the cremator operation and control efficiency. Then, a user terminal comprehensive control algorithm is designed for the user terminal, enhancing the data connection between user terminal nodes and within user terminal nodes in the IoT architecture, and improving the parameter fine-tuning and steady-state maintenance performance of all devices in the user terminal nodes. The present invention improves the operating stability and balance of the cremator. Specifically, the operating data of the cremator is collected and preprocessed to improve the reliability of the parameters. According to the preprocessed cremator operating data, a visualization image conversion is performed to obtain a cremator operating state image. The visualization image conversion includes an operating data function image conversion and an operating data thermal image conversion. The cremator operating state image includes a cremator operating state function image and a cremator operating state thermal image, realizing visual feedback and making the cremator operating state feedback more intuitive. According to the parameter steady-state analysis algorithm and the thermal image analysis algorithm, the operating state of the cremator operating state image is judged to obtain a cremator operating state analysis report. Then, according to the cremator operating state analysis report, a scheme search is performed on the control strategy database to obtain a central adjustment scheme. The parameter steady-state analysis algorithm is used to eliminate function image noise and analyze and judge the fluctuation state of the function image. The thermal image analysis algorithm is used to locate different thermal regions and analyze and judge the distribution state of the thermal regions to analyze the balance of the cremator operation to quickly address the complex internal conditions during the cremator operation. The IoT central end correlates and controls different-oriented cremator adjustment schemes to strengthen the data correlation between the IoT central end and the user terminal during control, further improving the cremator operation and control efficiency. The cremator operation is controlled according to the central adjustment scheme, and the execution result of the cremator operation control is fed back to the cloud database. The present invention improves the operating stability and balance of the cremator.

[0129] Please refer to Figure 3, which shows a schematic structural diagram of an Internet of Things control system for cremator operation parameters proposed in the third embodiment of the present invention. The system includes:

[0130] An acquisition module 10, configured to acquire cremator operation data and perform preprocessing;

[0131] A visualization conversion module 20, configured to perform visualization image conversion according to the preprocessed cremator operation data to obtain a cremator operation status image. The visualization image conversion includes operation data function image conversion and operation data thermology image conversion. The cremator operation status image includes a cremator operation status function image and a cremator operation status thermology image;

[0132] A central analysis module 30, configured to perform an operation status judgment on the cremator operation status image according to a parameter steady-state analysis algorithm and a thermology image analysis algorithm to obtain a cremator operation status analysis report, and then perform a scheme retrieval on a control strategy database according to the cremator operation status analysis report to obtain a central adjustment scheme. The parameter steady-state analysis algorithm is used to eliminate function image noise and analyze and judge the fluctuation state of the function image, and the thermology image analysis algorithm is used to locate different thermology regions and analyze and judge the distribution state of the thermology regions;

[0133] A control module 40, configured to perform cremator operation control according to the central adjustment scheme and feedback the execution result of the cremator operation control to the cloud database.

[0134] The present invention also proposes a computer storage medium, on which one or more programs are stored. When the program is executed by a processor, the above-mentioned visualization remote control method for cremator operation parameters is implemented.

[0135] The present invention also proposes a computer device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored on the memory to implement the above-mentioned visualization remote control method for cremator operation parameters.

[0136] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0137] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection part (electronic device) having one or more wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0138] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0139] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0140] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

Claims

1. An Internet of Things control method for the operating parameters of a cremator, characterized in that Including: Collecting and preprocessing the operation data of the cremator; Performing visual image conversion based on the preprocessed operation data of the cremator to obtain the operation status image of the cremator. The visual image conversion includes function image conversion of operation data and thermal image conversion of operation data. The operation status image of the cremator includes the function image of the operation status of the cremator and the thermal image of the operation status of the cremator; The step of performing visual image conversion based on the preprocessed operation data of the cremator to obtain the operation status image of the cremator specifically includes: Dividing the preprocessed operation data of the cremator into parameter-based operation data and image-based operation data; Retrieving the corresponding function expression in the preset function database according to the parameter type to generate a function image for the parameter-based operation data according to the function expression to obtain the function image of the operation status of the cremator. The function image generation includes generating the function image of the temperature parameter-based operation data. The specific algorithm for generating the function image of the temperature parameter-based operation data is as follows: ， Among them, represents the operation data of the temperature parameter type, represents the time data, represents the internal heat conduction coefficient of the cremator furnace, represents the Laplace operator; Extracting channel images from the image-based operation data according to color channels. The color channels include the red channel, the green channel, and the blue channel. Extracting the pixel channel values of the channel images corresponding to each channel and performing pixel value weighting processing to obtain the thermal image of the operation status of the cremator. The specific formula for the pixel value weighting processing is as follows: ， Among them, represents the pixel value of a single pixel point, and respectively represent the pixel weights of the minimum value and the maximum value, and respectively represent the minimum value function and the maximum value function, respectively represent the pixel channel values of a single pixel point on three color channels; Judging the operation status of the cremator based on the operation status image of the cremator according to the parameter steady-state analysis algorithm and the thermal image analysis algorithm to obtain the operation status analysis report of the cremator. Then, retrieving the scheme in the regulation strategy database according to the operation status analysis report of the cremator to obtain the central regulation scheme. The parameter steady-state analysis algorithm is used to eliminate the noise of the function image and analyze and judge the fluctuation state of the function image. The thermal image analysis algorithm is used to locate different thermal regions and analyze and judge the distribution state of the thermal regions; The specific formula of the parameter steady-state analysis algorithm is as follows: ， ， ， Among them, represents the function value after denoising the function image of the cremator operating state, represents the mean value of the function values after denoising the function image of the cremator operating state, represents the function fluctuation value of the function image of the cremator operating state, represents the number of function points, represents the ordinal number of the function points; The step of judging the operation status of the cremator based on the operation status image of the cremator according to the parameter steady-state analysis algorithm and the thermal image analysis algorithm to obtain the operation status analysis report of the cremator further includes: Calculating the temperature values of all pixel points in the thermal image of the operation status of the cremator, and then calibrating the temperature values according to the pixel values of the pixel points after grayscale processing to divide the region of the thermal image of the operation status of the cremator into a high-temperature region, a rated-temperature region, and a low-temperature region. The specific algorithm for the region division is as follows: ， Among them, represents the pixel region of the thermal image of the cremator operating state, , , respectively represent the high-temperature region, the rated-temperature region, and the low-temperature region, represents the temperature value of the pixel points in the region, and respectively represent the lowest temperature threshold and the highest temperature threshold of the rated temperature of the cremator operation; Judging the operation status of a single region in the high-temperature region, the rated-temperature region, and the low-temperature region respectively according to the thermal image analysis algorithm. The specific thermal image analysis algorithm is as follows: ， ， ， Among them, represents the basic predicted value of the temperature fluctuation change in a single area, represents the correction value of the temperature fluctuation change in a single area, represents the pixel area change value, represents the area temperature change value, represents the deviation value, represents the correction slope parameter, represents the standard rated temperature value of the cremator operation, represents the edge temperature value of a single area, represents the air temperature value inside the cremator, represents the air thermal conductivity inside the cremator, represents the correction weight, represents the refined predicted value of the temperature fluctuation change in a single area; Obtaining the refined prediction value of the temperature fluctuation change of all regions to obtain the second operation status analysis report of the cremator; Performing operation regulation on the cremator according to the central regulation scheme and feeding back the execution result of the operation regulation of the cremator to the cloud database; The step of performing operation regulation on the cremator according to the central regulation scheme and feeding back the execution result of the operation regulation of the cremator to the cloud database specifically includes: According to the central regulation scheme, obtain the regulation instructions of the temperature parameter and the temperature regulation parameter, so as to regulate the operation of the cremator according to the adaptive fuzzy regulation network. The optimization regulation algorithm of the adaptive fuzzy regulation network is as follows: ， ， Among them, represents the error cost value, represents the regulated predetermined output value, represents the regulated actual output value, represents the time step, represents the center value of the membership function, represents the learning rate parameter; Feed back the execution result of the cremator operation regulation to the cloud database; If it is determined that the cremator is in a dangerous operation state, perform emergency control of the cremator according to the preset safety emergency rules, and conduct multi-terminal alarms and record the backup of the dangerous operation information.

2. The Internet of Things control method for the cremator operation parameters according to claim 1, wherein The step of judging the operation state of the cremator operation state image according to the parameter steady-state analysis algorithm and the thermal image analysis algorithm to obtain the cremator operation state analysis report specifically includes: Denoise the cremator operation state function image according to the denoising algorithm. The specific formula of the denoising algorithm is as follows: ， Among them, represents the function value after denoising of the image of the cremator operating state function, and represent the width and height of the denoising window size respectively, and represent the discrete values of the abscissa and ordinate of the function value respectively, and represent the abscissa and ordinate of the function value respectively; Then judge the operation state of the cremator operation state function image according to the parameter steady-state analysis algorithm to obtain the first cremator operation state analysis report.

3. The Internet of Things control method for the operating parameters of the cremator according to claim 2, characterized in that After the step of obtaining the first cremator operation state analysis report, it also includes: Perform key-value matching operations according to the keywords in the first cremator operation state analysis report, and perform parameter adjustment value pairing in the regulation strategy database according to the retrieval keys corresponding to the keywords, so as to screen out the regulation operation instruction set with the largest number of parameter adjustment items; Generate a parameter adjustment scheme according to the regulation operation instruction set; Or, according to the positioning information and temperature fluctuation change information of all pixel points in the second cremator operation state analysis report, locate the space area to be temperature-regulated inside the cremator to obtain the distribution information of the area to be regulated; Then retrieve the relevant regulation instructions of the area to be regulated in the regulation strategy database according to the distribution information of the area to be regulated; After obtaining the relevant regulation instruction set, set the regulation distribution value corresponding to the area to be regulated according to the refined prediction value of the regional temperature fluctuation change in the second cremator operation state analysis report to obtain the distribution adjustment scheme.

4. The IoT control method for the operating parameters of the cremator according to claim 1, wherein After the step of performing visual image conversion on the preprocessed cremator operation data to obtain the cremator operation state image, it also includes: Judge the adjustment of the user terminal according to the cremator operation state image; If it is determined that the current cremator operation state is in a state where the user terminal cannot be adjusted, the user terminal database generates a central regulation request report according to the non-adjustable type to wake up the regulation strategy database of the Internet of Things center for operation state judgment; If it is determined that the current cremator operation state is in a state where the user terminal can be adjusted, the user terminal database performs comprehensive regulation on the target cremator according to the user terminal comprehensive regulation algorithm. The specific user terminal comprehensive regulation algorithm is as follows: ， Among them, represents the velocity field, represents the scalar pressure, represents the external force, represents the number of components, = (1, 2, 3), represents the spatial variable, represents the time data.

5. An Internet of Things control system for the operating parameters of a cremator, characterized in that, It includes: A collection module for collecting cremator operation data and performing preprocessing; A visual conversion module for performing visual image conversion according to the preprocessed cremator operation data to obtain the cremator operation state image. The visual image conversion includes the conversion of the operation data function image and the conversion of the operation data thermal image. The cremator operation state image includes the cremator operation state function image and the cremator operation state thermal image; The step of performing visual image conversion on the pre - processed operation data of the cremator to obtain the operation status image of the cremator specifically includes: Dividing the pre - processed operation data of the cremator into parameter - type operation data and image - type operation data; Retrieving the corresponding function expression in the preset function database according to the parameter type to generate a function image for the parameter - type operation data according to the function expression, so as to obtain the function image of the cremator operation status. The function image generation includes generating the function image of the temperature parameter - type operation data. The specific algorithm for generating the function image of the temperature parameter - type operation data is as follows: ， Among them, represents the operating data of the temperature parameter type, represents the time data, represents the internal heat conduction coefficient of the cremator furnace, represents the Laplace operator; Extracting the channel image from the image - type operation data according to the color channel. The color channel includes the red channel, the green channel, and the blue channel. Extracting the pixel channel value of each corresponding channel image and performing pixel value weighting processing to obtain the thermal image of the cremator operation status. The specific formula for the pixel value weighting processing is as follows: ， Among them, represents the pixel value of a single pixel point, and respectively represent the pixel weights of the minimum value and the maximum value, and respectively represent the minimum value function and the maximum value function, respectively represent the pixel channel values of a single pixel point on three color channels; The central analysis module is used to judge the operation status of the cremator operation status image according to the parameter steady - state analysis algorithm and the thermal image analysis algorithm to obtain the operation status analysis report of the cremator, and then retrieve the solution in the regulation strategy database according to the operation status analysis report of the cremator to obtain the central regulation solution. The parameter steady - state analysis algorithm is used to eliminate the noise of the function image and analyze and judge the fluctuation state of the function image. The thermal image analysis algorithm is used to locate different thermal regions and analyze and judge the distribution state of the thermal regions; The specific formula of the parameter steady - state analysis algorithm is as follows: ， ， ， Among them, represents the function value after denoising the function image of the cremator operating state, represents the mean value of the function values after denoising the function image of the cremator operating state, represents the function fluctuation value of the function image of the cremator operating state, represents the number of function points, represents the ordinal number of the function point; The step of judging the operation status of the cremator operation status image according to the parameter steady - state analysis algorithm and the thermal image analysis algorithm to obtain the operation status analysis report of the cremator further includes: Calculating the temperature values of all pixel points in the thermal image of the cremator operation status, and then calibrating the temperature values according to the pixel values of the grayscale - processed pixel points to divide the region of the thermal image of the cremator operation status into a high - temperature region, a rated - temperature region, and a low - temperature region. The specific algorithm for the region division is as follows: ， Among them, represents the pixel area of the thermal image of the cremator operating state, , , respectively represent the high-temperature area, the rated-temperature area, and the low-temperature area, represents the temperature value of the pixel points within the area, and respectively represent the minimum temperature threshold and the maximum temperature threshold of the rated temperature of the cremator operation; Judging the operation status of a single region in the high - temperature region, the rated - temperature region, and the low - temperature region respectively according to the thermal image analysis algorithm. The specific thermal image analysis algorithm is as follows: ， ， ， Among them, represents the basic predicted value of the temperature fluctuation change in a single area, represents the correction value of the temperature fluctuation change in a single area, represents the pixel area change value, represents the regional temperature change value, represents the deviation value, represents the correction slope parameter, represents the standard rated temperature value of the cremator operation, represents the edge temperature value of a single area, represents the air temperature value inside the cremator, represents the air thermal conductivity inside the cremator, represents the correction weight, represents the refined predicted value of the temperature fluctuation change in a single area; Obtaining the refined prediction value of the temperature fluctuation change of all regions to obtain the second operation status analysis report of the cremator; The regulation module is used to perform cremator operation regulation according to the central regulation solution and feedback the execution result of the cremator operation regulation to the cloud database; The step of performing cremator operation regulation according to the central regulation solution and feedbacking the execution result of the cremator operation regulation to the cloud database specifically includes: Obtaining the regulation instructions of the temperature parameter and the temperature regulation parameter according to the central regulation solution to perform cremator operation regulation according to the adaptive fuzzy regulation network. The optimization regulation algorithm of the adaptive fuzzy regulation network is as follows: ， ， Among them, represents the error cost value, represents the regulated predetermined output value, represents the regulated actual output value, represents the time step, represents the center value of the membership function, represents the learning rate parameter; Feedbacking the execution result of the cremator operation regulation to the cloud database; If it is determined that the cremator is in a dangerous operating state, emergency control of the cremator is carried out according to the preset safety emergency rules, multi-terminal alarms are given, and backup of the dangerous operating information is recorded.

6. A storage medium, characterized in that, The storage medium stores one or more programs, which when executed by a processor implement the Internet of Things control method for the cremator operating parameters as described in any one of claims 1-4.

7. A computer device, characterized in that, The computer device includes a memory and a processor, wherein: The memory is used for storing computer programs; When the processor is used to execute the computer programs stored on the memory, the Internet of Things control method for the cremator operating parameters as described in any one of claims 1-4 is implemented.

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