Air preheater intelligent control system and method based on thermal imaging and artificial intelligence

Abstract

The invention discloses an air preheater intelligent control system and method based on thermal imaging and artificial intelligence, and relates to the technical field of temperature regulation, the system comprises a data acquisition module, a data preprocessing module, a data processing module and an AI decision module; according to the method, the operation data, the outlet temperature thermal image and the surrounding environment thermal image of the air preheater are collected, comprehensive analysis and processing are carried out in combination with the target heating temperature, intelligent adjustment of the air preheater can be achieved, and therefore the control precision and efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of temperature regulation technology, and more particularly to an intelligent control system and method for an air preheater based on thermal imaging and artificial intelligence. Background Art

[0002] At present, the air preheater is also referred to as air preheater for short. It is a preheating device that improves the heat exchange performance of the boiler and reduces heat loss. The function of the air preheater is to transfer the heat carried by the flue gas discharged from the tail flue of the boiler to the air before entering the boiler through the heat sink, and preheat the air to a certain temperature.

[0003] However, the prior art lacks a control system for the air preheater, and is unable to improve the working efficiency, reliability and intelligence level of the air preheater.

[0004] Therefore, how to provide an intelligent control system and method for an air preheater that can solve the above problems is an issue that technical personnel in this field urgently need to solve. Summary of the invention

[0005] In view of this, the present invention provides an intelligent control system and method for an air preheater based on thermal imaging and artificial intelligence. By collecting the operating data of the air preheater, the outlet temperature thermal image and the surrounding environment thermal image, and performing comprehensive analysis and processing in combination with the target heating temperature, intelligent adjustment of the air preheater can be achieved, thereby improving the control accuracy and efficiency.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: An intelligent control system for air preheater based on thermal imaging and artificial intelligence, comprising: A data acquisition module is used to collect the operation data of the air preheater, the thermal image of the outlet temperature, the thermal image of the surrounding environment, and the target heating temperature; A data preprocessing module, which is connected to the data acquisition module and is used to preprocess the operation data, the outlet temperature thermal image, and the surrounding environment thermal image; A data processing module, which is connected to the data preprocessing module and is used to process the preprocessed operation data, the outlet temperature thermal image, and the surrounding environment thermal image to obtain corresponding image processing results and operation data processing results; An AI decision-making module is connected to the data processing module and the data acquisition module, and is used to determine an optimal operation data control scheme based on image processing results, operation data processing results and target heating temperature.

[0007] Preferably, it also includes: An adjustment module is connected to the AI ​​decision-making module and is used to adjust the delivery parameters of the air preheater according to the optimal operation data control scheme.

[0008] Preferably, the data acquisition module includes: an operation data acquisition unit, a temperature thermal image acquisition unit and a target heating temperature acquisition unit.

[0009] Preferably, the data preprocessing module includes: An image preprocessing unit, connected to the temperature thermal image acquisition unit, for preprocessing the outlet temperature thermal image and the surrounding environment thermal image; A data preprocessing unit is connected to the operation data acquisition unit and is used to preprocess the operation data.

[0010] Preferably, the data processing module includes: The temperature thermal image processing unit is used to construct an image recognition model, and use the image recognition model to recognize the outlet temperature thermal image and the surrounding environment thermal image respectively to obtain the current outlet temperature and the surrounding environment temperature; The operation data processing unit is used to construct a data processing model and use the data processing model to process the operation data to obtain corresponding operation data processing results.

[0011] Preferably, the AI ​​decision-making module includes: A receiving unit, the receiving unit is connected to the temperature thermal image processing unit, the operation data processing unit and the data acquisition module, and is used to receive the current outlet temperature, the ambient temperature and the target heating temperature; A judgment unit, connected to the receiving unit, for determining a difference between a target heating temperature and a current outlet temperature; The first decision unit is used to perform a thermodynamic simulation using the current outlet temperature and the ambient temperature when the difference is less than or equal to a preset threshold, and determine whether the final outlet temperature can reach the target heating temperature according to the simulation result, and terminate the adjustment if it can; The second decision unit is used to construct an AI decision model when the difference is greater than a preset threshold or when the simulation results determine that the final outlet temperature cannot reach the target heating temperature, input the difference, the current outlet temperature, the ambient temperature and the operation data processing results into the AI ​​decision model for processing, and determine the operation data adjustment plan of the air preheater according to the processing results of the AI ​​decision model.

[0012] The present invention also provides an intelligent control method for an air preheater based on thermal imaging and artificial intelligence, comprising the following steps: Collect the operation data of the air preheater, the outlet temperature thermal image, the surrounding environment thermal image and the target heating temperature, and pre-process the operation data, the outlet temperature thermal image and the surrounding environment thermal image; A data processing model and an image recognition model are respectively constructed, and the preprocessed operation data are processed by the data processing model, and the preprocessed outlet temperature thermal image and the surrounding environment thermal image are processed by the image recognition model to obtain corresponding operation data processing results, current outlet temperature and surrounding environment temperature; The air preheater is adjusted according to the operating data processing results, the current outlet temperature, the ambient temperature and the target heating temperature.

[0013] Preferably, the specific process of adjusting the air preheater according to the operation data processing result, the current outlet temperature, the ambient temperature and the target heating temperature includes: Determine the difference between the current outlet temperature and the target heating temperature, and judge the relationship between the difference and a preset threshold; When the difference is less than or equal to the preset threshold, a thermodynamic simulation is performed using the current outlet temperature and the ambient temperature, and it is determined based on the simulation results whether the final outlet temperature can reach the target heating temperature. If so, the adjustment is terminated.

[0014] Preferably, the specific process of adjusting the air preheater according to the operation data processing result, the current outlet temperature, the ambient temperature and the target heating temperature also includes: When the simulation results determine that the final outlet temperature cannot reach the target heating temperature, or when the difference is greater than a preset threshold; An AI decision-making model is constructed, and the difference, current outlet temperature, ambient temperature and operation data processing results are input into the AI ​​decision-making model for processing, and the operation data adjustment plan of the air preheater is determined according to the processing results of the AI ​​decision-making model. It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses an intelligent control system and method for an air preheater based on thermal imaging and artificial intelligence, which has the following beneficial effects: 1. The present invention collects the operating data of the air preheater, the outlet temperature thermal image and the surrounding environment thermal image, and performs comprehensive analysis and processing in combination with the target heating temperature. This method can more accurately understand the actual working state of the air preheater and the external environmental conditions. By using the image recognition model and the data processing model, the air preheater can be intelligently adjusted, thereby improving the control accuracy and efficiency.

[0015] 2. The present invention introduces an AI decision-making model, which can intelligently formulate an air preheater operation data adjustment plan based on the difference between the current outlet temperature and the target heating temperature, the current outlet temperature, the ambient temperature, and the operation data processing results. This intelligent decision-making method avoids the problems of human misjudgment or lack of experience that may exist in traditional control methods, and improves the accuracy and reliability of decision-making.

[0016] 3. The present invention can predict whether the adjusted outlet temperature can reach the target heating temperature through thermodynamic simulation operation. This prediction function enables the system to be flexibly adjusted according to actual conditions, enhancing the adaptability and flexibility of the system. At the same time, by continuously learning and optimizing the AI ​​decision-making model, the system can also gradually improve its own control ability and adaptability, and also enable users to manage and adjust equipment more conveniently. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0018] Figure 1 A structural principle block diagram of an air preheater intelligent control system based on thermal imaging and artificial intelligence provided by the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] See also Figure 1 As shown, the embodiment of the present invention discloses an intelligent control system for an air preheater based on thermal imaging and artificial intelligence, comprising: The data acquisition module is used to collect the operation data of the air preheater, the outlet temperature thermal image, the surrounding environment thermal image and the target heating temperature. The operation data of the air preheater may include: the rotation speed, humidity, pressure, air flow and other parameters of the air preheater. The above parameters can effectively help to adjust the temperature during the operation of the air preheater. These data can not only reflect the working status of the air preheater, but also provide a basis for optimizing the control strategy; A data preprocessing module, which is connected to the data acquisition module and is used to preprocess the operation data, the outlet temperature thermal image, and the surrounding environment thermal image; The data processing module is connected to the data preprocessing module and is used to process the preprocessed operation data, the outlet temperature thermal image, and the surrounding environment thermal image to obtain corresponding image processing results and operation data processing results; The AI ​​decision module is connected with the data processing module and the data acquisition module, and is used to determine the best operation data control plan according to the image processing results, operation data processing results and target heating temperature.

[0021] In a specific embodiment, it also includes: The regulating module is connected to the AI ​​decision-making module and is used to adjust the delivery parameters of the air preheater according to the optimal operation data control plan.

[0022] In a specific embodiment, the data acquisition module includes: an operation data acquisition unit, a temperature thermal image acquisition unit and a target heating temperature acquisition unit.

[0023] In a specific embodiment, the data preprocessing module includes: An image preprocessing unit, which is connected to the temperature thermal image acquisition unit and is used to preprocess the outlet temperature thermal image and the surrounding environment thermal image, wherein the preprocessing process may include steps such as image filtering and image enhancement to improve the accuracy of subsequent data processing; The data preprocessing unit is connected to the operation data acquisition unit and is used to preprocess the operation data, wherein the preprocessing process may include outlier removal and filtering.

[0024] In a specific embodiment, the data processing module includes: The temperature thermal image processing unit is used to construct an image recognition model, and use the image recognition model to recognize the outlet temperature thermal image and the surrounding environment thermal image respectively to obtain the current outlet temperature and the surrounding environment temperature; The operation data processing unit is used to construct a data processing model and use the data processing model to process the operation data to obtain corresponding operation data processing results.

[0025] In a specific embodiment, the AI ​​decision module includes: A receiving unit, the receiving unit is connected to the temperature thermal image processing unit, the operation data processing unit and the data acquisition module, and is used to receive the current outlet temperature, the ambient temperature and the target heating temperature; A judgment unit, the judgment unit is connected to the receiving unit and is used to determine the difference between the target heating temperature and the current outlet temperature; The first decision unit is used to perform thermodynamic simulation using the current outlet temperature and the ambient temperature when the difference is less than or equal to a preset threshold, and determine whether the final outlet temperature can reach the target heating temperature according to the simulation result, and end the adjustment if it can; The second decision unit is used to build an AI decision model when the difference is greater than a preset threshold or when the simulation results determine that the final outlet temperature cannot reach the target heating temperature, input the difference, current outlet temperature, ambient temperature and operating data processing results into the AI ​​decision model for processing, and determine the operating data adjustment plan of the air preheater according to the processing results of the AI ​​decision model.

[0026] The embodiment of the present invention also provides an intelligent control method for an air preheater based on thermal imaging and artificial intelligence, comprising the following steps: Collect the operation data of the air preheater, the outlet temperature thermal image, the surrounding environment thermal image and the target heating temperature, and pre-process the operation data, the outlet temperature thermal image and the surrounding environment thermal image; A data processing model and an image recognition model are constructed respectively, and the preprocessed operation data are processed by the data processing model, and the preprocessed outlet temperature thermal image and the surrounding environment thermal image are processed by the image recognition model to obtain the corresponding operation data processing results, the current outlet temperature and the surrounding environment temperature; The air preheater is adjusted according to the operating data processing results, the current outlet temperature, the ambient temperature and the target heating temperature.

[0027] Specifically, the image recognition model may include a feature extraction module, a recognition module and a calculation module. The feature extraction module performs feature extraction and edge recognition on the preprocessed outlet temperature thermal image and the surrounding environment thermal image, respectively, determines the corresponding recognition area, and then inputs the recognition area into the recognition module to obtain the corresponding radiation value. The calculation module is pre-set with a temperature calculation model, and the radiation value is input into the temperature calculation model to obtain the final temperature recognition result.

[0028] The data processing model may be a support vector machine (SVM) or an XGBoost classification model. By processing the preprocessed operating data using the data processing model, an operating data classification result that is beneficial to subsequent adjustments may be obtained, thereby facilitating subsequent adjustments.

[0029] In a specific embodiment, the specific process of adjusting the air preheater according to the operation data processing result, the current outlet temperature, the ambient temperature and the target heating temperature includes: Determine the difference between the current outlet temperature and the target heating temperature, and judge the relationship between the difference and a preset threshold value; When the difference is less than or equal to the preset threshold, a thermodynamic simulation is performed using the current outlet temperature and the ambient temperature, and based on the simulation results, it is determined whether the final outlet temperature can reach the target heating temperature. If so, the adjustment is terminated.

[0030] In a specific embodiment, the specific process of adjusting the air preheater according to the operation data processing result, the current outlet temperature, the ambient temperature and the target heating temperature also includes: When the simulation results determine that the final outlet temperature cannot reach the target heating temperature, or when the difference is greater than a preset threshold; An AI decision-making model is constructed, and the difference, current outlet temperature, ambient temperature, and operating data processing results are input into the AI ​​decision-making model for processing. The operating data adjustment plan of the air preheater is determined according to the processing results of the AI ​​decision-making model.

[0031] Specifically, the AI ​​decision model can be a processing model that combines a decision tree and a fuzzy neural network for multi-objective optimization. In the process of determining the operation data adjustment plan, the corresponding classification result is first determined based on the operation data processing result, and then the target constraint condition is constructed, where the target constraint condition may include requirements such as the shortest adjustment time. According to the target constraint condition, difference, current outlet temperature, ambient temperature and operation data processing result input into the corresponding AI decision model, the best operation data adjustment plan can be obtained to improve the adjustment efficiency.

[0032] At the same time, the embodiment of the present invention can also continuously learn and optimize the AI ​​decision-making model through the operation data adjustment scheme, and gradually improve its own control ability and adaptability. In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0033] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent control system for air preheater based on thermal imaging and artificial intelligence, characterized in that: include: A data acquisition module is used to collect the operation data of the air preheater, the thermal image of the outlet temperature, the thermal image of the surrounding environment, and the target heating temperature; A data preprocessing module, which is connected to the data acquisition module and is used to preprocess the operation data, the outlet temperature thermal image, and the surrounding environment thermal image; A data processing module, which is connected to the data preprocessing module and is used to process the preprocessed operation data, the outlet temperature thermal image, and the surrounding environment thermal image to obtain corresponding image processing results and operation data processing results; An AI decision-making module is connected to the data processing module and the data acquisition module, and is used to determine an optimal operation data control scheme based on image processing results, operation data processing results and target heating temperature.

2. According to claim 1, the intelligent control system for air preheater based on thermal imaging and artificial intelligence is characterized in that: Also includes: An adjustment module is connected to the AI ​​decision-making module and is used to adjust the delivery parameters of the air preheater according to the optimal operation data control scheme.

3. The air preheater intelligent control system based on thermal imaging and artificial intelligence according to claim 1 is characterized in that: The data acquisition module includes: an operation data acquisition unit, a temperature thermal image acquisition unit and a target heating temperature acquisition unit.

4. The air preheater intelligent control system based on thermal imaging and artificial intelligence according to claim 3 is characterized in that: The data preprocessing module comprises: An image preprocessing unit, connected to the temperature thermal image acquisition unit, for preprocessing the outlet temperature thermal image and the surrounding environment thermal image; A data preprocessing unit is connected to the operation data acquisition unit and is used to preprocess the operation data.

5. The air preheater intelligent control system based on thermal imaging and artificial intelligence according to claim 4 is characterized in that: The data processing module comprises: The temperature thermal image processing unit is used to construct an image recognition model, and use the image recognition model to recognize the outlet temperature thermal image and the surrounding environment thermal image respectively to obtain the current outlet temperature and the surrounding environment temperature; The operation data processing unit is used to construct a data processing model and use the data processing model to process the operation data to obtain corresponding operation data processing results.

6. The air preheater intelligent control system based on thermal imaging and artificial intelligence according to claim 5 is characterized in that: The AI ​​decision-making module includes: A receiving unit, the receiving unit is connected to the temperature thermal image processing unit, the operation data processing unit and the data acquisition module, and is used to receive the current outlet temperature, the ambient temperature and the target heating temperature; A judgment unit, connected to the receiving unit, for determining a difference between a target heating temperature and a current outlet temperature; The first decision unit is used to perform a thermodynamic simulation using the current outlet temperature and the ambient temperature when the difference is less than or equal to a preset threshold, and determine whether the final outlet temperature can reach the target heating temperature according to the simulation result, and terminate the adjustment if it can; The second decision unit is used to construct an AI decision model when the difference is greater than a preset threshold or when the simulation results determine that the final outlet temperature cannot reach the target heating temperature, input the difference, the current outlet temperature, the ambient temperature and the operation data processing results into the AI ​​decision model for processing, and determine the operation data adjustment plan of the air preheater according to the processing results of the AI ​​decision model.

7. An intelligent control method for air preheater based on thermal imaging and artificial intelligence, characterized in that: The following steps are involved: Collect the operation data of the air preheater, the outlet temperature thermal image, the surrounding environment thermal image and the target heating temperature, and pre-process the operation data, the outlet temperature thermal image and the surrounding environment thermal image; A data processing model and an image recognition model are respectively constructed, and the preprocessed operation data are processed by the data processing model, and the preprocessed outlet temperature thermal image and the surrounding environment thermal image are processed by the image recognition model to obtain corresponding operation data processing results, current outlet temperature and surrounding environment temperature; The air preheater is adjusted according to the operating data processing results, the current outlet temperature, the ambient temperature and the target heating temperature.

8. The air preheater intelligent control method based on thermal imaging and artificial intelligence according to claim 7 is characterized in that: The specific process of adjusting the air preheater according to the operation data processing results, the current outlet temperature, the ambient temperature and the target heating temperature includes: Determine the difference between the current outlet temperature and the target heating temperature, and judge the relationship between the difference and a preset threshold; When the difference is less than or equal to the preset threshold, a thermodynamic simulation is performed using the current outlet temperature and the ambient temperature, and it is determined based on the simulation results whether the final outlet temperature can reach the target heating temperature. If so, the adjustment is terminated.

9. The air preheater intelligent control method based on thermal imaging and artificial intelligence according to claim 8 is characterized in that: The specific process of adjusting the air preheater according to the operation data processing results, the current outlet temperature, the ambient temperature and the target heating temperature also includes: When the simulation results determine that the final outlet temperature cannot reach the target heating temperature, or when the difference is greater than a preset threshold; An AI decision-making model is constructed, and the difference, current outlet temperature, ambient temperature and operation data processing results are input into the AI ​​decision-making model for processing, and the operation data adjustment plan of the air preheater is determined according to the processing results of the AI ​​decision-making model.

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