Power plant boiler ash conveying and detecting system

Abstract

The invention discloses a power plant boiler ash conveying and detecting system, which relates to the technical field of boiler operation and maintenance, and comprises a conveying module, an appearance detection module, a boiler combustion benefit evaluation module and a combustion optimization module, the conveying module is used for conveying boiler ash for detection; the appearance detection module detects the appearance condition of the stove ash based on an image processing technology, and analyzes and evaluates the combustion condition of the stove ash according to the detected appearance condition; the boiler combustion benefit evaluation module evaluates the current boiler combustion benefit condition based on the obtained combustion condition; and the combustion optimization module performs optimization processing on the boiler combustion condition of the current power plant based on the evaluated benefit condition. The combustion condition of the boiler ash is accurately evaluated based on the image processing technology, the combustion strategy is optimized based on the evaluation result, the heat efficiency and the power generation efficiency of the boiler are improved by optimizing the combustion process, and the fuel consumption and the operation cost are reduced, so that the economic benefits of a power plant are improved.

Description

Technical Field

[0001] The invention relates to the technical field of boiler operation and maintenance, and in particular to a boiler ash conveying detection system for a power plant. Background Art

[0002] The power plant boiler, also known as the power station boiler or power plant boiler, is one of the important equipment used for power generation in the power plant. Its operating efficiency and stability are directly related to the cost and benefit of power production. The ash produced during the boiler combustion process is a solid waste formed after the physical and chemical changes of coal and other fuels at high temperatures. By detecting and analyzing the ash, the combustion efficiency of the boiler can be effectively obtained. However, there is no relevant detection method in the prior art. The ash after combustion is only treated as a combustion waste, which makes it inconvenient for people to analyze the combustion of the boiler, and the analysis is laborious and time-consuming. In this regard, we propose a power plant boiler ash transportation detection system. Summary of the invention

[0003] In order to solve the above technical problems, a power plant boiler ash conveying detection system is provided. This technical solution solves the above problems.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is: a power plant boiler ash conveying detection system, including: a conveying module, an appearance detection module, a boiler combustion benefit evaluation module and a combustion optimization module;

[0005] The conveying module is used to convey boiler ash for testing;

[0006] The appearance detection module detects the appearance of the furnace ash based on image processing technology, and analyzes and evaluates the combustion status of the furnace ash based on the detected appearance.

[0007] The boiler combustion benefit evaluation module evaluates the current boiler combustion benefit based on the combustion status;

[0008] The combustion optimization module optimizes the boiler combustion conditions of the current power plant based on the evaluated benefits.

[0009] Preferably, the conveying module includes a sampling unit and a conveying unit. The sampling unit is used to sample the ash produced by combustion in the boiler. During the sampling process, the overall appearance shape of the ash is ensured to remain unchanged. The sampled ash is placed on the conveying unit, and the ash is conveyed by the conveying unit. The appearance detection module is located directly above the conveying unit, and the ash transported by the conveying unit is detected in real time.

[0010] Preferably, the appearance detection module includes a camera unit, a storage unit and an analysis unit. The camera unit is used to take real-time photos of the ash on the conveying module, and upload the captured images to the analysis unit for analysis to determine the combustion status of the ash. The analysis results are stored in the storage unit in real time for subsequent retrieval, viewing and analysis.

[0011] Preferably, the acquired ash image is preprocessed in the analysis unit, and the preprocessing includes graying, Gaussian filtering smoothing, normalization and format conversion. Feature extraction is performed on the preprocessed image, and the extracted features include color features, texture features and shape features. The extracted features are applied to the Canny operator for calculation, and edge detection is performed on the smoothed image to obtain the contour appearance information of the ash in the image; in the obtained edge detection image, the contour of the ash appears as a series of continuous white pixels, and the pixels constitute the boundary of the ash. Morphological operations are continued to be used to further process the edge image to smooth the contour, remove small noise and fill small holes in the contour. Finally, the appearance information of the ash contour is extracted, and the appearance information includes the length, shape and area of ​​the contour for subsequent analysis or recognition tasks.

[0012] Preferably, based on the contour appearance information of the ash in the image, the ash is classified, and the classification standard is:

[0013] The ash is light in color and has fine and uniform particles. In the current state, the ash is in a fully and completely burned state;

[0014] There are large particles of impurities and the ash is dark in color. In the current state, the ash is in an incomplete combustion state.

[0015] Preferably, the classification is based on logistic regression, and the logistic regression formula is:

[0016]

[0017] Where X is the input feature, a1 and a2 are parameters learned through training data, namely, the ash color and ash particle features, Y is the output value, P(Y=1X) means that given the input X, the output is Y, where the output value of Y is 0.7, which is the boundary of the decision classification. When the value of Y is between 1 and 0.7, the current ash is classified as a complete combustion state, and when the value of Y is between 0 and 0.7, the current ash is classified as an incomplete combustion state. The closer the value of Y is to 1, the more complete the boiler combustion is, and the closer the value of Y is to 0, the more incomplete the boiler combustion is.

[0018] Preferably, the boiler combustion efficiency evaluation module performs evaluation by obtaining the combustion conditions of the ash and the fuel consumption. The combustion conditions of the ash reflect the combustion efficiency of the fuel. If there are more combustible substances remaining in the ash, it means that the combustion is incomplete, which will lead to fuel waste and increased consumption. On the contrary, if the content of combustible substances in the ash is low, it means that the combustion efficiency is high and the fuel consumption is relatively reduced, thereby judging the efficiency of the boiler combustion in the current power plant.

[0019] Preferably, the combustion optimization module dynamically adjusts and optimizes the combustion strategy of the boiler based on the analysis results, comprehensively considers multiple factors such as fuel characteristics, load requirements, and environmental standards, and obtains the optimal fuel ratio, air-coal ratio, and secondary air adjustment strategy to improve combustion efficiency.

[0020] Preferably, the combustion optimization module also includes a benefit evaluation module, which regularly compares and analyzes the operating data before and after the optimization to evaluate the energy-saving and emission reduction effects, the improvement of economic benefits and the comprehensive benefits of extending the equipment life.

[0021] Preferably, the optimization measures of the combustion optimization module include:

[0022] Adjust the structure and position of the burner to improve the preheating of the combustion air and ensure that the fuel and air are fully mixed;

[0023] Ensure that the fuel can be fully burned, control the excess air coefficient, and reduce incomplete combustion losses;

[0024] Replace high-efficiency burner heads and adopt advanced combustion technology;

[0025] Clean the inside of the boiler, check the burner, adjust the combustion parameters, and keep the boiler in good condition;

[0026] Adjust the boiler's operating parameters according to actual needs;

[0027] Formulate energy consumption plans and monitor energy consumption;

[0028] Recover waste heat from boiler exhaust gas to heat water or other media, reducing fuel consumption;

[0029] The tail flue gas is used to heat the feed water and the air required for combustion, reducing heat loss and lowering the exhaust temperature.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention proposes an image processing technology that can accurately analyze the appearance characteristics, color, and particle size of ash, thereby accurately evaluating the combustion condition of ash, converting the combustion condition into specific benefit indicators, and providing managers with intuitive evaluation results. Based on the evaluation results, managers can make more scientific and reasonable decisions and optimize combustion strategies. By optimizing the combustion process, the thermal efficiency and power generation efficiency of the boiler can be improved, fuel consumption and operating costs can be reduced, and the economic benefits of the power plant can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a framework diagram of the invention detection system. DETAILED DESCRIPTION

[0033] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0034] Reference Figure 1 As shown, a boiler ash conveying and detection system for a power plant includes: a conveying module, an appearance detection module, a boiler combustion benefit evaluation module and a combustion optimization module;

[0035] The conveying module is used to convey boiler ash for testing;

[0036] The appearance detection module detects the appearance of the furnace ash based on image processing technology, and analyzes and evaluates the combustion status of the furnace ash based on the detected appearance.

[0037] The boiler combustion benefit evaluation module evaluates the current boiler combustion benefit based on the combustion status;

[0038] The combustion optimization module optimizes the boiler combustion conditions of the current power plant based on the evaluated benefits.

[0039] This application can ensure the rapid and stable transportation of boiler ash through the conveying module, reduce the accumulation of ash in the boiler, and improve the operating efficiency of the boiler. By real-time monitoring of the conveying status, the blockage problem in the conveying pipeline can be discovered and dealt with in time, avoiding the resulting production interruptions and safety hazards, and reducing equipment wear and failure caused by poor transportation, thereby reducing maintenance costs and downtime. Based on image processing technology, the appearance characteristics of the ash, including color and particle size, are accurately analyzed to accurately evaluate the combustion condition of the ash, and the combustion condition is converted into specific benefit indicators to provide managers with intuitive evaluation results. Based on the evaluation results, managers can make more scientific and reasonable decisions. By evaluating the combustion benefits, potential energy-saving and emission reduction space can be discovered, and the development of power plants in a green and low-carbon direction can be promoted. Optimizing the combustion process helps reduce the emission of nitrogen oxides and sulfur dioxide pollutants and reduce pollution to the environment.

[0040] The conveying module includes a sampling unit and a conveying unit. The sampling unit is used to sample the ash produced by combustion in the boiler. During the sampling process, the overall appearance and shape of the ash are ensured to remain unchanged. The sampled ash is placed on the conveying unit and the ash is conveyed by the conveying unit. The appearance inspection module is located directly above the conveying unit and performs real-time inspection of the ash transported by the conveying unit.

[0041] When the sampling unit of the present application samples the ash produced by combustion in the boiler, it can ensure that the overall appearance shape of the ash remains unchanged, which is crucial for subsequent appearance inspection, because the appearance characteristics of the ash directly reflect its combustion state and quality. The conveying unit is responsible for stably conveying the sampled ash to the appearance inspection module for inspection. During this process, the conveying unit needs to ensure that the ash is not damaged or contaminated during transportation to ensure the accuracy of the test results.

[0042] The appearance inspection module includes a camera unit, a storage unit and an analysis unit. The camera unit is used to take real-time photos of the ash on the conveying module, and upload the captured images to the analysis unit for analysis to determine the combustion status of the ash. The analysis results are stored in the storage unit in real time for subsequent viewing and analysis.

[0043] In this application, based on image processing technology, the appearance detection module can analyze the appearance characteristics of the ash with high precision. This high-precision analysis helps to more accurately evaluate the combustion of the ash and provide a more accurate basis for combustion optimization. By detecting the appearance characteristics of the ash in real time and evaluating its combustion, the system can adjust the combustion parameters in time to optimize the combustion process, which helps to improve the combustion efficiency of the boiler and reduce fuel consumption. The automated operation of the conveying module and the high-precision analysis of the appearance detection module reduce manual intervention and downtime, thereby reducing maintenance costs. By optimizing the combustion process to reduce pollutant emissions and reduce energy consumption, the system helps to improve the environmental benefits of power plants and meet increasingly stringent environmental regulations.

[0044] The acquired ash image is preprocessed in the analysis unit, and the preprocessing includes graying, Gaussian filtering smoothing, normalization and format conversion. Feature extraction is performed on the preprocessed image, and the extracted features include color features, texture features and shape features. The extracted features are applied to the Canny operator for calculation, and edge detection is performed on the smoothed image to obtain the contour appearance information of the ash in the image; in the obtained edge detection image, the contour of the ash appears as a series of continuous white pixels, and the pixels constitute the boundary of the ash. Morphological operations are continued to be used to further process the edge image to smooth the contour, remove small noise and fill small holes in the contour. Finally, the appearance information of the ash contour is extracted. The appearance information includes the length, shape and area of ​​the contour for subsequent analysis or recognition tasks.

[0045] This application converts color images into grayscale images, which can significantly reduce the amount of computational work in image processing. Because grayscale images only contain brightness information but not color information, the grayscale process can highlight the brightness information of the image, making the image more concise and clear, and convenient for subsequent processing. Gaussian filtering is an effective denoising method that can smooth random noise in the image and improve the quality of the image. Compared with other smoothing methods, Gaussian filtering can better retain the edge information of the image while removing noise. Normalization processing limits the pixel value of the image to a certain range (such as 0-1), which helps the stability and convergence of the subsequent processing algorithm. Normalization can reduce the data differences between different images and improve the recognition performance and accuracy of the image processing algorithm. Converting the image into a suitable format can improve its compatibility in different devices and software.

[0046] Based on the contour appearance information of the ash in the image, the ash is classified according to the following criteria:

[0047] The ash is light in color and has fine and uniform particles. In the current state, the ash is in a fully and completely burned state;

[0048] There are large particles of impurities and the ash is dark in color. In the current state, the ash is in an incomplete combustion state.

[0049] Classification is based on logistic regression, and the logistic regression formula is:

[0050]

[0051] Where X is the input feature, a1 and a2 are parameters learned through training data, namely, the ash color and ash particle features, Y is the output value, P(Y=1X) means that given the input X, the output is Y, where the output value of Y is 0.7, which is the boundary of the decision classification. When the value of Y is between 1 and 0.7, the current ash is classified as a complete combustion state, and when the value of Y is between 0 and 0.7, the current ash is classified as an incomplete combustion state. The closer the value of Y is to 1, the more complete the boiler combustion is, and the closer the value of Y is to 0, the more incomplete the boiler combustion is.

[0052] The boiler combustion efficiency evaluation module evaluates the ash combustion conditions and fuel consumption. The ash combustion conditions reflect the fuel combustion efficiency. If there are more combustible substances remaining in the ash, it means that the combustion is incomplete, which will lead to fuel waste and increased consumption. On the contrary, if the combustible substance content in the ash is low, it means that the combustion efficiency is high and the fuel consumption is relatively reduced, so as to judge the efficiency of boiler combustion in the current power plant.

[0053] Based on the analysis results, the combustion optimization module dynamically adjusts and optimizes the boiler's combustion strategy, comprehensively considering multiple factors such as fuel characteristics, load requirements, and environmental standards to obtain the optimal fuel ratio, air-coal ratio, and secondary air adjustment strategy to improve combustion efficiency.

[0054] By evaluating the combustion of ash, this application can timely discover the problem of incomplete combustion, thereby adjusting the combustion strategy, reducing the residual combustible material in the fuel, and avoiding unnecessary fuel waste, which directly reduces the operating cost of the power plant. The combustion optimization module dynamically adjusts the combustion strategy according to the evaluation results, such as optimizing the fuel ratio, wind-coal ratio and secondary air adjustment strategy, so as to improve the combustion efficiency. The improvement of combustion efficiency means that more heat or electricity can be generated under the same fuel consumption, further improving the economic benefits of the power plant. Long-term incomplete combustion will lead to boiler ash accumulation and coking problems, increase maintenance difficulty and cost, and timely optimize the combustion strategy to reduce the occurrence of these problems and reduce maintenance costs. Combustion optimization can not only improve combustion efficiency, but also reduce the generation and emission of harmful substances. By optimizing the combustion strategy, the emission of nitrogen oxides (NOx) and sulfur dioxide (SO2) pollutants can be reduced, which helps to improve air quality and protect the ecological environment. With the increasingly stringent environmental regulations, power plants need to continuously reduce pollutant emissions to meet environmental standards. The combustion optimization module can dynamically adjust the combustion strategy according to environmental standards to ensure that the power plant always meets environmental protection requirements.

[0055] The combustion optimization module also includes a benefit evaluation module, which regularly compares and analyzes the operating data before and after optimization to evaluate the energy-saving and emission reduction effects, economic benefit improvements, and the comprehensive benefits of extending equipment life.

[0056] The optimization measures of the combustion optimization module include:

[0057] Adjust the structure and position of the burner to improve the preheating of the combustion air and ensure that the fuel and air are fully mixed;

[0058] Ensure that the fuel can be fully burned, control the excess air coefficient, and reduce incomplete combustion losses;

[0059] Replace high-efficiency burner heads and adopt advanced combustion technology;

[0060] Clean the inside of the boiler, check the burner, adjust the combustion parameters, and keep the boiler in good condition;

[0061] Adjust the boiler's operating parameters according to actual needs;

[0062] Formulate energy consumption plans and monitor energy consumption;

[0063] Recover waste heat from boiler exhaust gas to heat water or other media, reducing fuel consumption;

[0064] The tail flue gas is used to heat the feed water and the air required for combustion, reducing heat loss and lowering the exhaust temperature.

[0065] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A power plant boiler ash conveying detection system, characterized in that: include: Conveying module, appearance inspection module, boiler combustion benefit evaluation module and combustion optimization module; The conveying module is used to convey boiler ash for testing; The appearance detection module detects the appearance of the furnace ash based on image processing technology, and analyzes and evaluates the combustion status of the furnace ash based on the detected appearance. The boiler combustion benefit evaluation module evaluates the current boiler combustion benefit based on the combustion status; The combustion optimization module optimizes the boiler combustion conditions of the current power plant based on the evaluated benefits.

2. A power plant boiler ash conveying detection system according to claim 1, characterized in that: The conveying module includes a sampling unit and a conveying unit. The sampling unit is used to sample the ash produced by combustion in the boiler. During the sampling process, the overall appearance and shape of the ash are ensured to remain unchanged. The sampled ash is placed on the conveying unit and the ash is conveyed by the conveying unit. The appearance inspection module is located directly above the conveying unit and performs real-time inspection of the ash transported by the conveying unit.

3. A power plant boiler ash conveying detection system according to claim 1, characterized in that: The appearance inspection module includes a camera unit, a storage unit and an analysis unit. The camera unit is used to take real-time photos of the ash on the conveying module, and upload the captured images to the analysis unit for analysis to determine the combustion status of the ash. The analysis results are stored in the storage unit in real time for subsequent viewing and analysis.

4. A power plant boiler ash conveying detection system according to claim 3, characterized in that: The acquired ash image is preprocessed in the analysis unit, and the preprocessing includes graying, Gaussian filtering smoothing, normalization and format conversion. Feature extraction is performed on the preprocessed image, and the extracted features include color features, texture features and shape features. The extracted features are applied to the Canny operator for calculation, and edge detection is performed on the smoothed image to obtain the contour appearance information of the ash in the image; in the obtained edge detection image, the contour of the ash appears as a series of continuous white pixels, and the pixels constitute the boundary of the ash. Morphological operations are continued to be used to further process the edge image to smooth the contour, remove small noise and fill small holes in the contour. Finally, the appearance information of the ash contour is extracted. The appearance information includes the length, shape and area of ​​the contour for subsequent analysis or recognition tasks.

5. A power plant boiler ash conveying detection system according to claim 4, characterized in that: Based on the contour appearance information of the ash in the image, the ash is classified according to the following criteria: The ash is light in color and has fine and uniform particles. In the current state, the ash is in a fully and completely burned state; There are large particles of impurities and the ash is dark in color. In the current state, the ash is in an incomplete combustion state.

6. A power plant boiler ash conveying detection system according to claim 5, characterized in that: Classification is based on logistic regression, and the logistic regression formula is: Where X is the input feature, a1 and a2 are parameters learned through training data, namely, the ash color and ash particle features, Y is the output value, P(Y=1X) means that given the input X, the output is Y, where the output value of Y is 0.7, which is the boundary of the decision classification. When the value of Y is between 1 and 0.7, the current ash is classified as a complete combustion state, and when the value of Y is between 0 and 0.7, the current ash is classified as an incomplete combustion state. The closer the value of Y is to 1, the more complete the boiler combustion is, and the closer the value of Y is to 0, the more incomplete the boiler combustion is.

7. A power plant boiler ash conveying detection system according to claim 1, characterized in that: The boiler combustion efficiency evaluation module evaluates the ash combustion conditions and fuel consumption. The ash combustion conditions reflect the fuel combustion efficiency. If there are more combustible substances remaining in the ash, it means that the combustion is incomplete, which will lead to fuel waste and increased consumption. On the contrary, if the combustible substance content in the ash is low, it means that the combustion efficiency is high and the fuel consumption is relatively reduced, so as to judge the efficiency of boiler combustion in the current power plant.

8. A power plant boiler ash conveying detection system according to claim 1, characterized in that: Based on the analysis results, the combustion optimization module dynamically adjusts and optimizes the boiler's combustion strategy, comprehensively considering multiple factors such as fuel characteristics, load requirements, and environmental standards to obtain the optimal fuel ratio, air-coal ratio, and secondary air adjustment strategy to improve combustion efficiency.

9. A power plant boiler ash conveying detection system according to claim 1, characterized in that: The combustion optimization module also includes a benefit evaluation module, which regularly compares and analyzes the operating data before and after optimization to evaluate the energy-saving and emission reduction effects, economic benefit improvements, and the comprehensive benefits of extending equipment life.

10. A power plant boiler ash conveying detection system according to claim 1, characterized in that: The optimization measures of the combustion optimization module include: Adjust the structure and position of the burner to improve the preheating of the combustion air and ensure that the fuel and air are fully mixed; Ensure that the fuel can be fully burned, control the excess air coefficient, and reduce incomplete combustion losses; Replace high-efficiency burner heads and adopt advanced combustion technology; Clean the inside of the boiler, check the burner, adjust the combustion parameters, and keep the boiler in good condition; Adjust the boiler's operating parameters according to actual needs; Formulate energy consumption plans and monitor energy consumption; Recover waste heat from boiler exhaust gas to heat water or other media, reducing fuel consumption; The tail flue gas is used to heat the feed water and the air required for combustion, reducing heat loss and lowering the exhaust temperature.

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