A power plant monitoring system

Abstract

The application discloses a power plant monitoring system, comprising a risk area division module, a front-end area image acquisition module, an area risk level input module, an image noise point processing module, a local occupancy rate analysis module and a risk proportion measurement module, through collecting power plant equipment warning area graphic data, and according to the risk level divided by the invasion rate, the risk image is classified by the local occupancy rate analysis module, then the numerical summation is carried out, the risk digital parameters of each area are generated, and specific data indexes which are quantifiable and comparable are formed, then the data is substituted according to the risk proportion of the known local area in the warning area, the specific value of the risk digital parameter is corrected, at this time, the data monitoring terminal can analyze the corrected risk digital parameter to complete risk discrimination, compared with the prior art, the risk misjudgment in the monitoring process can be further reduced, and the high-precision monitoring requirement is fully met.

Description

Technical Field

[0001] This invention belongs to the field of monitoring and control system technology, and specifically relates to a power plant monitoring system. Background Technology

[0002] The purpose of a power plant monitoring system is to utilize cameras and other equipment to transform the physical conditions of various areas of the power plant into analyzable digital images. This provides raw data for subsequent risk assessment, enabling timely detection of anomalies within the production area through real-time image acquisition, thus providing early warnings, preventing accidents, and ensuring the safe and stable operation of the power plant. Existing power plant monitoring systems typically use image acquisition equipment to monitor production areas, lacking functional division and risk level settings for these areas. They cannot differentiate the impact of different areas on overall safety, and the allocation of monitoring resources is not reasonable. Furthermore, traditional systems only process risk images at the single image level, failing to categorize and quantify them by area, making it difficult to form unified risk assessment parameters. This results in inaccurate risk assessments and fails to meet the requirements for high-precision monitoring. Therefore, we propose a new power plant monitoring system. Summary of the Invention

[0003] This invention provides a power plant monitoring system to solve the problems mentioned in the background art.

[0004] This invention provides the following technical solution: a power plant monitoring system, including a risk area division module, a front-end area image acquisition module, an area risk level input module, an image noise processing module, a local occupancy rate analysis module, and a risk proportion calculation module; The risk area division module is used to divide the power plant production area into local areas. The divided production areas include operation activity area, operating equipment area, non-controlled production area and real-time control area. The area risk level input module sets the risk level according to the risk impact of each area on the production area. After reading the risk image output by the front-end area image acquisition module, the local occupancy analysis module classifies the risk image according to its generating area. Then, according to the risk level set by the risk area division module, the risk images of each area are numerically summed to obtain the risk numerical parameters of each area. Using the above scheme, graphic data of warning areas of power plant equipment are collected, and risk levels are divided according to intrusion rate. The risk images are then classified by region through the local occupancy rate analysis module, and the values ​​are summed to generate risk numerical parameters for each region, forming specific data indicators that can be quantified and compared. Then, the specific values ​​of the risk numerical parameters are corrected by substituting the data into the known risk proportion of local areas in the warning area.

[0005] The risk weight calculation module calculates the risk weight based on the risk impact weight of each production area entered into the known database, substitutes the obtained risk numerical parameters of each area into the weight, and obtains the corrected risk numerical parameters, which are then used as reference values ​​for the current risk status analysis of each area.

[0006] Using the above technical solution, the power plant production area is divided into multiple functional areas through the risk area division module, and the area risk level input module sets a risk level for each area, and sets reference values ​​for warning content according to the risk proportion of different areas.

[0007] A further improvement of the present invention is that, after the image noise processing module acquires the risk images acquired by the front-end region image acquisition module, it classifies the risk images with noise, and sends a debugging signal to the front-end region image acquisition module according to the region of the risk images with noise, so that the front-end region image acquisition module performs a second verification of the current image, and after verification, the image noise processing module removes the no-risk noisy images.

[0008] By adopting the above technical solution, images with noise are automatically identified and classified, and debugging signals are sent to the front-end image acquisition module for secondary verification, eliminating noisy images without risk and reducing the possibility of false alarms.

[0009] A further improvement of the present invention is that the front-end area image acquisition module includes acquisition cameras, data transmitters, and orientation angle adjustment units arranged opposite each divided production area. The acquisition cameras are connected to the adjustment end of the orientation angle adjustment unit to realize real-time adjustment of the acquisition angle. The data transmitter is signal-connected to the risk area division module.

[0010] Using the above technical solution, after obtaining the risk image acquired by the front-end area image acquisition module, the specific area of ​​the production area where the risk image with noise is located is classified. Then, a debugging signal is sent to the front-end area image acquisition module, so that the front-end area image acquisition module performs a second image acquisition in comparison with the specific area of ​​the production area where the risk image with noise is located, and verifies whether the suspected risk object in the image is a regional interferometer.

[0011] A further improvement of the present invention is that one end of the risk proportion calculation module is connected to the data monitoring module, and the data monitoring module records the risk digital parameter threshold that triggers the warning signal.

[0012] A further improvement of the present invention is that the proposed data monitoring terminal is connected to the power plant monitoring terminal by signal, and after the power plant monitoring terminal obtains the corrected risk digital parameters, it performs threshold comparison analysis to determine whether to trigger the warning signal of the power plant monitoring terminal.

[0013] A further improvement of the present invention is that the data monitoring terminal is also provided with an image monitoring reset unit. When the data monitoring terminal analyzes that the currently corrected risk digital parameters have not triggered the warning signal of the intended data monitoring terminal, the image monitoring reset unit switches the front-end area image acquisition module to perform the next cycle of image acquisition.

[0014] A further improvement of the present invention is a method for using a power plant monitoring system, comprising the following steps: Step S10: Collect graphic data of warning areas for power plant equipment and classify risk levels according to intrusion rate; Step S20: Acquire images with suspicious noise points, mark the locations of noise points in the images, and debug the acquisition port for secondary image analysis; Step S30: After classifying the risk levels, the images are integrated according to their assigned areas and output as risk numerical parameters; Step S40: Substitute the known risk proportion of the local area in the warning zone into the data and correct the specific value of the risk numerical parameter; Step S50: Analyze the risk status. The data monitoring terminal analyzes the currently corrected risk digital parameters. If the warning signal of the planned data monitoring terminal is not triggered, the front-end area image acquisition module is switched to perform image acquisition for the next cycle. If the currently corrected risk digital parameters exceed the trigger threshold, the planned data monitoring terminal sends a warning signal.

[0015] Compared with existing technologies, the beneficial effects of this invention are as follows: This system collects graphic data of warning areas of power plant equipment, classifies risk levels according to intrusion rates, and then uses a local occupancy rate analysis module to classify risk images by region and sum the values ​​to generate risk digital parameters for each region, forming quantifiable and comparable specific data indicators. Then, based on the known risk proportion of local areas in the warning area, the data is substituted to correct the specific values ​​of the risk digital parameters. At this time, the data monitoring terminal can analyze the currently corrected risk digital parameters to complete the risk judgment. Compared with existing technologies, this can further reduce risk misjudgment during the monitoring process and fully meet the high-precision monitoring requirements. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the usage of a power plant monitoring system according to the present invention. Figure 2 This is a diagram illustrating the composition of a power plant monitoring system according to the present invention. Detailed Implementation

[0017] The present invention will be further described below with reference to specific embodiments. The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the present invention. In order to better illustrate the specific embodiments of the present invention, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the actual product size. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings. Based on the specific embodiments of the present invention, all other specific embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] In this embodiment, to address the problems of existing monitoring systems lacking data adjustment functions, being unable to classify production areas and set risk levels, failing to distinguish the impact of different areas on overall safety, having inadequate allocation of monitoring resources, and traditional systems processing risk images only at the single image level without categorizing by area and performing quantitative analysis, making it difficult to form unified risk assessment parameters, this invention proposes a power plant monitoring system. Please refer to [link / reference]. Figures 1-2 It includes a risk area division module, a front-end area image acquisition module, an area risk level input module, an image noise processing module, a local occupancy analysis module, and a risk proportion calculation module. The risk area division module is used to divide the power plant production area into local areas. The divided production areas include the operation activity area, the operating equipment area, the non-controlled production area and the real-time control area. The area risk level input module sets the risk level according to the risk impact of each area on the production area. In one optional embodiment of this example, after the local occupancy analysis module reads the risk image output by the front-end area image acquisition module, it classifies the risk image according to the area where it was generated. Then, according to the risk level set by the risk area division module, it sums the values ​​of the risk images after unified classification of each area to obtain the risk digital parameters of each area. It should be noted that this invention uses a local occupancy analysis module to classify risk images by region and then sums the values ​​to generate risk numerical parameters for each region. This transforms the collected image information into quantifiable and comparable data, providing more intuitive comparison data for subsequent risk assessment.

[0019] In one optional embodiment of this example, the risk weight calculation module calculates the risk weight based on the risk impact weight of each production area entered into the known database, substitutes the obtained risk numerical parameters of each area into the weight, and obtains the corrected risk numerical parameters, which are then used as reference values ​​for the current risk status analysis of each area.

[0020] It should be noted that the risk weighting calculation module, combined with the known impact weight of each region on the overall risk in the database, processes the initially obtained risk numerical parameters through weighted correction. Based on the weight differences of different regions in overall safety, the final risk reference value is made to conform to the actual production situation, thereby improving the accuracy of risk assessment.

[0021] In one optional embodiment of this example, after the image noise processing module obtains the risk images collected by the front-end region image acquisition module, it classifies the risk images with noise and sends a debugging signal to the front-end region image acquisition module according to the risk image regions with noise, so that the front-end region image acquisition module performs a second verification of the current image, and after verification, the image noise processing module removes the no-risk noisy images.

[0022] It should be noted that this solution automatically identifies and classifies noisy images by setting up an image noise processing module, and sends a debugging signal to the front-end area image acquisition module for secondary verification, eliminating noisy images without risk and reducing the possibility of false alarms. The image noise processing module is a functional module of the existing image recognition and analysis system. After obtaining the risk image acquired by the front-end area image acquisition module, it classifies the specific area of ​​the production area where the risky image with noise is located, and then sends a debugging signal to the front-end area image acquisition module, so that the front-end area image acquisition module performs secondary image acquisition against the specific area of ​​the production area where the risky image with noise is located, and verifies whether the suspected risk object in the image is a regional interference body (specifically, a non-worker). If it is not a regional interference body, the suspected image is deleted.

[0023] In this embodiment, by setting an image monitoring reset unit, the system automatically switches the front-end device to perform the next cycle of image acquisition when no warning signal is triggered, thereby realizing automated cyclic monitoring. At the same time, a risk threshold is set through the data monitoring module and a signal connection is established with the power plant monitoring terminal. If the corrected risk parameter exceeds the limit, a warning signal is triggered on the power plant monitoring terminal, thereby realizing automated triggering and improving the overall response efficiency of the monitoring system.

[0024] In one optional embodiment of this example, the front-end area image acquisition module includes acquisition cameras, data transmitters, and orientation angle adjustment units that are arranged facing each other in the divided production areas. The acquisition cameras are connected to the adjustment end of the orientation angle adjustment unit to realize real-time adjustment of the acquisition angle. The data transmitters are signal-connected to the risk area division module.

[0025] In one optional embodiment of this example, one end of the risk proportion calculation module is connected to the data monitoring module, and the data monitoring module records the risk digital parameter threshold that triggers the warning signal.

[0026] In this embodiment, since different areas within the power plant (operation activity area, operating equipment area, non-controlled production area, and real-time control area) have different degrees of impact on production safety, in order to improve monitoring accuracy, the present invention divides the power plant production area into multiple functional areas through a risk area division module, and sets a risk level for each area by a regional risk level input module, and sets reference values ​​for warning content according to the risk proportion of different areas.

[0027] In one optional embodiment of this example, the data monitoring terminal is designed to be connected to the power plant monitoring terminal. After the data monitoring terminal obtains the corrected risk digital parameters, it performs threshold comparison analysis to determine whether to trigger the warning signal of the power plant monitoring terminal.

[0028] In an optional embodiment of this example, the data monitoring terminal is further provided with an image monitoring reset unit. When the data monitoring terminal analyzes that the currently corrected risk digital parameters have not triggered the warning signal of the intended data monitoring terminal, the image monitoring reset unit switches the front-end area image acquisition module to perform image acquisition for the next cycle.

[0029] This embodiment also provides a method for using a power plant monitoring system, including the following steps: Step S10: Collect graphic data of warning areas of power plant equipment and classify risk levels according to intrusion rate.

[0030] Step S20: Acquire images with suspicious noise, mark the locations of noise points in the images, and debug the acquisition port for secondary image analysis.

[0031] Step S30: After classifying the risk levels, the images are integrated according to their assigned areas and output as risk numerical parameters.

[0032] Step S40: Substitute the known risk proportion of the local area in the warning zone into the data and correct the specific value of the risk numerical parameter.

[0033] Step S50: Analyze the risk status. The data monitoring terminal analyzes the currently corrected risk digital parameters. If the warning signal of the planned data monitoring terminal is not triggered, the front-end area image acquisition module is switched to perform image acquisition for the next cycle. If the currently corrected risk digital parameters exceed the trigger threshold, the planned data monitoring terminal sends a warning signal.

[0034] It should be noted that this system collects graphic data of warning areas of power plant equipment, classifies risk levels according to intrusion rates, and then uses a local occupancy rate analysis module to categorize risk images by region and sum the values ​​to generate risk numerical parameters for each region. This forms quantifiable and comparable specific data indicators. Subsequently, based on the known risk proportion of local areas in the warning zone, the data is substituted to correct the specific values ​​of the risk numerical parameters. At this point, the data monitoring terminal can analyze the currently corrected risk numerical parameters to complete the risk judgment. Compared with existing technologies, this can further reduce risk misjudgment during the monitoring process and fully meet the needs of high-precision monitoring.

[0035] The foregoing has shown and described 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 embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A power plant monitoring system, characterized in that: It includes a risk area delineation module, a front-end area image acquisition module, an area risk level input module, an image noise processing module, a local occupancy analysis module, and a risk weight calculation module. The risk area division module is used to divide the power plant production area into local areas. The divided production areas include operation activity area, operating equipment area, non-controlled production area and real-time control area. The area risk level input module sets the risk level according to the risk impact of each area on the production area. After reading the risk image output by the front-end area image acquisition module, the local occupancy analysis module classifies the risk image according to its generating area. Then, according to the risk level set by the risk area division module, the risk images of each area are numerically summed to obtain the risk numerical parameters of each area. The risk weight calculation module calculates the risk weight based on the risk impact weight of each production area entered into the known database, substitutes the obtained risk numerical parameters of each area into the weight, and obtains the corrected risk numerical parameters, which are then used as reference values ​​for the current risk status analysis of each area.

2. The power plant monitoring system according to claim 1, characterized in that: After the image noise processing module acquires the risk images collected by the front-end region image acquisition module, it classifies the risk images with noise and sends a debugging signal to the front-end region image acquisition module according to the region of the risk images with noise, so that the front-end region image acquisition module performs a second verification of the current image. After verification, the image noise processing module removes the no-risk noisy images.

3. A power plant monitoring system according to claim 2, characterized in that: The front-end area image acquisition module includes acquisition cameras, data transmitters, and orientation angle adjustment units, which are arranged facing each other in the divided production areas. The acquisition cameras are connected to the adjustment end of the orientation angle adjustment unit to realize real-time adjustment of the acquisition angle. The data transmitter is signal-connected to the risk area division module.

4. A power plant monitoring system according to claim 3, characterized in that: One end of the risk proportion calculation module is connected to the data monitoring module, and the data monitoring module records the risk digital parameter threshold that triggers the warning signal.

5. A power plant monitoring system according to claim 4, characterized in that: The proposed data monitoring terminal is connected to the power plant monitoring terminal via a signal connection. After the data monitoring terminal acquires the corrected risk digital parameters, it performs threshold comparison analysis to determine whether to trigger the warning signal of the power plant monitoring terminal.

6. A power plant monitoring system according to claim 5, characterized in that: The data monitoring terminal is also equipped with an image monitoring reset unit. When the data monitoring terminal analyzes that the currently corrected risk digital parameters have not triggered the warning signal of the intended data monitoring terminal, the image monitoring reset unit switches the front-end area image acquisition module to perform image acquisition for the next cycle.

7. A method of using a power plant monitoring system according to any one of claims 1-6, characterized in that, Includes the following steps: Step S10: Collect graphic data of warning areas for power plant equipment and classify risk levels according to intrusion rate; Step S20: Acquire images with suspicious noise points, mark the locations of noise points in the images, and debug the acquisition port for secondary image analysis; Step S30: After classifying the risk levels, the images are integrated according to their assigned areas and output as risk numerical parameters; Step S40: Substitute the known risk proportion of the local area in the warning zone into the data and correct the specific value of the risk numerical parameter; Step S50: Analyze the risk status. The data monitoring terminal analyzes the currently corrected risk digital parameters. If the warning signal of the planned data monitoring terminal is not triggered, the front-end area image acquisition module is switched to perform image acquisition for the next cycle. If the currently corrected risk digital parameters exceed the trigger threshold, the planned data monitoring terminal sends a warning signal.

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