Water conservancy and hydropower equipment remote operation and maintenance management system based on Internet of Things

Abstract

The invention relates to the technical field of water conservancy and hydropower equipment, in particular to a water conservancy and hydropower equipment remote operation and maintenance management system based on the Internet of Things, and the system comprises a front-end monitoring module which is used for monitoring the quality of a water body introduced into a grid trash remover; the sensing module is used for sensing operation state parameters of the grid trash remover in real time when the grid trash remover is in an operation state; the evaluation module is used for receiving the water quality monitoring result in the front-end monitoring module and the operation state parameters of the grid trash remover in the sensing module, and evaluating the current performance state of the grid trash remover by combining the two; according to the method, the water quality monitoring result is used as a parameter for evaluating the running state of the grating trash-cleaning machine, the auxiliary system performs running safety evaluation on the grating trash-cleaning machine in combination with the running state parameter of the grating trash-cleaning machine, a visual image representing the change of the running state of the grating trash-cleaning machine is generated based on the evaluation result, and different early warning logics are configured, so that the operation safety of the grating trash-cleaning machine is improved. And an operation safety early warning of the grating trash remover is sent out, so that a guarantee is provided for stable operation of the grating trash remover.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy and hydropower equipment, and in particular to a remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things. Background Art

[0002] Screen cleaners are crucial in water conservancy and hydropower projects. Installed at the water inlet, they effectively intercept debris such as branches, weeds, and garbage from the water flow. By continuously cleaning, they ensure smooth water flow to turbines and other equipment, preventing damage and maintaining power generation efficiency. These devices play a key role in ensuring stable project operation and equipment safety.

[0003] The invention patent application with application number 202210969479.4 discloses an intelligent monitoring and early warning method for a grate garbage cleaning machine, the method comprising: obtaining a forebay monitoring image, a first bucket monitoring image, and a second bucket monitoring image; identifying and extracting regions of interest from the forebay monitoring image, the first bucket monitoring image, and the second bucket monitoring image respectively; according to a preset garbage recognition model, identifying forebay garbage from the region of interest of the forebay monitoring image, identifying garbage in the bucket from the region of interest of the first bucket monitoring image, and identifying garbage under the bucket from the region of interest of the second bucket monitoring image; calculating the proportion of forebay garbage based on the identified forebay garbage, and if the proportion of the forebay garbage is greater than a preset first garbage proportion threshold, issuing a forebay garbage abnormality alarm; screening out large pieces of garbage in the bucket based on the identified garbage in the bucket, and if the length of the large pieces of garbage in the bucket is greater than a preset length threshold, issuing a garbage abnormality alarm in the bucket; screening out large pieces of garbage under the bucket based on the identified garbage under the bucket, and if the proportion of the large pieces of garbage under the bucket is greater than A second garbage ratio threshold is preset to issue an alarm for abnormal garbage under the bucket; the method also includes: obtaining a third bucket monitoring image, identifying and extracting an area of ​​interest from the third bucket monitoring image; inputting the area of ​​interest in the third bucket monitoring image into a preset bucket tilt detection model to obtain the horizontal tilt angle of the bucket; if the horizontal tilt angle of the bucket is greater than the preset angle threshold, an alarm for abnormal bucket tilt is issued. This application solves the problem that "in the daily operation of the screen cleaning machine, the screen cleaning machine is often damaged or even shut down due to situations such as the bars being stuck by garbage, the bucket being tilted by garbage, and the motor being overloaded and heated due to being stuck. The failure will affect the daily production of the water treatment plant. At present, during the daily operation of the equipment, the water treatment plant uses manual regular patrols to monitor the garbage situation in the sewage lift pump collection pool and decide whether to start the screen cleaning machine. At the same time, it is necessary to monitor the operating status of the equipment. If there is any abnormality, the equipment will be shut down. However, this method wastes a lot of human resources and may affect the operation of the screen cleaning machine due to missed inspections due to lack of concentration."

[0004] However, existing technologies for monitoring the operation of screen cleaning machines often focus on fault diagnosis of the equipment itself, lacking in predictive power. Furthermore, fault diagnosis typically only considers the equipment's own operating parameters, without taking into account parameters related to the water being treated by the equipment. To this end, a remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things was proposed. Summary of the Invention

[0005] In view of the above shortcomings of the prior art, the present invention provides a remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things, which solves the technical problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things includes: The front-end monitoring module is used to monitor the water quality of the screen cleaning machine introduced; the perception module is used to perceive the operating status parameters of the screen cleaning machine in real time when the screen cleaning machine is in operation; the evaluation module is used to receive the water quality monitoring results in the front-end monitoring module and the operating status parameters of the screen cleaning machine in the perception module, and combine the two to evaluate the current performance status of the screen cleaning machine; the early warning module is used to set the safety judgment threshold of the performance status of the screen cleaning machine, receive the current performance status evaluation result of the screen cleaning machine in the evaluation module, compare the evaluation result with the judgment threshold, and trigger an early warning prompt when the evaluation result is less than the judgment threshold; the message module is used to record the trigger time of the historical early warning prompt of the early warning module, and generate the screen cleaning machine operation message based on the recorded trigger time.

[0007] Furthermore, the front-end monitoring module is integrated with a camera, and the front-end monitoring module is operated to collect images of the water body introduced into the screen cleaning machine, and monitor the water quality based on the water body images; The front-end monitoring module performs a water quality monitoring based on a preset time threshold, and when collecting water body images within the preset time threshold, the water body image collection frequency is adaptively controlled based on the flow rate of the water body introduced into the screen cleaning machine, so that the faster the water flow rate, the higher the water body image collection frequency, and the slower the water flow rate, the lower the water body image collection frequency; Among them, the front-end monitoring module and the perception module run synchronously in the system.

[0008] Furthermore, the monitoring logic of the water quality of the screen cleaning machine introduced into the front-end monitoring module is expressed as follows: ; Where: C is the water quality performance value; n is the total amount of water body images; α and β are weight coefficients; M and N are the width and height of the water body image; F i(x, y) is the pixel value at coordinate (x, y) of the i-th water body image after grayscale processing and Gaussian filtering; is the average gray value of the water body image; S i is the image area of ​​the impurity region segmented by the image segmentation algorithm for the i-th water body image; A is the area of ​​the water body image; Among them, the weight coefficients α and β are both positive numbers, and the sum of their addition is 1. The values ​​of the two are customized by the system user. The larger C is, the worse the water quality is, and vice versa.

[0009] Furthermore, the operating status parameters of the screen cleaning machine sensed by the sensing module include: operating power, water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth; Among them, the perception module stores the perceived operating status parameters of the screen cleaning machine, and in the storage stage, differentiates and stores them based on the preset time threshold of the front-end monitoring module operation application, so that the source time threshold of the screen cleaning machine operating status parameters stored in each differentiated storage interval is equal to the preset time threshold of the front-end monitoring module operation application.

[0010] Furthermore, in the evaluation module, during the evaluation phase of the current performance status of the screen cleaning machine, the health of the screen cleaning machine's operating status is evaluated based on the screen cleaning machine's operating status parameters; Define the parameter deviation value, taking operating power as an example: ; Where: ΔP is the operating power deviation value; (P min ,P max ) is the normal operating power range; The average operating power value of the operating status parameters of the screen cleaning machine perceived by the sensing module; Among them, the parameter deviation value definition logic of the water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth in the screen cleaning machine operating status parameters is the same as the operating power deviation value definition logic. The calculation results of the deviation values ​​of the water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth are recorded as ΔH, ΔN, ΔT, and ΔD.

[0011] Furthermore, the operational health assessment logic of the screen cleaning machine is: ; The larger the S is, the better the operation health of the screen cleaning machine is; conversely, the smaller the S is, the worse the operation health of the screen cleaning machine is. The evaluation logic of the current performance status of the grid cleaning machine in the evaluation module is: ; Where: is the current performance value of the screen cleaning machine; S is the operational health of the screen cleaning machine; C is the water quality performance value; in, The larger the value, the better the current performance of the screen cleaning machine is; conversely, the smaller the value, the worse the current performance of the screen cleaning machine is.

[0012] Furthermore, the safety judgment threshold of the performance status of the grille cleaning machine in the early warning module is customized by the system end user. When the early warning module triggers the early warning prompt, the early warning module sends an early warning prompt information to the grille cleaning machine management backend. The content of the early warning prompt information is a text message preset by the system end user in text format; The early warning module is provided with a visualization unit and a prediction unit at a lower level. The visualization unit is used to record the evaluation results received by the early warning module and generate a line graph representing the trend of the evaluation results based on the evaluation results. The prediction unit is used to traverse the line graph generated in the visualization unit and predict whether there are hidden dangers in the grille cleaning machine based on the line graph. Among them, when the prediction result of the prediction unit operation is yes, the control warning module synchronously triggers the warning prompt. The warning prompt content triggered by the prediction unit is different from the warning prompt content triggered by the autonomous operation of the warning module, and the warning prompt content triggered by the prediction unit is customized by the system user.

[0013] Furthermore, the prediction unit updates the line graph in real time based on the evaluation results received by the early warning module, and when the line graph contains the evaluation results applied when the early warning module autonomously triggers the early warning prompt, the line graph is reset and regenerated based on the subsequently received evaluation results; When the prediction unit traverses the line graph to predict whether there are hidden dangers in the grille cleaning machine, it predicts based on the lines corresponding to the three latest evaluation results in the line graph. If the line is continuously decreasing, the prediction result is yes, otherwise, the prediction result is no.

[0014] Furthermore, the content of the screen cleaning machine operation message generated by the message module further includes the screen cleaning machine performance status evaluation result corresponding to the early warning prompt triggering time; Among them, the screen cleaning machine operation message generated by the message module is fed back to the screen cleaning machine management background in real time.

[0015] Furthermore, the front-end monitoring module is interactively connected with the perception module and the evaluation module through a wireless network, the evaluation module is interactively connected with the early warning module through a wireless network, the early warning module is interactively connected with the visualization unit and the prediction unit through a wireless network, and the early warning module is interactively connected with the message module through a wireless network.

[0016] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects: The present invention provides a remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things. During operation, the system introduces water quality monitoring of a screen cleaning machine as a parameter for evaluating the operating status of the screen cleaning machine. The system further assists the system in performing an operational safety assessment of the screen cleaning machine in combination with the operating status parameters of the screen cleaning machine itself. At the same time, based on the assessment results, a visual image representing the change in the operating status of the screen cleaning machine is generated, and different early warning logics are configured to issue an operational safety warning for the screen cleaning machine, thereby providing a guarantee for the long-term and stable operation of the screen cleaning machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort.

[0018] Figure 1 This is a structural diagram of the remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things. DETAILED DESCRIPTION

[0019] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0020] The present invention will be further described below with reference to the embodiments.

[0021] Example: The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things in this embodiment is as follows: Figure 1 As shown, including: Front-end monitoring module, used to monitor the quality of water introduced into the screen cleaning machine; The front-end monitoring module is integrated with a camera. The front-end monitoring module collects water images introduced into the screen cleaning machine and monitors water quality based on the water images. The front-end monitoring module performs a water quality monitoring based on a preset time threshold. When collecting water images within the preset time threshold, the water image collection frequency is adaptively controlled based on the flow rate of the water introduced into the screen cleaning machine. The faster the water flow rate, the higher the water image collection frequency, and the slower the water flow rate, the lower the water image collection frequency. Among them, the front-end monitoring module and the perception module run synchronously in the system; The monitoring logic of the water quality of the screen cleaning machine introduced into the front-end monitoring module is expressed as follows: ; Where: C is the water quality performance value; n is the total amount of water body images; α and β are weight coefficients; M and N are the width and height of the water body image; F i (x, y) is the pixel value at coordinate (x, y) of the i-th water body image after grayscale processing and Gaussian filtering; is the average gray value of the water body image; S i is the image area of ​​the impurity region segmented by the image segmentation algorithm for the i-th water body image; A is the area of ​​the water body image; Among them, the weight coefficients α and β are both positive numbers, and the sum of their addition is 1. The values ​​of the two are customized by the system end user. The larger the C is, the worse the water quality is, and vice versa, the better the water quality is. The water quality performance value is calculated through the above logical formula to provide support for the further operation of the evaluation module in the system. The monitoring results are expressed in this digital form, which makes it easier for system users to read and judge the specific conditions of the water quality.

[0022] A sensing module is used to sense the operating status parameters of the screen cleaning machine in real time when the screen cleaning machine is in operation; The operating status parameters of the screen cleaning machine sensed by the sensing module include: operating power, water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth; The sensing module stores the sensed operating status parameters of the screen cleaning machine, and during the storage phase, differentiates and stores the parameters based on the preset time threshold of the front-end monitoring module's operation application, so that the source time threshold of the screen cleaning machine's operating status parameters stored in each differentiated storage interval is equal to the preset time threshold of the front-end monitoring module's operation application; The evaluation module is used to receive the water quality monitoring results from the front-end monitoring module and the operating status parameters of the screen cleaning machine from the perception module, and combine the two to evaluate the current performance status of the screen cleaning machine; In the evaluation module, during the current performance status evaluation phase of the screen cleaning machine, the operating health of the screen cleaning machine is evaluated based on the operating status parameters of the screen cleaning machine. Define the parameter deviation value, taking operating power as an example: ; Where: ΔP is the operating power deviation value; (P min ,P max ) is the normal operating power range; The average operating power value of the operating status parameters of the screen cleaning machine perceived by the sensing module; Among them, the definition logic of the parameter deviation value of the water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth in the operating state parameters of the screen cleaning machine is the same as the definition logic of the operating power deviation value. The calculation results of the deviation value of the water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth are recorded as ΔH, ΔN, ΔT, and ΔD; The logic for evaluating the operational health of the screen cleaning machine is as follows: ; The larger the S is, the better the operation health of the screen cleaning machine is; conversely, the smaller the S is, the worse the operation health of the screen cleaning machine is. The evaluation logic of the current performance status of the grid cleaning machine in the evaluation module is: ; Where: is the current performance value of the screen cleaning machine; S is the operational health of the screen cleaning machine; C is the water quality performance value; in, The larger the value, the better the current performance of the screen cleaning machine is; conversely, the worse the current performance of the screen cleaning machine is. The above logical formula is used to evaluate the operational health of the screen cleaning machine, providing support for the operation of the early warning module of the system in this embodiment, ensuring that the system stably triggers early warnings to perform remote maintenance and management of the screen cleaning machine.

[0023] The early warning module is used to set a safety threshold for the performance status of the screen cleaning machine, receive the current performance status evaluation result of the screen cleaning machine from the evaluation module, compare the evaluation result with the judgment threshold, and trigger an early warning prompt when the evaluation result is less than the judgment threshold; The threshold for determining the performance status of the screen cleaning machine in the early warning module is customized by the system user. When the early warning module triggers an early warning prompt, the early warning module sends an early warning prompt message to the screen cleaning machine management backend. The content of the early warning prompt message is a text message preset by the system user in text format. The early warning module is provided with a visualization unit and a prediction unit at the lower level. The visualization unit is used to record the evaluation results received by the early warning module and generate a line graph representing the trend of the evaluation results based on the evaluation results. The prediction unit is used to traverse the line graph generated in the visualization unit and predict whether there are hidden dangers in the grille cleaning machine based on the line graph. Among them, when the prediction result of the prediction unit operation is yes, the control warning module will synchronously trigger the warning prompt. The warning prompt content triggered by the prediction unit is different from the warning prompt content triggered by the independent operation of the warning module, and the warning prompt content triggered by the prediction unit is customized by the system end user; The prediction unit updates the line graph in real time based on the evaluation results received by the early warning module. If the line graph contains the evaluation results applied when the early warning module autonomously triggers an early warning prompt, the line graph is reset and regenerated based on the subsequent evaluation results received. When the prediction unit traverses the line graph to predict whether the grille cleaning machine has hidden dangers, it uses the line corresponding to the latest three evaluation results in the line graph to make predictions. If the line shows a continuous decline, the prediction result is yes, otherwise, the prediction result is no; The message module is used to record the trigger time of the historical warning prompt of the warning module and generate the screen cleaning machine operation message based on the recorded trigger time; The operation message of the screen cleaning machine generated by the message module also includes the performance status evaluation result of the screen cleaning machine corresponding to the early warning prompt triggering time; Among them, the operation message of the screen cleaning machine generated by the message module is fed back to the screen cleaning machine management background in real time; The front-end monitoring module is interactively connected with the perception module and the evaluation module through a wireless network. The evaluation module is interactively connected with the early warning module through a wireless network. The early warning module is interactively connected with the visualization unit and the prediction unit through a wireless network. The early warning module is interactively connected with the message module through a wireless network.

[0024] In this embodiment, the front-end monitoring module monitors the water quality of the screen cleaning machine. The perception module simultaneously operates while the screen cleaning machine is in operation to perceive the screen cleaning machine's operating status parameters in real time. The evaluation module operates post-operatively to receive the water quality monitoring results from the front-end monitoring module and the screen cleaning machine's operating status parameters from the perception module, and combines the two to evaluate the screen cleaning machine's current performance status. The early warning module further sets a safety threshold for determining the screen cleaning machine's performance status, receives the evaluation result of the screen cleaning machine's current performance status from the evaluation module, compares the evaluation result with the determination threshold, and triggers an early warning when the evaluation result is less than the determination threshold. The visualization unit simultaneously records the evaluation result received by the early warning module and generates a line graph representing the numerical trend of the evaluation result based on the evaluation result. The prediction unit traverses the line graph generated by the visualization unit in real time and predicts whether the screen cleaning machine has hidden hazards based on the line graph. Finally, the message module records the triggering time of the historical early warning prompts of the early warning module and generates a screen cleaning machine operation message based on the recorded triggering time. This achieves remote management and intelligent operation of the screen cleaning machine, saving the application cost of the screen cleaning machine in water conservancy and hydropower projects.

[0025] In summary, in the above embodiment, during the operation of the system, the water quality monitoring of the screen cleaning machine is introduced as a parameter for evaluating the operating status of the screen cleaning machine. The system further assists the system in performing an operational safety assessment of the screen cleaning machine in combination with the operating status parameters of the screen cleaning machine itself. At the same time, a visual image representing the change in the operating status of the screen cleaning machine is generated based on the assessment results, and different early warning logics are configured to issue an operational safety warning for the screen cleaning machine, thereby providing a guarantee for the long-term and stable operation of the screen cleaning machine.

[0026] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things is characterized by: include: Front-end monitoring module, used to monitor the quality of water introduced into the screen cleaning machine; A sensing module is used to sense the operating status parameters of the screen cleaning machine in real time when the screen cleaning machine is in operation; The evaluation module is used to receive the water quality monitoring results from the front-end monitoring module and the operating status parameters of the screen cleaning machine from the perception module, and combine the two to evaluate the current performance status of the screen cleaning machine; The early warning module is used to set a safety threshold for the performance status of the screen cleaning machine, receive the current performance status evaluation result of the screen cleaning machine from the evaluation module, compare the evaluation result with the judgment threshold, and trigger an early warning prompt when the evaluation result is less than the judgment threshold; The message module is used to record the trigger time of the historical warning prompt of the warning module and generate the screen cleaning machine operation message based on the recorded trigger time.

2. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 1 is characterized in that: The front-end monitoring module is integrated with a camera, and the front-end monitoring module collects water images introduced into the screen cleaning machine and monitors water quality based on the water images; The front-end monitoring module performs a water quality monitoring based on a preset time threshold, and when collecting water body images within the preset time threshold, the water body image collection frequency is adaptively controlled based on the flow rate of the water body introduced into the screen cleaning machine, so that the faster the water flow rate, the higher the water body image collection frequency, and the slower the water flow rate, the lower the water body image collection frequency; Among them, the front-end monitoring module and the perception module run synchronously in the system.

3. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 2 is characterized in that: The monitoring logic of the water quality of the screen cleaning machine introduced into the front-end monitoring module is expressed as follows: ； Where: C is the water quality performance value; n is the total amount of water body images; α and β are weight coefficients; M and N are the width and height of the water body image; F i (x, y) is the pixel value at coordinate (x, y) of the i-th water body image after grayscale processing and Gaussian filtering; is the average gray value of the water body image; S i is the image area of ​​the impurity region segmented by the image segmentation algorithm for the i-th water body image; A is the area of ​​the water body image; Among them, the weight coefficients α and β are both positive numbers, and the sum of their addition is 1. The values ​​of the two are customized by the system user. The larger C is, the worse the water quality is, and vice versa.

4. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 1 is characterized in that: The operating status parameters of the screen cleaning machine sensed by the sensing module include: operating power, water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth; Among them, the perception module stores the perceived operating status parameters of the screen cleaning machine, and in the storage stage, differentiates and stores them based on the preset time threshold of the front-end monitoring module operation application, so that the source time threshold of the screen cleaning machine operating status parameters stored in each differentiated storage interval is equal to the preset time threshold of the front-end monitoring module operation application.

5. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 1 is characterized in that: In the evaluation module, during the evaluation phase of the current performance status of the screen cleaning machine, the health of the screen cleaning machine's operating status is evaluated based on the screen cleaning machine's operating status parameters; Define the parameter deviation value, taking operating power as an example: ； Where: ΔP is the operating power deviation value; (P min ,P max ) is the normal operating power range; The average operating power value of the operating status parameters of the screen cleaning machine perceived by the sensing module; Among them, the parameter deviation value definition logic of the water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth in the screen cleaning machine operating status parameters is the same as the operating power deviation value definition logic. The calculation results of the deviation values ​​of the water level difference before and after the screen, noise level, driving torque, and rake bucket insertion depth are recorded as ΔH, ΔN, ΔT, and ΔD.

6. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 5 is characterized in that: The logic for evaluating the operational health of the screen cleaning machine is as follows: ； The larger the S is, the better the operation health of the screen cleaning machine is; conversely, the smaller the S is, the worse the operation health of the screen cleaning machine is. The evaluation logic of the current performance status of the grid cleaning machine in the evaluation module is: ； Where: is the current performance value of the screen cleaning machine; S is the operational health of the screen cleaning machine; C is the water quality performance value; in, The larger the value, the better the current performance of the screen cleaning machine is; conversely, the smaller the value, the worse the current performance of the screen cleaning machine is.

7. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 1 is characterized in that: The safety judgment threshold of the performance status of the grille cleaning machine in the early warning module is customized by the system end user. When the early warning module triggers the early warning prompt, the early warning module sends an early warning prompt message to the grille cleaning machine management backend. The content of the early warning prompt message is a text message preset by the system end user in a text format; The early warning module is provided with a visualization unit and a prediction unit at a lower level. The visualization unit is used to record the evaluation results received by the early warning module and generate a line graph representing the trend of the evaluation results based on the evaluation results. The prediction unit is used to traverse the line graph generated in the visualization unit and predict whether there are hidden dangers in the grille cleaning machine based on the line graph. Among them, when the prediction result of the prediction unit operation is yes, the control warning module synchronously triggers the warning prompt. The warning prompt content triggered by the prediction unit is different from the warning prompt content triggered by the autonomous operation of the warning module, and the warning prompt content triggered by the prediction unit is customized by the system user.

8. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 7 is characterized in that: The prediction unit updates the line graph in real time based on the evaluation results received by the early warning module, and when the line graph contains the evaluation results applied when the early warning module autonomously triggers the early warning prompt, the line graph is reset and regenerated based on the subsequently received evaluation results; When the prediction unit traverses the line graph to predict whether there are hidden dangers in the grille cleaning machine, it predicts based on the lines corresponding to the three latest evaluation results in the line graph. If the line is continuously decreasing, the prediction result is yes, otherwise, the prediction result is no.

9. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 1 is characterized in that: The content of the screen cleaning machine operation message generated by the message module also includes the screen cleaning machine performance status evaluation result corresponding to the early warning prompt triggering time; Among them, the screen cleaning machine operation message generated by the message module is fed back to the screen cleaning machine management background in real time.

10. The remote operation and maintenance management system for water conservancy and hydropower equipment based on the Internet of Things according to claim 1 is characterized in that: The front-end monitoring module is interactively connected with the perception module and the evaluation module through a wireless network, the evaluation module is interactively connected with the early warning module through a wireless network, the early warning module is interactively connected with the visualization unit and the prediction unit through a wireless network, and the early warning module is interactively connected with the message module through a wireless network.

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