Hydropower station safety monitoring method and system

Abstract

The invention provides a hydropower station safety monitoring method and system, and the method comprises the following steps: 1, collecting historical monitoring data and real-time monitoring data in the operation process of a hydropower station, and carrying out the preprocessing of the collected data; 2, constructing a safety coefficient evaluation model through historical monitoring data, and carrying out safety evaluation on the real-time monitoring data; 3, a hydropower station early warning model is constructed through a data safety assessment result, and the safety condition and damage of the hydropower station are assessed; and 4, establishing a short-term and long-term prediction model, and performing future data prediction and safety evaluation in combination with the safety coefficient evaluation model and the hydropower station early warning model. The monitoring parameters of the hydropower station can be classified and evaluated through the constructed safety coefficient evaluation model, comprehensive safety evaluation can be performed through the hydropower station early warning model in combination with different monitoring parameters of the hydropower station, and the operation safety of the hydropower station is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of hydropower station monitoring, and in particular to a hydropower station safety monitoring method and system. Background Art

[0002] With the growing global demand for clean energy, the safe and stable operation of hydropower stations, as important renewable energy generation facilities, is crucial for ensuring power supply and infrastructure security. However, hydropower stations operate in a complex environment and face a variety of potential safety risks, such as unit failures, gate anomalies, and water area changes. Traditional hydropower station safety monitoring methods rely primarily on manual inspections and single sensor monitoring. These methods suffer from low monitoring efficiency, incomplete data, and poor real-time performance, making it difficult to meet the needs of high-precision, real-time monitoring of modern large-scale hydropower stations. Existing hydropower station safety monitoring can only conduct local safety monitoring of hydropower stations, making it difficult to fully and accurately reflect the overall safety status of hydropower stations and prone to detection blind spots. Summary of the Invention

[0003] In view of this, an object of the present invention is to provide a hydropower station safety monitoring method and system to at least solve the above problems.

[0004] The technical solution adopted in the present invention is as follows: A first aspect of the present invention provides a hydropower station safety monitoring method, comprising the following steps: Step 1: Collect historical monitoring data and real-time monitoring data during the operation of the hydropower station and pre-process the collected data; Step 2: Build a safety factor assessment model based on historical monitoring data and conduct safety assessment on real-time monitoring data; Step 3: Build a hydropower station early warning model to assess the safety status and damage of the hydropower station; Step 4: Establish a short-term-long-term prediction model and combine it with the security assessment model to perform future data prediction and security assessment.

[0005] Furthermore, the historical monitoring data collected during the operation of the hydropower station in step 1 includes historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data; the real-time monitoring data includes dam deformation data, unit operation data, gate operation data and water area detection data.

[0006] Furthermore, the preprocessing in step 1 is specifically as follows: normalizing the data and processing the incomplete and abnormal data using interpolation method.

[0007] Furthermore, step 2 is specifically as follows: Feature extraction is performed on historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data respectively. The extracted features are used to construct safety factor assessment models, including dam deformation model, unit health model, gate safety model and water area detection model. The parameter safety factors and overall safety factors of dam, unit, gate and water area are output through real-time monitoring data.

[0008] Furthermore, step 3 is specifically as follows: constructing a hydropower station early warning model through parameter safety factors and overall safety factors of the dam, unit, gate and water area. The hydropower station early warning model includes an overall early warning model and a hierarchical early warning model.

[0009] Furthermore, the overall early warning model is specifically as follows: The weight coefficients of the dam, generator, gate, and water area are obtained through training with historical accident data of the hydropower station. The overall early warning model is established based on the overall safety factor and weight coefficient, and the overall safety factor of the hydropower station is output. Safety warning is carried out based on the set early warning safety factor. The formula of the overall early warning model is:

[0010] in, represents the overall safety factor, 、 、 、 Represent the overall safety factors of the dam, unit, gate and water area respectively, 、 、 、 Represent the weight coefficients of dam, unit, gate and water area respectively, Represents the dynamic adjustment factor.

[0011] Furthermore, after issuing an early warning, the overall early warning model updates the weight coefficient by comparing the early warning result with the actual result.

[0012] Furthermore, the hierarchical warning model is specifically as follows: based on the historical operation and maintenance management data of the hydropower station, the parameter safety factors of the dam, unit, gate and water area are associated with the damage type and parameters of the hydropower station, and a hierarchical warning decision tree is constructed. For each damage type of the hydropower station, the corresponding parameters are associated, and the damage type of the hydropower station and damage warning are judged by the parameter safety factor.

[0013] Furthermore, step 4 is specifically as follows: different time series models are constructed based on historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data, different VARIMA models are constructed using the time series models, and the VARIMA models are used to predict future monitoring data of the hydropower station. The future monitoring data is used to evaluate the future safe operation of the hydropower station through the safety factor assessment model and the hydropower station early warning model.

[0014] A second aspect of the present invention provides a hydropower station safety monitoring system for executing the hydropower station safety monitoring method according to any one of claims 1 to 9. The system includes a data acquisition module, a data evaluation module, an overall early warning module, a graded early warning module and a future early warning module. The data acquisition module is used to collect monitoring data during the operation of the hydropower station, including dam deformation data, unit operation data, gate operation data and water area monitoring data. The data evaluation module is used to evaluate the safety factor of the collected data. The overall early warning module is used to perform a safety assessment of the overall operation of the hydropower station. The graded early warning module is used to perform a safety assessment of the damage category of the hydropower station. The future early warning module is used to perform a safety assessment of the future operation of the hydropower station.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method and system for monitoring the safety of a hydropower station. The method collects monitoring parameters of the hydropower station, classifies the parameters, and establishes a model for evaluation. The method uses an overall early warning model of the hydropower station to perform an overall integrated evaluation of the monitoring parameters of the hydropower station, and can obtain the overall operating status of the hydropower station. The method uses a hierarchical early warning module of the hydropower station early warning model to associate the monitoring parameters of the hydropower station with the damage type of the hydropower station, and can monitor local damage to the hydropower station through changes in the monitoring parameters. The hydropower station early warning model can perform local and overall monitoring and early warning of the hydropower station, and can ensure the safety of the operation of the hydropower station. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 This is a flow chart of a hydropower station safety monitoring method provided by the present invention; Figure 2 This is a structural diagram of a hydropower station safety monitoring system provided by the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention is further elaborated in detail below in conjunction with the drawings and specific embodiments of the specification. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. In the following description, reference is made to "some embodiments", which describes a subset of all possible embodiments, but it should be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.

[0019] In the following description, numerous specific details are provided to provide a more thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced without one or more of these details. In other instances, certain technical features well known in the art are not described to avoid confusion with the present invention.

[0020] It should be understood that the present invention can be implemented in different forms and should not be interpreted as being limited to the embodiments proposed herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the present invention to those skilled in the art. And the purpose of the terms used herein is only to describe specific embodiments and is not intended to limit the present invention. When used herein, the singular forms "one", "an" and "said / the" are also intended to include plural forms, unless the context clearly indicates another way. It should also be understood that the terms "comprising" and / or "comprising" when used in this specification determine the presence of the features, integers, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, parts and / or groups. When used herein, the term "and / or" includes any and all combinations of the relevant listed items.

[0021] It should also be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical," "horizontal," "inner," "outer," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only implementation methods.

[0022] In order to fully understand the present invention, a detailed structure will be presented in the following description to illustrate the technical solution proposed by the present invention. The optional embodiments of the present invention are described in detail below. However, in addition to these detailed descriptions, the present invention may also have other embodiments. Reference Figure 1 An embodiment of the present invention provides a method for safety monitoring of a hydropower station, comprising the following steps: Step 1: Collect historical monitoring data and real-time monitoring data during the operation of the hydropower station and pre-process the collected data; The historical monitoring data collected during the operation of the hydropower station include historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data; the real-time monitoring data include dam deformation data, unit operation data, gate operation data and water area detection data; the preprocessing includes normalizing the data and using interpolation method to process incomplete and abnormal data.

[0023] Step 2: Build a safety factor assessment model based on historical monitoring data and conduct a safety assessment on real-time monitoring data; specifically: Feature extraction is performed on historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data respectively. The extracted features are used to construct safety factor assessment models, including dam deformation model, unit health model, gate safety model and water area detection model. The parameter safety factors and overall safety factors of dam, unit, gate and water area are output through real-time monitoring data.

[0024] Step 3: Build a hydropower station early warning model to assess the safety status and damage of the hydropower station; specifically: The hydropower station early warning model is constructed through the parameter safety factors and overall safety factors of the dam, unit, gate and water area. The hydropower station early warning model includes an overall early warning model and a hierarchical early warning model.

[0025] For example, the overall early warning model is used to evaluate and issue early warnings on the overall operating status of the hydropower station, and the graded early warning model is used to monitor local damage to the hydropower station.

[0026] The overall early warning model is specifically: The weight coefficients of the dam, generator, gate, and water area are obtained through training with historical accident data of the hydropower station. The overall early warning model is established based on the overall safety factor and weight coefficient, and the overall safety factor of the hydropower station is output. Safety warning is carried out based on the set early warning safety factor. The formula of the overall early warning model is:

[0027] in, represents the overall safety factor, 、 、 、 Represent the overall safety factors of the dam, unit, gate and water area respectively, 、 、 、 Represent the weight coefficients of dam, unit, gate and water area respectively, Represents the dynamic adjustment factor.

[0028] For example, by introducing The dynamic adjustment factor is used to dynamically correct the overall safety factor based on comprehensive factors such as real-time environmental changes and operating status, so as to improve the accuracy and reliability of the early warning model.

[0029] After issuing an early warning, the overall early warning model updates the weight coefficient by comparing the early warning results with the actual results.

[0030] The hierarchical warning model is specifically as follows: based on the historical operation and maintenance management data of the hydropower station, the parameter safety factors of the dam, unit, gate and water area are associated with the damage type and parameters of the hydropower station, and a hierarchical warning decision tree is constructed. For each damage type of the hydropower station, the corresponding parameters are associated, and the parameter safety factors are used to judge the damage type of the hydropower station and issue a damage warning.

[0031] For example, the hierarchical early warning model associates the monitoring parameters of the hydropower station with the damage type. For example, the gate closing speed is associated with the vibration and damage of the unit. The damage of the hydropower station can be judged by the changes in the monitoring parameters, and timely early warning and maintenance can be carried out.

[0032] Step 4: Build a short-term and long-term prediction model and combine it with the safety assessment model to predict future data and conduct safety assessments. Specifically, different time series models are constructed based on historical dam deformation data, historical unit operation data, historical gate operation data, and historical water area inspection data. Different VARIMA models are constructed using these time series models. The VARIMA models are used to predict future monitoring data of the hydropower station. This future monitoring data is then used in the safety factor assessment model and the hydropower station early warning model to assess the future safe operation of the hydropower station.

[0033] Another embodiment of the present invention provides a hydropower station safety monitoring system for executing the hydropower station safety monitoring method described in any one of claims 1-9, the system including a data acquisition module, a data evaluation module, an overall early warning module, a graded early warning module and a future early warning module, the data acquisition module being used to collect monitoring data during the operation of the hydropower station, including dam deformation data, unit operation data, gate operation data and water area monitoring data, the data evaluation module being used to evaluate the safety factor of the collected data, the overall early warning module being used to perform a safety assessment of the overall operation of the hydropower station, the graded early warning module being used to perform a safety assessment of the damage category of the hydropower station, and the future early warning module being used to perform a safety assessment of the future operation of the hydropower station.

[0034] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for safety monitoring of a hydropower station, characterized in that: The following steps are involved: Step 1: Collect historical monitoring data and real-time monitoring data during the operation of the hydropower station and pre-process the collected data; Step 2: Build a safety factor assessment model based on historical monitoring data and conduct safety assessment on real-time monitoring data; Step 3: Build a hydropower station early warning model based on the results of the data security assessment to evaluate the safety status and damage of the hydropower station; Step 4: Establish a short-term and long-term prediction model and combine it with the safety factor assessment model and hydropower station early warning model to perform future data prediction and safety assessment.

2. A hydropower station safety monitoring method according to claim 1, characterized in that: The historical monitoring data collected during the operation of the hydropower station in step 1 include historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data; the real-time monitoring data include dam deformation data, unit operation data, gate operation data and water area detection data.

3. A hydropower station safety monitoring method according to claim 2, characterized in that: The preprocessing in step 1 is as follows: normalizing the data and processing the incomplete and abnormal data using interpolation method.

4. A hydropower station safety monitoring method according to claim 3, characterized in that: Step 2 is as follows: Feature extraction is performed on historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data respectively. The extracted features are used to construct safety factor assessment models, including dam deformation model, unit health model, gate safety model and water area detection model. The parameter safety factors and overall safety factors of dam, unit, gate and water area are output through real-time monitoring data.

5. A hydropower station safety monitoring method according to claim 4, characterized in that: Step 3 is specifically as follows: constructing a hydropower station early warning model through the parameter safety factors and overall safety factors of the dam, unit, gate and water area. The hydropower station early warning model includes an overall early warning model and a hierarchical early warning model.

6. A hydropower station safety monitoring method according to claim 5, characterized in that: The overall early warning model is specifically: The weight coefficients of the dam, generator, gate, and water area are obtained through training based on historical accident data of the hydropower station. The overall early warning model is established based on the overall safety factor and weight coefficient, and the overall safety factor of the hydropower station is output. Safety early warning is carried out based on the set early warning safety factor. The overall early warning model formula is: in, represents the overall safety factor, 、 、 、 Represent the overall safety factors of the dam, unit, gate and water area respectively, 、 、 、 Represent the weight coefficients of dam, unit, gate and water area respectively, Represents the dynamic adjustment factor.

7. A hydropower station safety monitoring method according to claim 6, characterized in that: After issuing an early warning, the overall early warning model updates the weight coefficient by comparing the early warning results with the actual results.

8. A hydropower station safety monitoring method according to claim 7, characterized in that: The hierarchical warning model is specifically as follows: based on the historical operation and maintenance management data of the hydropower station, the parameter safety factors of the dam, unit, gate and water area are associated with the damage type and parameters of the hydropower station, and a hierarchical warning decision tree is constructed. For each damage type of the hydropower station, the corresponding parameters are associated, and the parameter safety factors are used to judge the damage type of the hydropower station and issue a damage warning.

9. A hydropower station safety monitoring method according to claim 8, characterized in that: Step 4 is as follows: different time series models are constructed based on historical dam deformation data, historical unit operation data, historical gate operation data and historical water area detection data; different VARIMA models are constructed using the time series models; the VARIMA models are used to predict future monitoring data of the hydropower station; and the future monitoring data are used to evaluate the future safe operation of the hydropower station through the safety factor assessment model and the hydropower station early warning model.

10. A hydropower station safety monitoring system, characterized in that: Used to execute the hydropower station safety monitoring method described in any one of claims 1 to 9, the system includes a data acquisition module, a data evaluation module, an overall early warning module, a graded early warning module and a future early warning module, the data acquisition module is used to collect monitoring data during the operation of the hydropower station, including dam deformation data, unit operation data, gate operation data and water area monitoring data, the data evaluation module is used to evaluate the safety factor of the collected data, the overall early warning module is used to perform a safety assessment on the overall operation of the hydropower station, the graded early warning module is used to perform a safety assessment on the damage category of the hydropower station, and the future early warning module is used to perform a safety assessment on the future operation of the hydropower station.

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