Hydropower station monitoring system signal optimization method, system, equipment and medium

Abstract

The invention discloses a hydropower station monitoring system signal optimization method and system, equipment and a medium, and the method comprises the steps: obtaining a state signal of hydropower station equipment, and dividing the state signal into a plurality of standard operation stages when a preset operation type is detected to be started; pre-constructing a normal signal set template according to the operation type, and defining the types and sequences of signals which should appear and the maximum allowable time deviation between adjacent signals according to stages; the signals collected in real time are dynamically compared with the template according to stages, and if signal missing, time sequence out-of-tolerance or illegal signals undefined by the template exist, it is judged that the signals are abnormal; and triggering an abnormal response mechanism, automatically popping up an alarm window, displaying a specific operation stage of abnormal occurrence and an actual value and an expected value of a deviation signal, and synchronously calling an associated equipment monitoring picture to realize accurate positioning and quick response.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hydropower station monitoring, and in particular to a hydropower station monitoring system signal optimization method, system, device and medium. BACKGROUND

[0002] In a traditional hydropower station, whenever a unit is started or stopped or a plant power switching is performed, a large number of device status signals will be generated in real time, such as whether the circuit breaker is open or closed, whether the oil pump in the oil pressure device is started or stopped, the feedback value of the guide vane opening degree, whether the state of the relay protection device changes, and the like. These signals are continuously uploaded to the monitoring platform at a high frequency and a dense rhythm, forming a large time sequence data stream during the operation process. However, the existing monitoring technology also has many problems. First, the information redundancy is particularly serious - all the signals generated during normal operation are displayed on the monitoring interface, and as a result, the truly key abnormal alarms or fault signs are submerged, and the operator often needs to spend a lot of time manually screening and picking to find useful information. Second, the abnormal detection is always slow - the system itself lacks automated time sequence logic verification capability, mainly relying on the operator's experience to determine whether the signal is problematic, and once there is signal reporting delay, communication jitter, or multiple device signals interfering with each other, it is easy to misjudge or miss. Third, the human-computer interaction efficiency is not high - the monitoring interface cannot dynamically focus on the possible problem areas according to the current operation stage and device state, and the operation and maintenance personnel need to switch between several screens to locate the root cause when an abnormality occurs, so the response time is naturally prolonged. These problems not only increase the workload of the operation personnel, but also reduce the perception and response capability of the hydropower station to sudden faults. SUMMARY

[0003] In view of the above existing problems, the present application is proposed.

[0004] Therefore, the present application provides a hydropower station monitoring system signal optimization method, system, device and medium to solve the problem that the existing hydropower station monitoring system lacks intelligent filtering and abnormal identification capability for massive time sequence signals during the operation process, resulting in key alarms being submerged by redundant information, abnormal detection relying on manual work and being prone to misjudgment, human-computer interaction being rigid and requiring frequent switching between screens, and overall response lagging and being inefficient.

[0005] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a hydropower station monitoring system signal optimization method, comprising: Acquire state signals of a hydropower station device, and when a preset operation type is detected to start, divide an operation process into multiple standard operation stages according to the preset operation type; A corresponding normal signal set template is constructed in advance for the preset operation type, the template is organized according to the standard operation stages, and contains signal types that should appear in each stage, an order of appearance of signals, and a maximum time deviation allowed between adjacent signals; The collected device state signals are dynamically compared with the normal signal set template stage by stage according to the divided standard operation stages, and if any of the following situations exists, it is determined that an abnormality occurs: a signal is missing, a signal timing exceeds an allowed deviation, and an illegal signal that is not defined in the template; When the abnormality is detected, an abnormal dynamic response mechanism is triggered, an alarm window is automatically popped up, the alarm window displays a specific operation stage where the abnormality occurs and signal details that deviate, and a device monitoring screen associated with the abnormality is synchronously called.

[0006] As a preferred scheme of the hydropower station monitoring system signal optimization method, the preset operation type includes unit startup operation, unit shutdown operation, and plant power switching operation; When the preset operation type is unit startup operation, the standard operation stages include auxiliary device startup stage, speed regulator startup stage, excitation stage, and grid connection stage; In the case where no abnormality is detected, the monitoring interface displays aggregated state prompt information, and provides a clickable detailed signal link associated with signal data of a standard operation stage divided for the current operation.

[0007] As a preferred scheme of the hydropower station monitoring system signal optimization method, the normal signal set template includes signal types that should appear in each stage and a maximum time deviation allowed between adjacent signals; The signal types include circuit breaker action signal, oil pump start / stop signal, guide vane opening feedback signal, and machine terminal voltage signal; The maximum time deviation is a preset threshold value set according to a corresponding operation type and device characteristics.

[0008] As a preferred scheme of the hydropower station monitoring system signal optimization method, the collected device state signals are dynamically compared with the normal signal set template stage by stage according to the divided standard operation stages, including: In the current operation stage, it is determined whether a must-appear signal defined in the normal signal set template appears in the collected device state signals; For a reproducible signal that has already appeared, obtain the timestamp corresponding to the reproducible signal and verify whether the timestamp satisfies the timing constraint rules defined in the normal signal set template; The signal types in the collected device status signals are compared with the signal types defined in the normal signal set template to identify whether there are any signal types not included in the template.

[0009] The beneficial effect of this preferred technical solution is that by performing multi-dimensional dynamic comparisons of the existence, timing compliance, and legality of the signal type of the inevitable signal in stages, it achieves accurate and real-time identification of abnormal behavior during the operation of the hydropower station, effectively avoiding missed reports and misjudgments.

[0010] As a preferred embodiment of the signal optimization method for the hydropower station monitoring system described in this invention, the signal details of the deviation displayed in the alarm window include the actual value of the current signal and the expected value of the corresponding signal in the normal signal set template; The specific operational stage of the abnormality displayed in the alarm window is a stage identifier determined based on the deviation signal details. The stage identifier includes abnormal unit excitation, abnormal backup power supply switching, and abnormal unit speed. The preset handling suggestions displayed in the alarm window are preset text information corresponding to the stage identifier.

[0011] As a preferred embodiment of the signal optimization method for the hydropower station monitoring system described in this invention, the equipment monitoring screen associated with the anomaly includes the hydraulic control system screen, the excitation system monitoring screen, and the circuit breaker energy storage status screen. The retrieval of the device monitoring screen is automatically determined based on the signal type involved in the anomaly and the preset device-signal mapping relationship.

[0012] As a preferred embodiment of the signal optimization method for the hydropower station monitoring system described in this invention, the abnormal dynamic response mechanism includes: While the alarm window pops up, a clickable link to the detailed signal is generated; In response to a click operation on the detailed signal link, a time series table of all signals in the current operation phase is expanded, the time series table containing the timestamp and parameter values ​​of each signal; During normal operation, the detailed signal links are provided as an auxiliary interactive control for aggregated status information.

[0013] The beneficial effects of this preferred technical solution are that by providing interactive and detailed signal links in both abnormal and normal operating states, it enables on-demand drill-down and context-aware display of monitoring information, reducing interface interference while ensuring full transparency and control of the operation process by maintenance personnel.

[0014] Secondly, the present invention provides a signal optimization system for a hydropower station monitoring system, comprising: The operation phase division module is used to acquire the status signals of the hydropower station equipment and, when a preset operation type is detected to be started, divide the operation process into multiple standard operation phases according to the preset operation type. The normal signal template construction module is used to pre-construct a corresponding normal signal set template for the preset operation type. The template is organized according to the standard operation stage and includes the signal type that should appear in each stage, the order in which the signals appear, and the maximum allowable time deviation between adjacent signals. The multi-dimensional signal anomaly detection module is used to dynamically compare the collected device status signals with the normal signal set template stage by stage according to the divided standard operation stages. If any of the following situations exist, such as signal missing, signal timing exceeding the allowable deviation, or illegal signal not defined in the template, it is determined that an anomaly has occurred. The intelligent alarm and linkage response module is used to trigger the abnormal dynamic response mechanism when the abnormality is detected, automatically pop up an alarm window, display the specific operation stage of the abnormality and the signal details of the deviation, and simultaneously retrieve the monitoring screen of the device associated with the abnormality.

[0015] Thirdly, the present invention provides an electronic device, comprising: Memory, used to store programs; A processor is configured to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the signal optimization method for the hydropower station monitoring system.

[0016] Fourthly, the present invention provides a computer-readable storage medium, comprising: when the program is executed by a processor, the steps of implementing the signal optimization method for the hydropower station monitoring system.

[0017] The beneficial effects of this invention are as follows: This invention achieves structured modeling and standardized expression of the operation process of hydropower station equipment by dividing standard operation stages based on preset operation types and constructing a normal signal set template that includes signal type, timing sequence, and maximum time deviation; by dynamically comparing the real-time collected equipment status signals with the template according to stages, and synchronously verifying three types of abnormal situations such as signal loss, timing deviation, and illegal signals, this invention achieves high-precision and low-false-alarm automatic identification of operation anomalies. By popping up an alarm window containing the specific operation stage, deviation signal details, and related handling suggestions when an anomaly occurs, and linking to retrieve the monitoring screen of the corresponding device, while providing aggregated status and expandable detailed signal links during normal operation, the technology enables contextual awareness and on-demand information presentation in human-computer interaction, significantly improving the transparency and response efficiency of maintenance personnel for complex operation processes. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a basic flowchart illustrating a signal optimization method for a hydropower station monitoring system, provided as an embodiment of the present invention. Detailed Implementation

[0019] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0020] Example 1, referring to Figure 1 As an embodiment of the present invention, a signal optimization method for a hydropower station monitoring system is provided, comprising: S100: Acquire the status signals of the hydropower station equipment, and when a preset operation type is detected to be started, divide the operation process into multiple standard operation stages according to the preset operation type; S200: Pre-build a normal signal set template for the preset operation type. The template is organized according to the standard operation stage and includes the signal type that should appear in each stage, the order in which the signals appear, and the maximum allowable time deviation between adjacent signals. S300: The collected device status signals are dynamically compared with the normal signal set template stage by stage according to the divided standard operation stages. If any of the following situations exist, such as missing signals, signal timing exceeding the allowable deviation, or illegal signals not defined in the template, it is determined that an abnormality has occurred. S400: When an anomaly is detected, the dynamic anomaly response mechanism is triggered, and an alarm window automatically pops up. The alarm window displays the specific operational stage of the anomaly and the signal details of the deviation, and simultaneously retrieves the monitoring screen of the device associated with the anomaly.

[0021] It should be noted that existing hydropower station monitoring systems face a series of challenges during operation, including a lack of structured modeling of the operation process, with a large number of raw state signals presented in a discrete and disordered manner, making it difficult for maintenance personnel to accurately grasp the progress of operations; anomaly detection mainly relies on threshold exceeding limits or simple logical judgments, which cannot identify complex process anomalies such as signal loss, timing disorder, or illegal signals, resulting in high false alarm and missed alarm rates; alarm information usually only indicates equipment failure without being associated with specific operation stages and signal deviation details, lacking diagnostic context; in addition, the interface information is overloaded during normal operation, and there is a lack of intelligent linkage with monitoring screens and handling suggestions when anomalies occur, resulting in slow fault location and low response efficiency; overall, existing systems are unable to achieve refined and intelligent monitoring and guidance of the entire process of key operations such as start-up, shutdown, and switching.

[0022] Therefore, in response to the aforementioned problems in existing hydropower station monitoring systems, such as the lack of intelligent filtering and anomaly identification capabilities for massive time-series signals during operation, resulting in critical alarms being overwhelmed by redundant information, anomaly detection relying on manual intervention and prone to misjudgment, rigid human-computer interaction requiring frequent screen switching, and overall sluggish response and low efficiency, the S100-S400 steps are implemented. By constructing a normal signal set template based on the operation stage and performing multi-dimensional dynamic comparison, combined with a context-aware intelligent alarm and interaction mechanism, accurate anomaly identification, transparent status presentation, and efficient operation and maintenance response for critical operation processes of hydropower stations are achieved.

[0023] Example 2, this is an embodiment of the present invention, which provides a signal optimization method for a hydropower station monitoring system based on the previous embodiment, including: In this embodiment of the application, the preset operation types in step S100 include unit start-up operation, unit shutdown operation, and plant power switching operation. The system collects equipment status signals in real time during start-up, shutdown, and switching operations, and extracts the signal type, timestamp, and associated equipment information for each signal. When the preset operation type is unit start-up operation, the standard operation stages include auxiliary equipment start-up stage, governor start-up stage, excitation stage and grid connection stage. If no anomalies are detected, the monitoring interface displays aggregated status prompts and provides clickable links to detailed signals, which are associated with signal data from the standard operation phase defined by the current operation.

[0024] In this embodiment of the application, the automatic identification method of operation type in step S100 is triggered by detecting preset operation start events (such as power-on command, switching command issuance), and loading the corresponding operation process template accordingly, thereby realizing the automatic identification of operation types such as unit power-on, power-off or plant power switching.

[0025] In an optional implementation, the automatic identification method of operation type in step S100 can also be that the system collects the device status signal stream in real time, and automatically identifies the signal pattern that matches the known operation characteristics (such as "auxiliary equipment start-up → speed increase → voltage establishment") through sequence pattern mining or clustering algorithms. It does not rely on external operation commands. Once a match is successful, the current operation type is determined and the corresponding normal signal set template is loaded for subsequent comparison.

[0026] In an optional implementation, the automatic identification method of the operation type in step S100 can also allow the operation and maintenance personnel to manually select a preset operation type (such as "unit start-up") on the monitoring interface before the operation begins. The system loads the corresponding normal signal set template accordingly and verifies whether the actual signal flow is consistent with the selected operation type during the subsequent signal comparison process. If there is a serious deviation, it will prompt that the operation type is incorrectly selected or automatically correct it.

[0027] In this embodiment of the application, the normal signal set template in step S200 includes the signal types that should appear in each stage and the maximum allowable time deviation between adjacent signals; Signal types include circuit breaker action signals, oil pump start / stop signals, guide vane opening feedback signals, and terminal voltage signals; The maximum time deviation is a preset threshold set according to the corresponding operation type and equipment characteristics.

[0028] In this embodiment of the application, the normal signal set template in step S200 is constructed by experts pre-defining the signal types, signal sequence, and maximum allowable time deviation between adjacent signals that should appear in each standard operation stage for each preset operation type (such as unit start-up, shutdown, and switching), and storing these rules in a structured manner in a dynamic template library.

[0029] In an optional implementation, the normal signal set template in step S200 can also be constructed by extracting a large number of successfully executed operation records from the historical operation library, statistically analyzing the frequency and timing distribution of signals at each stage, automatically setting the must-occur signal (e.g., occurrence rate ≥ 98%) and the maximum time deviation (e.g., mean plus 3 times the standard deviation), and generating a structured template for real-time comparison.

[0030] In an optional implementation, the construction of the normal signal set template in step S200 can also be based on a high-fidelity digital twin model of the hydropower station equipment. In the virtual environment, standard operating procedures (such as power-on and switching) are simulated, the ideal signal sequence and its timing relationship of the simulation output are collected, and the normal signal set template is imported into the system for real-time comparison.

[0031] In the embodiments of this application, for example, during the unit start-up operation, the maximum allowable time deviation between the "auxiliary equipment start-up successful" signal and the "unit speed ≥ 95%" signal is 90 seconds, and the maximum allowable time deviation between the "unit speed ≥ 95%" signal and the "unit grid connection successful" signal is 10 seconds; during the plant power switching operation, after the circuit breaker closing command is issued, the maximum allowable response time of the closing success signal is 5 seconds.

[0032] In this embodiment of the application, step S300 involves dynamically comparing the collected device status signals with the normal signal set template stage by stage according to the divided standard operation stages, including: During the current operational phase, determine whether the mandatory signals defined in the normal signal set template appear in the collected device status signals; For a reproducible signal that has already appeared, obtain the timestamp corresponding to the reproducible signal and verify whether the timestamp meets the timing constraint rules defined in the normal signal set template; The signal types in the collected device status signals are compared with the signal types defined in the normal signal set template to identify whether there are any signal types not included in the template.

[0033] In this embodiment of the application, the comparison and judgment logic of abnormal signals in step S300 is implemented by performing triple verification in stages: first, it is determined whether the must-occur signal defined by the template is missing; second, it is verified whether the timestamp of the already appearing signal meets the preset timing constraints; and finally, it is screened to see if there is an illegal signal type not defined by the template. If any condition is met, it is determined to be abnormal.

[0034] In an optional implementation, the abnormal signal comparison and judgment logic in step S300 can also model the real-time signal sequence of the current operation stage as a time sequence diagram, input it into the pre-trained GNN model for overall evaluation, output the abnormal probability and key deviation nodes, and if the abnormal probability exceeds the threshold, it is determined that an abnormality has occurred, and the problem signal is located for alarm and response.

[0035] In an optional implementation, the abnormal signal comparison and judgment logic in step S300 can also construct time series by comparing the actual signal sequence collected in the current operation stage with the standard sequence in the normal signal set template, calculate the minimum cumulative distance between the two using the DTW algorithm, and if the distance exceeds the preset tolerance threshold, it is judged as abnormal, and the specific signal point that deviates is located according to the DTW alignment path.

[0036] In this embodiment, signal missing includes the absence of the "speed governor lockout" signal during the speed governor start-up phase; timing deviation includes the "unit speed feedback" failing to reach the threshold even after exceeding the template allowable time; and illegal signals include the appearance of a circuit breaker tripping command related to switching operations during the start-up phase. Further, specific situations of timing deviation include: during the excitation phase, the generator terminal voltage failing to reach 95% of the rated value within 15 seconds after excitation starts, or the backup power circuit breaker closing signal failing to return within 5 seconds after the operation command is issued.

[0037] In this embodiment of the application, the signal details of the deviation displayed in the alarm window in step S400 include the actual value of the current signal and the expected value of the corresponding signal in the normal signal set template, and synchronously display the real-time operating parameters of the equipment associated with the abnormality; for example, when an excitation abnormality is detected, the alarm window displays "terminal voltage: 60%", while the expected value for this stage in the template is "≥95%".

[0038] The alarm window displays the specific operational stage of the anomaly as a stage identifier determined based on the deviation signal details. The stage identifiers include unit excitation anomaly, backup power supply switching anomaly, and unit speed anomaly. The alarm window displays preset handling suggestions, which are preset text information corresponding to the stage identifier.

[0039] In this embodiment of the application, the equipment monitoring screen associated with the anomaly in step S400 includes the hydraulic control system screen, the excitation system monitoring screen, and the circuit breaker energy storage status screen. The retrieval of equipment monitoring screens is automatically determined based on the signal type involved in the anomaly and the preset device-signal mapping relationship.

[0040] For power switching anomalies in the plant, the system also simultaneously retrieves the corresponding time period's operation event recordings for playback and analysis.

[0041] In this embodiment of the application, the monitoring screen retrieval method when an anomaly occurs in step S400 automatically matches and retrieves the corresponding device monitoring screen (such as the excitation system monitoring screen) according to the signal type involved in the anomaly (such as excitation voltage anomaly) through a preset device-signal mapping relationship.

[0042] In an optional implementation, the monitoring screen retrieval method when an anomaly occurs in step S400 can also automatically retrieve the monitoring screens of all relevant equipment in the affected area based on the topological connection relationship of the primary / secondary equipment of the hydropower station and the influence range of the signal source propagating upstream and downstream after the anomaly signal is detected, so as to realize multi-screen linkage display.

[0043] In an optional implementation, the monitoring screen retrieval method when an anomaly occurs in step S400 can also construct an operation and maintenance knowledge graph that includes the relationship between signals, devices, fault modes and monitoring screens. When an anomaly is triggered, the monitoring screen most relevant to the current anomaly is calculated through graph reasoning, and one or more screens are intelligently recommended for automatic retrieval or manual confirmation.

[0044] In this embodiment of the application, the abnormal dynamic response mechanism in step S400 includes: While the alarm window pops up, a clickable link to the detailed signal is generated; In response to a click on a detailed signal link, expand the time series table of all signals in the current operation phase. The time series table contains the timestamp and parameter values ​​of each signal. During normal operation, detailed signal links are provided as supplementary interactive controls for aggregated state information.

[0045] In this embodiment, the overall technical process includes: after the operation begins, the system performs signal acquisition and preprocessing, selects the corresponding normal signal set template according to the current operation type; dynamically compares the real-time signal stream with the template through a time-series analysis engine to determine whether it conforms to the expected process; if the signal sequence conforms to the template, it displays aggregated status information and provides clickable detailed signal links for further viewing until the operation is completed; if it does not conform to the template, it triggers an abnormal alarm, displays abnormal details (including specific operation stage, deviation signals and parameters) in a pop-up window, automatically associates the real-time monitoring screen or video of the faulty device, pushes preset handling suggestions, and records an abnormal log; at the same time, the system feeds back the abnormal data to the template self-learning module for subsequent dynamic optimization and updates of the template, realizing closed-loop intelligent monitoring.

[0046] In this embodiment, the hydropower station monitoring system adopts a modular architecture design, mainly including the following components: a PLC / relay protection device as a signal source, which collects the status signals of the hydropower station equipment in real time and transmits them to the system; the system has a data layer, including a real-time signal library for storing currently collected signal data, a historical operation library for saving signal records and abnormal cases in past operations, and a dynamic template library for storing normal signal set templates built for different preset operation types (such as unit start-up, shutdown, and switching), and supporting template version management and updates; a time sequence analysis engine receives the signal stream from the real-time signal library, performs a stage-by-stage comparison based on the matching operation type template in the dynamic template library, and determines whether the signal conforms to the expected sequence and whether the time deviation is within the allowable range; the anomaly detection module analyzes the time sequence... The analysis engine verifies the results, identifies anomalies such as missing signals, timing errors, or illegal signals, and generates anomaly events. The anomaly details management module organizes and displays anomaly information, including the specific operational stage of the anomaly, the actual and expected values ​​of the deviation signal, related device parameters, and preset handling suggestions. The aggregated status display module outputs the aggregated status prompt of the current operation (such as "Powering on") to the monitoring interface when no anomaly occurs, and provides clickable detailed signal links for drill-down viewing. The multi-system linkage interface acts as an intermediate layer, enabling the interaction of anomaly information with external systems. Specifically, it pushes fault work orders to the work order management system, sends key signal data of the anomaly period to the parameter trend analysis system, and retrieves real-time images or operation recordings from related devices to the video surveillance system, achieving cross-system collaborative response. The dynamic template library and anomaly case library are connected via a database, supporting template loading, updating, and self-learning optimization based on historical cases.

[0047] Example 3 is an embodiment of the present invention. This embodiment differs from the first embodiment in that it provides a signal optimization system for a hydropower station monitoring system.

[0048] It should be noted that the technical solution of the hydropower station monitoring system signal optimization system is based on the same concept as the technical solution of the hydropower station monitoring system signal optimization method described above. For details not described in detail in the technical solution of the hydropower station monitoring system signal optimization system in this embodiment, please refer to the description of the technical solution of the hydropower station monitoring system signal optimization method described above.

[0049] This embodiment describes a signal optimization system for a hydropower station monitoring system, comprising: The operation phase division module is used to acquire the status signals of hydropower station equipment and, when a preset operation type is detected to be started, divide the operation process into multiple standard operation phases according to the preset operation type. The normal signal template construction module is used to pre-build the corresponding normal signal set template for the preset operation type. The template is organized according to the standard operation stage and includes the signal type that should appear in each stage, the order in which the signals appear, and the maximum allowable time deviation between adjacent signals. The multi-dimensional signal anomaly detection module is used to dynamically compare the collected device status signals with the normal signal set template stage by stage according to the divided standard operation stages. If any of the following situations exist, such as missing signals, signal timing exceeding the allowable deviation, or illegal signals not defined in the template, it is determined that an anomaly has occurred. The intelligent alarm and linkage response module is used to trigger the dynamic response mechanism when an anomaly is detected. The alarm window will automatically pop up, displaying the specific operational stage of the anomaly and the signal details of the deviation, and simultaneously retrieve the monitoring screen of the device associated with the anomaly.

[0050] This embodiment also provides an electronic device applicable to a signal optimization method for a hydropower station monitoring system, including: The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement a signal optimization method for a hydropower station monitoring system as described in the above embodiments.

[0051] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a signal optimization method for a hydropower station monitoring system as proposed in the above embodiments.

[0052] The storage medium proposed in this embodiment belongs to the same inventive concept as the signal optimization method for a hydropower station monitoring system proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0053] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0054] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for signal optimization of a hydropower plant monitoring system, characterized by, The method comprises: acquiring state signals of a hydropower station device, and dividing an operation process into a plurality of standard operation stages according to a preset operation type when a preset operation type start is detected; previously constructing a corresponding normal signal set template for the preset operation type, the template being organized according to the standard operation stages, containing signal types that should appear in each stage, an order of appearance of signals, and a maximum time deviation allowed between adjacent signals; dynamically comparing the collected device state signals with the normal signal set template stage by stage according to the divided standard operation stages, and determining that an abnormality occurs if any of the following situations exists: a signal is missing, a signal timing exceeds the allowed deviation, or an illegal signal not defined in the template; when the abnormality is detected, triggering an abnormal dynamic response mechanism, automatically popping up an alarm window, the alarm window displaying a specific operation stage where the abnormality occurs and signal details deviating therefrom, and synchronously calling a device monitoring screen associated with the abnormality.

2. The method of signal optimization for a hydroelectric power plant monitoring system of claim 1, wherein: The preset operation type includes unit startup operation, unit shutdown operation, and plant power switching operation; when the preset operation type is unit startup operation, the standard operation stages include an auxiliary device startup stage, a speed regulator startup stage, a field excitation stage, and a grid connection stage; in the case where no abnormality is detected, the monitoring interface displays an aggregated state prompt information, and provides a clickable detailed signal link associated with signal data of the standard operation stage divided for the current operation.

3. The method for signal optimization of a hydroelectric plant monitoring system according to claim 1 or 2, characterized in that: The normal signal set template includes signal types that should appear in each stage and a maximum time deviation allowed between adjacent signals; The signal types include circuit breaker action signals, oil pump start / stop signals, guide vane opening feedback signals, and generator terminal voltage signals; The maximum time deviation is a preset threshold value set according to the corresponding operation type and device characteristics.

4. The method of signal optimization for a hydroelectric power plant monitoring system of claim 3, wherein: The dynamic comparison of the collected device state signals with the normal signal set template stage by stage according to the divided standard operation stages comprises: in the current operation stage, determining whether the mandatory signals defined in the normal signal set template appear in the collected device state signals; for the mandatory signals that have appeared, acquiring time stamps corresponding to the mandatory signals, and verifying whether the time stamps satisfy the timing constraint rules defined in the normal signal set template; comparing signal types in the collected device state signals with signal types defined in the normal signal set template to identify whether there is a signal type not contained in the template.

5. The method of signal optimization for a hydroelectric power plant monitoring system of claim 4, wherein: The signal details deviating therefrom displayed in the alarm window include actual values of the current signals and expected values of corresponding signals in the normal signal set template; The specific operation stage where the abnormality occurs displayed in the alarm window is a stage identifier determined based on the signal details deviating therefrom, the stage identifier including unit excitation abnormality, standby power supply switching abnormality, and unit speed abnormality; The preset disposal suggestion displayed in the alarm window is preset text information corresponding to the stage identifier.

6. The method of signal optimization for a hydroelectric power plant monitoring system of claim 5, wherein: The device monitoring screen associated with the abnormality includes a hydraulic control system screen, an excitation system monitoring screen, and a circuit breaker energy storage state screen. The device monitoring picture call based on the signal type involved in the exception and the preset device-signal mapping relationship is automatically determined.

7. The method of signal optimization for a hydroelectric power plant monitoring system of claim 6, wherein: The abnormal dynamic response mechanism comprises: At the same time of pop-up alarm window, generate clickable detailed signal link; In response to the click operation on the detailed signal link, expand the time sequence list of all signals in the current operation stage, and the time sequence list contains the timestamp and parameter value of each signal; In the operation process without exception, the detailed signal link is provided as an auxiliary interactive control of aggregated state information.

8. A hydroelectric power plant monitoring system signal optimization system applying the method according to any one of claims 1-7, characterized by, Comprise: An operation stage division module is configured to acquire state signals of the hydropower station device, and divide an operation process into multiple standard operation stages according to a preset operation type when the preset operation type is detected to be started; A normal signal template construction module is configured to pre-construct a corresponding normal signal set template for the preset operation type, the template is organized according to the standard operation stage, and contains signal types that should appear in each stage, the order of signal appearance, and the maximum time deviation allowed between adjacent signals; A multi-dimensional signal abnormality detection module is configured to compare the collected device state signals with the normal signal set template stage by stage according to the divided standard operation stage, and if any of the following situations exists, it is determined that an abnormality occurs: signal missing, signal timing exceeding the allowed deviation, and illegal signal not defined in the template; An intelligent alarm and linkage response module is configured to trigger an abnormal dynamic response mechanism when the abnormality is detected, automatically pop up an alarm window, and the alarm window displays the specific operation stage where the abnormality occurs and the deviated signal details, and synchronously calls a device monitoring picture associated with the abnormality.

9. An electronic device, comprising: Comprise: A memory is configured to store a program; A processor is configured to load the program to execute the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium storing a program, characterized in that, The program is executed by the processor to implement the steps of the method according to any one of claims 1-7. The program is executed by the processor to implement the steps of the method according to any one of claims 1-7.

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