Method and system for intelligently monitoring and analyzing running state of cylinder valve

Abstract

The invention discloses an intelligent monitoring and analysis method and system for the running state of a cylinder valve. The method realizes automatic intelligent monitoring and analysis of the running state of the cylinder valve, reduces the workload of manual inspection, improves the operation and maintenance efficiency and the fault response speed, and supports an unattended mode of a hydropower station.

Description

Technical Field

[0001] This invention relates to the field of hydropower station cylinder valve system status monitoring technology, and in particular to a method and system for intelligent monitoring and analysis of cylinder valve operating status. Background Technology

[0002] Cylindrical valves, as a type of inlet valve for hydroelectric generator units, are increasingly widely used in large and mega-hydropower stations. They possess functions and advantages that ordinary butterfly valves or ball valves do not have, such as rapid and efficient opening and closing, and tight closure. During the normal operation of a hydropower station, a large amount of data generated during the operation of cylindrical valves is typically recorded. Currently, monitoring the operating status of cylindrical valves mainly relies on regular manual inspections. Maintenance personnel need to periodically query and filter the cylindrical valve operating data from the monitoring system to analyze the system's operating status, requiring professionals to spend a significant amount of time on data filtering and status assessment. Summary of the Invention

[0003] The main objective of this invention is to provide an intelligent monitoring and analysis method for the operating status of cylinder valves, which regularly monitors and analyzes the data during the operation of cylinder valves and generates reports to send to maintenance personnel, enabling maintenance personnel to regularly grasp the operating status of the cylinder valve system.

[0004] Another objective of this invention is to provide an intelligent monitoring and analysis device for the operating status of a cylinder valve.

[0005] The third objective of this invention is to provide a computer device.

[0006] The fourth objective of this invention is to provide a non-transitory computer-readable storage medium.

[0007] To achieve the above objectives, a first aspect of the present invention provides a method for intelligent monitoring and analysis of the operating status of a cylinder valve, comprising: S1, real-time collection of operating data during the operation of the cylinder valve through the Industrial Internet, the operating data including cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and time, and proportional servo valve setpoint and feedback value; S2, stores the collected operational data in a preset format to the database, and cleans up expired data according to a set cycle; S3 performs multi-dimensional intelligent analysis based on stored operating data, generating a structured analysis report that includes statistics on the number of cylinder valve actions, timeout determination, oil pump operating deviation, servo valve deviation, and opening curve comparison to obtain analysis results; S4 periodically sends normal status reports through a preset communication channel based on the analysis results, and triggers the immediate sending of alarm reports when timeouts, deviations, or curve anomalies are detected.

[0008] In one embodiment of the present invention, the real-time acquisition of operating data during the operation of the cylinder valve via the Industrial Internet includes: S11, the valve opening degree and time are sampled synchronously at a preset sampling interval to form dynamic curve data of the valve opening / closing process; S12, calculate the difference between the setpoint and feedback value of the proportional servo valve, and record the result. Abnormal data points.

[0009] In one embodiment of the present invention, storing the collected operational data into a database according to a preset format includes: S21 uses a time-series database to store the valve opening / closing timestamp data, where each event record contains a triplet of unit number, action type and timestamp. S22, Establish a dual-unit comparison table for oil pump operating time data, stored in the following format: and A parallel field structure.

[0010] In one embodiment of the present invention, the multi-dimensional intelligent analysis based on stored runtime data includes: S31, When calculating the maximum opening / closing time of the cylinder valve, the sliding window algorithm is used to sort all action times within the reporting period and extract the peak value; S32, when statistically analyzing the oil pump operating time deviation, the calculation formula is as follows: It also records units whose deviations exceed a preset threshold.

[0011] In one embodiment of the present invention, the step of periodically sending a normal status report based on the analysis results includes: S41, the report is encrypted using a hierarchical encryption transmission protocol, and reports containing abnormal data are encrypted using the AES-256 algorithm; S42 sends alarm reports via both SMS and WeChat Work channels, with sending priority based on... The abnormality level is dynamically adjusted.

[0012] In one embodiment of the present invention, it further includes: S5, a time-series forecasting model is constructed based on historical data, and the calculation formula is as follows: ,in and These are adaptive learning coefficients used to predict the future operating status of the cylinder valve system and generate maintenance recommendations.

[0013] To achieve the above objectives, a second aspect of the present invention provides an intelligent monitoring and analysis device for the operating status of a cylinder valve, comprising: The industrial internet data acquisition module is used to collect operational data of the cylinder valve in real time through the industrial internet. The operational data includes cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and time, and proportional servo valve setpoint and feedback value. The time-series database storage module is used to store the collected runtime data into the database in a preset format and to clean up expired data according to a set period. The multi-dimensional intelligent analysis module is used to perform multi-dimensional intelligent analysis based on stored operating data, and generate a structured analysis report that includes statistics on the number of cylinder valve actions, timeout judgment, oil pump operating deviation, servo valve deviation, and opening curve comparison to obtain analysis results; The communication and alarm module is used to periodically send normal status reports through a preset communication channel based on the analysis results, and to trigger the immediate sending of alarm reports when timeouts, deviations, or curve anomalies are detected.

[0014] The intelligent monitoring and analysis method and device for the operating status of cylinder valves according to embodiments of the present invention monitors and analyzes the monitoring data required by maintenance personnel during the operation of cylinder valves and generates reports to send to maintenance personnel, enabling maintenance personnel to regularly grasp the operating status of the cylinder valve system. It is applicable to the automated status assessment and predictive maintenance of cylinder valve systems in large hydropower stations.

[0015] To achieve the above objectives, a third aspect of this application provides a computer device, including a processor and a memory; wherein the processor reads executable program code stored in the memory to run a program corresponding to the executable program code, so as to implement the intelligent monitoring and analysis method for cylinder valve operating status as described in the first aspect embodiment.

[0016] To achieve the above objectives, the fourth aspect of this application proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the intelligent monitoring and analysis method for the operating status of a cylinder valve as described in the first aspect embodiment. Attached Figure Description

[0017] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 A flowchart of an intelligent monitoring and analysis method for the operating status of a cylinder valve provided in an embodiment of the present invention; Figure 2 This is an architecture diagram of an intelligent monitoring and analysis system for the operating status of a cylinder valve provided in an embodiment of the present invention; Figure 3 A data logic diagram of an intelligent monitoring and analysis system for the operating status of a cylinder valve provided in an embodiment of the present invention; Figure 4This is a diagram of the intelligent analysis report interface for cylinder valve operation data provided in an embodiment of the present invention; Figure 5 This is a comparison chart of the valve opening and closing curves with the standard curve provided in an embodiment of the present invention; Figure 6 This is a structural diagram of an intelligent monitoring and analysis device for the operating status of a cylinder valve provided in an embodiment of the present invention; Figure 7 The computer device provided in the embodiments of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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 scope of protection of the present invention.

[0020] The following description, with reference to the accompanying drawings, describes an intelligent monitoring and analysis method and system for the operating status of a cylinder valve according to an embodiment of the present invention.

[0021] Example 1 This embodiment provides a method for intelligent monitoring and analysis of the operating status of a cylinder valve. For example... Figure 1 As shown, the method includes the following steps: S1, real-time acquisition of operating data during the operation of the cylinder valve via the Industrial Internet, including cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and time, and proportional servo valve setpoint and feedback value.

[0022] Specifically, in some implementations, the core data input step of the intelligent monitoring and analysis system of this invention is the real-time acquisition of control commands, status signals, and timestamp data during the operation of the cylinder valve via the Industrial Internet. This step relies on the industrial Ethernet and PLC (Programmable Logic Controller) system within the hydropower station, employing industrial communication protocols such as OPC UA (Open Platform UA) or Modbus TCP to achieve high-precision, low-latency acquisition of key operating parameters in the cylinder valve control system. The acquired data includes, but is not limited to, cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and timing, and setpoints and feedback values ​​of the proportional servo valve. All data carries precise timestamp information to ensure the time consistency and accuracy of subsequent analysis.

[0023] The system acquisition frequency is typically set to 100ms to 500ms to meet the requirements for capturing dynamic processes. Timestamp accuracy should be no less than milliseconds to support accurate calculation of valve action time. The setpoint and feedback value acquisition accuracy of the proportional servo valve is 0.1%, with a sampling range of 0% to 100%, conforming to the control signal accuracy requirements in IEC 61131-3. The acquisition of oil pump start / stop commands needs to be logically correlated with unit status signals (such as generator state, shutdown state) to determine whether the oil pump operation conforms to the expected process.

[0024] This step is widely used in the cylinder valve system of large hydropower stations, especially in the "unmanned operation" mode. The system can automatically collect and store cylinder valve operating data, providing a data foundation for subsequent intelligent analysis. The collected data will be transmitted to the data storage system and used to calculate key indicators such as cylinder valve opening / closing time, oil pump running time, and proportional servo valve deviation.

[0025] This step automates and enables real-time acquisition of valve operating data, avoiding the inefficiency and lag of traditional manual inspections. Through high-precision timestamps and multi-dimensional signal acquisition, the system can accurately identify abnormal behaviors during valve operation, such as timeouts and excessive deviations, providing a reliable basis for predictive maintenance and fault early warning.

[0026] Furthermore, S1 includes: S11, the valve opening degree and time are sampled synchronously at a preset sampling interval to form dynamic curve data of the valve opening / closing process.

[0027] Specifically, this step utilizes high-precision sensors and a timestamp synchronization module deployed in the valve control system to achieve real-time acquisition and recording of valve opening signals and time information. Specifically, the sensors acquire valve position signals, typically analog or digital stroke feedback signals, with a sampling frequency set to 10Hz (i.e., a sampling period of 0.1s). This ensures that sufficient dynamic change points are captured during the valve's opening or closing process, thereby constructing a high-resolution valve opening-time dynamic curve.

[0028] The sampling process must meet time synchronization accuracy requirements, typically employing industrial Ethernet or a high-precision clock module built into the PLC to ensure the deviation between the sampling timestamp and the actual action time is less than 10ms. Sampling data is stored in a structured format (e.g., timestamp + opening value) in the data storage system, providing fundamental data support for subsequent intelligent analysis. During the data processing phase, the system segments the valve opening and closing process according to the sampling time point, extracting key features such as opening / closing time, curve slope, and maximum opening response delay.

[0029] This procedure is widely applicable to the status monitoring of cylinder valve systems in large hydropower stations, especially under conditions of frequent unit start-ups and shutdowns and load regulation, effectively capturing abnormal trends in cylinder valve operation. With a sampling interval of 0.1 seconds, the system can identify non-standard opening curves caused by hydraulic system response lag, servo valve control deviations, or mechanical jamming, thus providing data for predictive maintenance.

[0030] The technical benefits of this step are reflected in improved accuracy and real-time performance of condition assessment. Through high-frequency synchronous sampling, the system can generate accurate dynamic curves, providing reliable input for subsequent deviation analysis from standard curves. This helps to promptly detect abnormal valve operation, reduce the frequency of manual inspections, and improve the level of intelligence in hydropower station operation.

[0031] S12, calculate the difference between the setpoint and feedback value of the proportional servo valve, and record the result. Abnormal data points.

[0032] Specifically, this step is based on the real-time acquisition of the proportional servo valve control signal of the cylinder valve, specifically including the setpoint. and feedback value By calculating the absolute value of their difference and the preset deviation threshold By making comparisons, potential control anomalies or actuator malfunctions can be identified.

[0033] In some implementations, this calculation process is typically performed in real-time or offline by the signal processing unit in the intelligent analysis module after the data acquisition system has completed signal sampling. Specifically, within each sampling period, the system reads the given control signal and the actual feedback signal from the proportional servo valve, calculates the difference, and determines whether the requirements are met. If this condition is met, the system will mark the data point as an anomaly and record key information such as the time of occurrence, deviation value, unit to which it belongs, and servo valve number, for subsequent anomaly analysis and report generation.

[0034] The value needs to be configured based on the control accuracy of the cylinder valve system and actual operating experience. In large hydropower stations, it is usually... Set the servo valve stroke range to 0.5% to 1.0% to ensure effective anomaly detection while avoiding false alarms due to normal fluctuations. For example, if the servo valve stroke range is... Up to 100%, then Can be set to to .

[0035] This step is mainly used in practical applications to monitor the control accuracy and response ability of servo valves. Especially during the opening and closing processes of cylinder valves, excessive deviation of proportional servo valves may indicate problems such as hydraulic system leakage, spool jamming, or sensor failures. By recording and analyzing these abnormal data points, the system can provide accurate fault location basis for maintenance personnel, thereby improving the operational reliability and maintenance efficiency of the cylinder valve system.

[0036] Furthermore, this step has important early warning value in the entire intelligent monitoring system. Its technical implementation not only depends on high-precision data acquisition and synchronization mechanisms, but also needs to combine preprocessing means such as timestamp alignment and signal filtering to ensure the accuracy of deviation calculation. Through this step, the system can achieve dynamic monitoring of the cylinder valve control loop, providing key technical support for the realization of the "unattended" mode of hydropower stations.

[0037] S2. Store the collected operation data in the database in a preset format, and clean up expired data according to the set period.

[0038] Specifically, the acquisition system obtains key status signals during the operation of the cylinder valve through the PLC or SCADA system, including but not limited to opening commands, closing commands, position status commands, timestamps, oil pump start / stop status, proportional servo valve given and feedback values, etc. These data are transmitted to the data storage module in real time through industrial communication protocols such as OPC UA or Modbus TCP. The data storage system adopts a preset database table structure, and each field corresponds to a specific operation parameter, such as `valve_open_time`, `valve_close_time`, `pump_run_duration`, etc., and the data types include `TIMESTAMP`, `FLOAT`, `BOOLEAN`, etc., to meet the storage requirements of different data types. The data writing operation follows the ACID transaction principle to ensure data consistency and reliability in high-concurrency scenarios.

[0039] The data storage system supports custom storage periods and data retention policies. For example, the data retention period can be set to 365 days, and data older than this time will be marked as expired and a batch deletion operation will be performed at the set cleanup period (such as 2 am on Sunday). The cleanup policy can be filtered based on the timestamp field, for example, execute the SQL statement `DELETE FROM valve_data WHERE timestamp < CURRENT_DATE - INTERVAL '365 days'` to ensure that the database capacity is controllable and avoid the impact of redundant data on system performance.

[0040] This step is widely used in the valve systems of large hydropower stations, especially in "unmanned" operation modes where maintenance personnel cannot access field data in real time. Therefore, it relies on the system's automatic storage and cleanup mechanism to ensure the queryability of historical data and the stability of system operation. Simultaneously, this mechanism provides a high-quality, structured data source for subsequent intelligent data analysis systems, supporting the statistical analysis of indicators such as valve opening / closing counts, timeouts, and oil pump runtime deviations.

[0041] This step enables standardized storage and automated management of valve operation data, effectively improving data processing efficiency, reducing the frequency of manual intervention, and providing stable and reliable historical data support for the system. It is a fundamental step in realizing intelligent analysis and predictive maintenance.

[0042] Furthermore, S2 includes: S21 uses a time-series database to store the valve opening / closing timestamp data, where each event record contains a triplet of unit number, action type, and timestamp.

[0043] Specifically, this step uses a structured storage method to record key events during the operation of the cylinder valve in the form of triplets, namely (unit number, action type, timestamp), thereby providing an efficient and traceable data foundation for subsequent data analysis and anomaly detection.

[0044] In some implementations, this step is technically based on the integration of an Industrial Internet of Things (IIoT) platform with a Time Series Database (TSDB). Upon receiving an open or close command, the PLC (Programmable Logic Controller) in the valve control system records the corresponding action timestamp and uploads the data in real time to the data acquisition system via industrial communication protocols such as OPC UA, MQTT, or Modbus. The data acquisition system cleans and formats the raw data, then writes the event data into the time series database. Each event record includes the unit number (e.g., #1, #2, etc.), the action type (open or close), and a timestamp accurate to the millisecond level (e.g., `2024-05-15 14:30:45.123`).

[0045] Timestamps are typically accurate to the millisecond level. The unit is seconds (s) to ensure the accuracy of event timing. The action type field is an enumeration (`enum`) with a value of "on" or "off" for easy subsequent statistical and classification processing. The unit number field is a string used to identify the valve actions of different units, supporting parallel analysis of multiple units.

[0046] This step is widely used in the condition monitoring systems of cylinder valves in large hydropower stations. Through the efficient writing and querying capabilities of the time-series database, the system can quickly statistically analyze key indicators such as the number of opening / closing times and the distribution of action times for cylinder valves within a set reporting period, and use this data to calculate analytical parameters such as the number of timeouts and the maximum action time. For example, if the cylinder valve opening time is set to... Then the opening time each time If satisfied If it does not, it will be judged as a timeout event.

[0047] By using structured storage and high-precision timestamp recording, the analyzability and traceability of valve operation data are significantly improved, providing a reliable data source for subsequent intelligent analysis systems. Meanwhile, the efficient query capabilities of the time-series database support the generation of real-time or periodic operation status reports, facilitating the realization of an "unmanned" operation and maintenance mode for hydropower stations and improving system automation and operational efficiency.

[0048] S22, Establish a dual-unit comparison table for oil pump operating time data, stored in the following format: and A parallel field structure.

[0049] Specifically, this step stores the running time data of two oil pumps (#1 pump and #2 pump) using a parallel field structure, with the specific fields being: and This table is used to record the time interval between each oil pump start-up and shutdown. In terms of technical implementation, this comparison table typically adopts a relational database table structure design, with each record corresponding to one oil pump operation event. It includes fields such as unit number, start-up timestamp, stop timestamp, and runtime. and As parallel fields, the running time of the two oil pumps is stored separately to facilitate subsequent horizontal comparative analysis.

[0050] The accuracy of oil pump running time acquisition should be no less than milliseconds to ensure the accuracy of time deviation calculation. Running time deviation is defined as the absolute value of the difference between the total running time of two oil pumps under the same operating conditions, i.e. This deviation value can serve as an important basis for judging whether the performance of the oil pump is balanced. If the deviation exceeds the set threshold (such as 5 seconds), it may indicate that there are problems such as oil pump wear, abnormal oil pressure, or control signal delay in the system.

[0051] This comparison table is primarily used for analyzing the operating status of oil pumps during unit startup and shutdown. For example, when the unit enters generator or shutdown mode, the system records the start-up and shutdown times of the cylinder valve oil pump and... and The data is written into the corresponding fields to form structured data. Through regular statistics and comparisons, maintenance personnel can quickly identify abnormal oil pump operation, providing data support for subsequent maintenance.

[0052] Through structured storage and comparative analysis, a quantitative assessment of the operating status of dual oil pumps was achieved, improving the automation and accuracy of valve system operating status monitoring and providing a reliable data foundation for predictive maintenance.

[0053] S3 performs multi-dimensional intelligent analysis based on stored operating data, generating a structured analysis report that includes statistics on the number of cylinder valve actions, timeout determination, oil pump operating deviation, servo valve deviation, and opening curve comparison to obtain analysis results.

[0054] Specifically, the system first reads historical data on the valve's operating status from the data storage module, including timestamps of opening / closing commands recorded by the PLC, status feedback signals, oil pump start / stop times, servo valve setpoints and feedback values, and sampled data showing the valve opening degree changing over time. The system uses time series analysis to clean, align, and normalize this data, ensuring consistency across time. Subsequently, the system uses a pre-defined logical judgment model to count the number of valve actions, for example, by detecting event pairs between "open command" and "fully open status command" to calculate the number of openings. Similarly, count the number of times it is closed. .

[0055] Regarding timeout determination, the system sets standard time thresholds for valve opening and closing. and If the actual action time or If the timeout occurs, it is considered a timeout, and the number of timeouts is recorded. And the time of occurrence. Regarding the oil pump operating deviation, the system calculates the difference in running time between oil pumps 1 and 2 under the same operating conditions. And set a deviation threshold. It is used to determine whether there is an anomaly.

[0056] In servo valve deviation analysis, the system compares the setpoint of the proportional servo valve. With feedback value Perform point-by-point comparisons and calculate the deviation. And set a deviation threshold. This is used to identify abnormal control accuracy. In addition, the system samples and analyzes the opening curve during the opening and closing process of the cylinder valve, with a sampling interval of [missing information]. It then compares the value point by point with the preset standard curve and calculates the deviation value. It is used to evaluate the smoothness and consistency of the valve's operation.

[0057] In practical applications, this step is suitable for condition assessment and predictive maintenance of valve systems in large hydropower stations. Especially in "unmanned" operation modes, it can significantly reduce the frequency of manual inspections and improve maintenance efficiency. Its technical value lies in providing maintenance personnel with intuitive and quantifiable operational status assessment data through structured report output, thereby achieving intelligent support for fault early warning and maintenance decisions.

[0058] Furthermore, S3 includes: S31, when calculating the maximum opening / closing time of the cylinder valve, the sliding window algorithm is used to sort all action times within the reporting period and extract the peak value.

[0059] Specifically, in the data intelligent analysis system, the step of calculating the maximum opening / closing time of the cylinder valve employs a sliding window algorithm to sort all action times within the reporting cycle and extract the peak value. This technology is based on the principles of time series data processing and statistical analysis. In some implementations, the system first extracts all opening and closing action time sequences of the cylinder valve within a set reporting cycle from the data storage module. Each action time consists of the opening command time and fully open state time, and the closing command time and fully closed state time recorded by the PLC. The timestamp accuracy is typically at the millisecond level (ms) to ensure the accuracy of the action time.

[0060] Furthermore, the system employs a sliding window algorithm to process the time series data. The size of the sliding window can be set according to actual needs, for example, set to... That is, each analysis window lasts 60 seconds. Within each window, the system tracks the valve opening time. and closing time The data is sorted in ascending order of timestamps to identify the longest action time within the window. After sorting, the system compares all action times to extract the maximum value within the window. Record the corresponding unit number and the time of occurrence.

[0061] Optionally, the system can also set an action time threshold. This is used to determine whether a timeout has occurred. For example, if the valve opening time... If this happens, a timeout alarm will be triggered. In practical applications, this step is suitable for assessing the operational status of multi-unit valve systems in large hydropower stations, and is particularly important for periodic maintenance and anomaly detection.

[0062] Through this step, the system can automatically identify the longest operation time of the cylinder valve within a set cycle, providing maintenance personnel with key performance indicators such as maximum opening time, maximum closing time and their corresponding unit information, thereby achieving a quantitative assessment of the cylinder valve's operating efficiency and improving the system's intelligence level and operation and maintenance response speed.

[0063] S32, when statistically analyzing the oil pump operating time deviation, the calculation formula is as follows: It also records units whose deviations exceed a preset threshold.

[0064] Specifically, in a data-driven intelligent analysis system, statistical analysis of the pump operating time deviation is a crucial step in evaluating the operational stability and load balance of a cylinder valve hydraulic system. This step involves calculating the absolute value of the cumulative operating time difference between the two pumps (#1 pump and #2 pump) within a set reporting period, i.e. This allows us to identify whether there is an imbalance in runtime.

[0065] The system first acquires the start and stop timestamps of each oil pump in real time through the data acquisition module, and calculates the duration of each pump operation based on the timestamps. Then, the system accumulates all operating times within a set reporting period (e.g., 7 days, 15 days, or as needed), obtaining the results. and These two sums represent the total duration for which pump #1 and pump #2 each provided hydraulic support to the valve system during the reporting period. By calculating the difference between the two and taking the absolute value, the system can quantify the operating time deviation between the pumps, providing a basis for subsequent anomaly detection.

[0066] Deviation threshold The value is typically set based on the oil pump's design life, load capacity, and system redundancy configuration; a typical value is... or It can also be set to a fixed time value (e.g.) ).when When this happens, the system will record the unit as having an abnormal operating time deviation and add it to the alarm list.

[0067] This procedure is widely used in the valve systems of large hydropower stations, especially under conditions of frequent unit start-ups and shutdowns and frequent valve operations. By continuously monitoring the deviation in oil pump operating time, the system can assist maintenance personnel in determining whether there are problems such as oil pump failure, uneven distribution of control system load, or hydraulic system load imbalance, thereby providing early warnings and arranging maintenance plans.

[0068] By quantifying the differences in oil pump operating time, the operational reliability and maintenance efficiency of the cylinder valve hydraulic system are improved. In unmanned operation mode, this function can effectively reduce the frequency of manual intervention, realize automated monitoring and intelligent diagnosis of the status of critical equipment, and provide strong support for the intelligent operation and maintenance of hydropower stations.

[0069] S4 periodically sends normal status reports through a preset communication channel based on the analysis results, and triggers the immediate sending of alarm reports when timeouts, deviations, or curve anomalies are detected.

[0070] Specifically, in some implementations, the report sending system of this invention periodically sends normal status reports through a preset communication channel based on the output results of the data intelligent analysis system, and triggers the immediate sending of alarm reports when timeouts, deviations, or curve anomalies are detected. This step is a key link in realizing automated operation and maintenance in the entire intelligent monitoring and analysis system for the valve's operating status, and its technical implementation is based on a classification processing mechanism and standardized configuration of communication protocols based on status assessment results.

[0071] The system employs a timed task scheduling mechanism. By setting a report sending cycle (such as 24 hours, 72 hours, or a user-defined cycle), a standardized operational status report is generated by the data intelligent analysis system at the end of each cycle. This report includes key indicators such as the number of valve opening / closing times, maximum operating time, oil pump runtime, number of reverse adjustments, number of air replenishment actions, and the deviation between the proportional servo valve's setpoint and feedback. The report content is encapsulated in a structured data format (such as JSON or XML) and sent to the maintenance personnel's monitoring terminal or mobile device via a pre-defined communication channel (such as industrial communication protocols like OPC UA, MQTT, and Modbus TCP).

[0072] The system supports user-defined alarm thresholds, such as valve opening / closing timeout thresholds (default setting is 120 seconds), oil pump running time deviation thresholds (default setting is ±15 seconds), and proportional servo valve deviation thresholds (default setting is ±5%). When real-time monitoring data exceeds the set thresholds, the system will trigger the generation and transmission of an immediate alarm report. For example, if the valve opening time... If the timeout occurs, it is determined to be an activation timeout, and the time of occurrence and unit number are recorded.

[0073] This procedure is widely applicable to the valve systems of large hydropower stations, especially in "unmanned" operation modes. Maintenance personnel can receive abnormal alarms in real time through a remote monitoring platform and take timely maintenance measures to prevent equipment failures from escalating. Meanwhile, periodic reports provide data support for regular maintenance plans, improving operational efficiency and system reliability.

[0074] This step enables an automated reporting and hierarchical transmission mechanism for the operating status of cylinder valves, effectively reducing the frequency of manual inspections, improving the speed of anomaly response, and providing a solid technical guarantee for the intelligent operation and maintenance of hydropower stations.

[0075] Furthermore, S4 includes: S41 uses a hierarchical encryption transmission protocol to encrypt reports, and reports containing abnormal data are encrypted using the AES-256 algorithm.

[0076] Specifically, in this invention, the step of "encrypting the report using a hierarchical encryption transmission protocol, with reports containing abnormal data encrypted using the AES-256 algorithm" is a crucial step in ensuring the data security of the intelligent analysis report on the valve's operating status during transmission. This step is technically implemented based on a hierarchical encryption mechanism, combined with the AES-256 algorithm to perform high-strength encryption on abnormal data, ensuring that sensitive information is not illegally accessed or tampered with during transmission.

[0077] In some implementations, hierarchical encryption transport protocols process reports in layers based on their sensitivity. Normal operation status reports use basic encryption methods (such as symmetric encryption algorithms like TLS 1.3 or SM4), while reports containing anomalous data are encrypted using the AES-256 algorithm. AES-256 is an Advanced Encryption Standard (AES-256) with a 256-bit key length. It is a symmetric encryption algorithm with extremely high encryption strength and good computational efficiency, meeting the security requirements for data encryption in the NIST (National Institute of Standards and Technology) SP 800-38D standard.

[0078] In its specific operation, after generating a report, the system first categorizes the report content using a preset rule engine. If the report contains abnormal information such as "valve opening timeout" or "excessive deviation between proportional servo valve setpoint and feedback," the system automatically triggers the AES-256 encryption process. The encryption process includes key negotiation, data segmentation, padding (e.g., PKCS7), and encryption mode selection (e.g., CBC or GCM). The encryption key is negotiated between the report sending system and the receiving maintenance personnel's terminal through a secure channel (e.g., Diffie-Hellman key exchange) to ensure dynamic key updates and security.

[0079] In application scenarios, this encryption mechanism is widely applicable to remote monitoring and report transmission in hydropower station valve systems, especially in "unmanned operation" mode. Maintenance personnel receive encrypted reports via mobile terminals or remote monitoring platforms and must use a pre-issued decryption key to decrypt the reports before viewing the content. This step effectively prevents abnormal data from being stolen or tampered with during transmission, thus improving the overall security level of the system.

[0080] This step, by introducing the AES-256 algorithm to encrypt abnormal data, ensures the confidentiality and integrity of sensitive information, enhances the data transmission security of the system in the industrial internet environment, and provides reliable information assurance for the predictive maintenance of the cylinder valve system.

[0081] S42 sends alarm reports via both SMS and WeChat Work channels, with sending priority based on... The abnormality level is dynamically adjusted.

[0082] Specifically, this step involves sending alarm reports via both SMS and WeChat Work channels, dynamically adjusting the sending priority based on the anomaly level. This technology is based on real-time monitoring and intelligent analysis of the cylinder valve's operating status. In some implementations, the system analyzes the cylinder valve's operating data using a pre-set anomaly detection algorithm to calculate the loss function value for each anomaly event. This value is used to quantify the severity of the anomaly. Loss function The calculation is based on deviation indicators across multiple dimensions, such as the deviation of the valve opening / closing time from the standard value, the deviation of the proportional servo valve setpoint from the feedback value, and the deviation of the oil pump running time, etc., specifically in the form of:

[0083] in, Indicates the first The actual value of each monitoring parameter This indicates its reference value. These are the weighting coefficients for the corresponding parameters. This represents the total number of abnormal parameters involved in the calculation. This formula is used to comprehensively evaluate the degree of operational abnormality of the valve at a given moment, thereby determining the alarm priority.

[0084] In terms of implementation, the system adopts a tiered alarm mechanism, which will... The values ​​are divided into multiple levels (such as low, medium, high, and urgent), and different sending strategies are configured for each level. For example, when Exceeding the preset threshold When this happens, the system will trigger an alarm and, according to... The size of the notification determines whether to send it via SMS, WeChat Work, or both. SMS is suitable for immediate notifications in emergencies, while WeChat Work is used for routine alarm notifications and archiving.

[0085] The system supports user-defined alarm level thresholds, sending channel priority rules, alarm message templates, etc. For example, you can set... This indicates that an alarm is triggered when the loss exceeds 30%. Furthermore, the system supports a multi-user subscription mechanism, allowing maintenance personnel to configure the frequency and method of receiving alarm information based on their permissions.

[0086] This step is widely applicable in practical applications to the operation and maintenance of valve systems in large hydropower stations, especially in "unmanned" modes, where it significantly improves fault response efficiency. Through a dual-channel transmission mechanism, the system ensures reliable delivery of alarm information under different network environments and personnel availability conditions, thereby achieving closed-loop management of valve operating status. Its technical value lies in improving the timeliness and accessibility of alarm information, providing maintenance personnel with multi-dimensional and tiered early warning support, and effectively reducing the risk of equipment failure.

[0087] The intelligent monitoring and analysis method for the operating status of cylinder valves in this invention realizes automated monitoring and intelligent analysis of the operating status of cylinder valves, reduces the workload of manual inspection, improves operation and maintenance efficiency, and supports the "unmanned operation" mode of hydropower stations.

[0088] Also includes: S5, a time-series forecasting model is constructed based on historical data, and the calculation formula is as follows: ,in and These are adaptive learning coefficients used to predict the future operating status of the cylinder valve system and generate maintenance recommendations.

[0089] Specifically, this step involves collecting key operating parameters of the valve during its opening and closing process (such as opening degree, timestamp, and oil pump start / stop status) and using an adaptive learning mechanism to establish a predictive model, thereby achieving dynamic prediction of the valve's future operating state. In the specific implementation, a linear time-series prediction model is used, and its calculation formula is as follows:

[0090] in, Indicates the time of the cylinder valve The actual opening value, This indicates the change in valve opening between adjacent time points. and The adaptive learning coefficients are dynamically adjusted through online learning algorithms (such as Least Mean Square Error (LMS) or Recursive Least Squares (RLS)) to adapt to the nonlinear changes in the valve's operating state and external disturbances.

[0091] The system first preprocesses the valve operation data, including time alignment, outlier removal, and sliding window division, to ensure the continuity and stability of the input data. Then, historical data is used to train the model parameters. and This allows the model to accurately reflect the dynamic response characteristics of the cylinder valve under different operating conditions. In practical applications, the model makes a prediction every 0.1 seconds and compares it with the current sampled value. If the deviation exceeds a preset threshold (e.g., ...), the model will detect the error. If this occurs, an abnormal alarm mechanism will be triggered.

[0092] This step in the system is mainly used to predict potential anomalies during the opening and closing of the cylinder valve, such as timeouts, oil pump operation deviations, and proportional servo valve feedback anomalies, thereby providing maintenance personnel with data-driven maintenance suggestions. Its technical value lies in improving the real-time performance and accuracy of cylinder valve status assessment, providing key support for the "unmanned operation" mode of hydropower stations.

[0093] The intelligent monitoring and analysis method for the operating status of cylinder valves in this invention introduces a time-series prediction model based on historical data. The system can dynamically predict the future operating status of cylinder valves and automatically generate maintenance suggestions, thereby further improving the accuracy and timeliness of predictive maintenance, extending equipment service life and reducing the risk of unplanned downtime.

[0094] Example 2 This invention relates to an intelligent monitoring and analysis system for the operating status of a cylinder valve, mainly comprising a data acquisition system, a data storage system, a data intelligent analysis system, and a report sending system. Figure 2 and Figure 3 As shown: The data acquisition system, relying on power plant industrial internet technology, can collect data needed by maintenance personnel during the operation of the cylinder valve, including: cylinder valve opening command, cylinder valve fully open position status command; cylinder valve closing command, cylinder valve fully closed position status command; cylinder valve opening command time, cylinder valve fully open position status command time; cylinder valve closing command time, cylinder valve fully closed position status command time; unit generating status command, unit shutdown status command; cylinder valve system oil pump start command, stop command; cylinder valve system oil pump start command time, stop command time; cylinder valve reverse adjustment command, reset command; cylinder valve pressure oil tank automatic air replenishment valve air replenishment command, stop air replenishment command; cylinder valve pressure oil tank automatic air replenishment valve receiving air replenishment command time, stop air replenishment command time; cylinder valve proportional servo valve setpoint, feedback value, and cylinder valve opening degree.

[0095] The data storage system is mainly responsible for storing and periodically cleaning the data collected by the data acquisition system, as well as storing the reports generated by the data intelligent analysis system.

[0096] The data intelligent analysis system mainly enables intelligent analysis of the data stored in the data storage system, generating reports including the number of times the cylinder valve opens and closes within a certain period, the number of times the cylinder valve opens and closes for timeout, the maximum opening and closing time of the cylinder valve and the corresponding unit number, the running time and running time deviation of the cylinder valve oil pump during unit startup and shutdown, the number of times the cylinder valve oil pump starts during unit startup and shutdown, the number of times the cylinder valve reverses, the number of times the cylinder valve replenishes air, the cylinder valve replenishment time, the deviation between the setpoint and feedback of the cylinder valve proportional servo valve, and the deviation between the cylinder valve opening and closing curves and the standard curve.

[0097] The report sending system can perform normal and alarm sending. Normal sending involves periodically sending the valve operation status report generated by the data intelligent analysis system to maintenance personnel. Alarm sending involves monitoring the valve operation status and sending a valve operation status report to maintenance personnel when an abnormality occurs.

[0098] In data intelligence analysis systems: Number of times the cylinder valve is opened: The total number of times the cylinder valve control system PLC receives an opening command and then receives a cylinder valve fully open position status command within the set report sending interval.

[0099] Number of times the cylinder valve closes: The total number of times the cylinder valve control system PLC receives a closing command and then moves to the fully closed position within the set report sending interval.

[0100] Cylinder valve opening time: The time from when the cylinder valve control system PLC receives the cylinder valve opening command to when the cylinder valve is in the fully open position is recorded, and the cylinder valve opening time is recorded for each time within the set report sending interval.

[0101] Cylinder valve closing time: The time from when the cylinder valve control system PLC receives the cylinder valve closing command to when the cylinder valve is in the fully closed position is recorded, and the cylinder valve closing time is recorded for each time within the set report sending interval.

[0102] Valve opening timeout count: The valve opening time is compared with the set valve opening time value for each time within the set report sending interval. If the valve opening time is longer than the set value, it is judged as a valve opening timeout. The total number of times the valve opening timeout is judged as a valve opening timeout within the set report sending interval is counted along with the time of each valve opening timeout.

[0103] Valve closing timeout count: The valve closing time is compared with the set valve closing time value for each time within the set report sending interval. If the valve closing time is greater than the set valve closing time value, it is judged as a valve closing timeout. The total number of times the valve closing timeout is judged within the set report sending interval is counted along with the time of each valve closing timeout.

[0104] Maximum valve opening time: The maximum value of the valve opening time within the report sending interval.

[0105] Maximum valve closing time: The maximum valve closing time within the report sending interval.

[0106] Running time of cylinder valve oil pump during unit startup: When the unit receives the power generation status command, the cylinder valve control system PLC receives the oil pump start command and the oil pump stop command, and records the running time of cylinder valve oil pump during each unit startup within the report sending interval.

[0107] Duration of cylinder valve oil pump operation during unit shutdown: When the unit receives the shutdown status order, the cylinder valve control system PLC receives the oil pump start order and the oil pump stop order, and records the duration of cylinder valve oil pump operation during each unit shutdown within the report sending interval.

[0108] Operating time deviation of cylinder valve oil pump: The absolute value of the difference in the total operating time of cylinder valve No. 1 and No. 2 oil pumps within the report sending interval.

[0109] Number of times the cylinder valve oil pump is started: The total number of times the cylinder valve control system PLC receives an oil pump start command to receive an oil pump stop command within the report sending interval.

[0110] Number of times the cylinder valve reverses: The number of times the cylinder valve system receives a cylinder valve reverse action command and a cylinder valve reverse reset command within the report sending interval.

[0111] Number of times the cylinder valve replenishes air: The total number of times the automatic air replenishment device of the cylinder valve pressure oil tank receives an air replenishment order to receive a stop air replenishment order within the report sending interval.

[0112] Cylinder valve air replenishment time: The time from receiving the air replenishment order to receiving the stop air replenishment order within the report sending interval.

[0113] Cylinder valve proportional servo valve setpoint and feedback deviation: The difference between the setpoint and feedback of the cylinder valve proportional servo valve at each sampling time within the report sending interval.

[0114] Deviation between the cylinder valve opening process curve and the standard cylinder valve opening process curve: During the cylinder valve opening process, the cylinder valve opening degree and time are sampled and a curve is formed. The difference between the cylinder valve opening degree at the same sampling time and the standard cylinder valve opening process curve is calculated. The sampling interval is 0.1s. The sampling time is the time from when the cylinder valve receives the opening command to when the cylinder valve receives the fully open position status command within the report sending interval.

[0115] Deviation between the cylinder valve closing process curve and the cylinder valve closing process standard curve: During the cylinder valve opening process, the cylinder valve opening degree and time are sampled and a curve is formed. The difference between the cylinder valve opening degree at the same sampling time and the set cylinder valve closing process standard curve is the sampling interval time of 0.1s. The sampling time is the time from when the cylinder valve receives the closing command to when the cylinder valve receives the fully closed position status command within the report sending interval.

[0116] The main reasons for abnormal operation of the cylinder valve are: cylinder valve opening timeout, cylinder valve closing timeout, cylinder valve oil pump running time exceeding the set value when the unit starts up, cylinder valve oil pump running time exceeding the set value when the unit stops, excessive deviation between the setpoint and feedback of the cylinder valve proportional servo valve, excessive deviation between the cylinder valve opening curve and the standard cylinder valve opening curve, and excessive deviation between the cylinder valve closing curve and the standard cylinder valve opening curve. When any of the above phenomena occur, it is judged that the cylinder valve is in abnormal operation, and the reporting system sends a cylinder valve operation status report to the maintenance personnel.

[0117] Among them, the intelligent analysis report interface for cylinder valve operation data is as follows: Figure 4 As shown, the opening and closing curves of the cylinder valve are compared with the standard curve. Figure 5 As shown.

[0118] This invention enables intelligent data analysis of the cylinder valve system and generates reports, which are periodically sent to maintenance personnel. This allows personnel to keep abreast of the relevant operating status of the cylinder valve, reducing the number of inspections and contributing to the realization of unmanned operation in power plants.

[0119] Example 3 This invention also provides an intelligent monitoring and analysis device 10 for the operating status of a cylinder valve, such as... Figure 6 As shown, the device 10 includes: The industrial internet data acquisition module 100 is used to collect operational data of the cylinder valve in real time through the industrial internet. The operational data includes cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and time, and proportional servo valve setpoint and feedback value. The time-series database storage module 200 is used to store the collected running data into the database in a preset format and to clean up expired data according to a set period. The multi-dimensional intelligent analysis module 300 is used to perform multi-dimensional intelligent analysis based on stored operating data, and generate a structured analysis report that includes statistics on the number of cylinder valve actions, timeout determination, oil pump operating deviation, servo valve deviation, and opening curve comparison to obtain analysis results; The communication and alarm module 400 is used to periodically send normal status reports through a preset communication channel based on the analysis results, and to trigger the immediate sending of alarm reports when timeouts, deviations, or curve abnormalities are detected.

[0120] Furthermore, the industrial internet data acquisition module is also used for: The valve opening degree and time are sampled synchronously at a preset sampling interval to form dynamic curve data of the valve opening / closing process; The difference between the setpoint and feedback value of the proportional servo valve is calculated and recorded. Abnormal data points.

[0121] This invention discloses an intelligent monitoring and analysis device for the operating status of a cylinder valve, which realizes automated monitoring and intelligent analysis of the operating status of the cylinder valve, reduces the workload of manual inspection, improves operation and maintenance efficiency, and supports the "unmanned operation" mode of hydropower stations.

[0122] Example 4 To implement the methods of the above embodiments, the present invention also provides a computer device, such as... Figure 7 As shown, the computer device 600 includes a memory 601 and a processor 602; wherein, the processor 602 reads executable program code stored in the memory 601 to run a program corresponding to the executable program code, so as to implement the various steps of the method described above.

[0123] Example 5 To implement the above embodiments, this application also proposes a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method described in the foregoing embodiments.

[0124] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0125] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0126] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. A method for intelligent monitoring and analysis of the operating status of a cylinder valve, characterized in that, include: S1, real-time collection of operating data during the operation of the cylinder valve through the Industrial Internet, the operating data including cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and time, and proportional servo valve setpoint and feedback value; S2, stores the collected operational data in a preset format to the database, and cleans up expired data according to a set cycle; S3 performs multi-dimensional intelligent analysis based on stored operating data, generating a structured analysis report that includes statistics on the number of cylinder valve actions, timeout determination, oil pump operating deviation, servo valve deviation, and opening curve comparison to obtain analysis results; S4 periodically sends normal status reports through a preset communication channel based on the analysis results, and triggers the immediate sending of alarm reports when timeouts, deviations, or curve anomalies are detected.

2. The method as described in claim 1, characterized in that, The real-time acquisition of operational data during the operation of the cylinder valve via the Industrial Internet includes: S11, the valve opening degree and time are sampled synchronously at a preset sampling interval to form dynamic curve data of the valve opening / closing process; S12, calculate the difference between the setpoint and feedback value of the proportional servo valve, and record the result. Abnormal data points.

3. The method as described in claim 1, characterized in that, The step of storing the collected operational data into the database according to a preset format includes: S21 uses a time-series database to store the valve opening / closing timestamp data, where each event record contains a triplet of unit number, action type and timestamp. S22, Establish a dual-unit comparison table for oil pump operating time data, stored in the following format: and A parallel field structure.

4. The method as described in claim 1, characterized in that, The multi-dimensional intelligent analysis based on stored runtime data includes: S31, When calculating the maximum opening / closing time of the cylinder valve, the sliding window algorithm is used to sort all action times within the reporting period and extract the peak value; S32, when statistically analyzing the oil pump operating time deviation, the calculation formula is as follows: It also records units whose deviations exceed a preset threshold.

5. The method as described in claim 1, characterized in that, The periodic sending of normal status reports based on the analysis results includes: S41, the report is encrypted using a hierarchical encryption transmission protocol, and reports containing abnormal data are encrypted using the AES-256 algorithm; S42 sends alarm reports via both SMS and WeChat Work channels, with sending priority based on... The abnormality level is dynamically adjusted.

6. The method as described in claim 1, characterized in that, Also includes: S5, a time-series forecasting model is constructed based on historical data, and the calculation formula is as follows: ,in and These are adaptive learning coefficients used to predict the future operating status of the cylinder valve system and generate maintenance recommendations.

7. A device for intelligent monitoring and analysis of the operating status of a cylinder valve, characterized in that, include: The industrial internet data acquisition module is used to collect operational data of the cylinder valve in real time through the industrial internet. The operational data includes cylinder valve opening / closing commands and status feedback, oil pump start / stop commands and time, and proportional servo valve setpoint and feedback value. The time-series database storage module is used to store the collected runtime data into the database in a preset format and to clean up expired data according to a set period. The multi-dimensional intelligent analysis module is used to perform multi-dimensional intelligent analysis based on stored operating data, and generate a structured analysis report that includes statistics on the number of cylinder valve actions, timeout judgment, oil pump operating deviation, servo valve deviation, and opening curve comparison to obtain analysis results; The communication and alarm module is used to periodically send normal status reports through a preset communication channel based on the analysis results, and to trigger the immediate sending of alarm reports when timeouts, deviations, or curve anomalies are detected.

8. The apparatus as claimed in claim 7, characterized in that, The industrial internet data acquisition module is also used for: The valve opening degree and time are sampled synchronously at a preset sampling interval to form dynamic curve data of the valve opening / closing process; The difference between the setpoint and feedback value of the proportional servo valve is calculated and recorded. Abnormal data points.

9. A computer device, characterized in that, Including processor and memory; The processor reads the executable program code stored in the memory to run the program corresponding to the executable program code, so as to implement the intelligent monitoring and analysis method for the cylinder valve operating status as described in any one of claims 1-6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the intelligent monitoring and analysis method for the operating status of cylinder valves as described in any one of claims 1-6.

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