Hydraulic power plant electromechanical equipment fault monitoring method, system, equipment and medium

Abstract

The invention relates to the technical field of hydroelectric monitoring, in particular to a hydraulic power plant electromechanical equipment fault monitoring method, system and equipment and a medium. Collecting various signals of the electromechanical equipment in real time, wherein the signals comprise current, voltage and temperature; when the signal deviates from the standard threshold value, fault detection is carried out; performing time and space registration on the signal to obtain a correction signal; and performing fault diagnosis by comparing the correction signal with a fault library. The temperature measurement label accurately measures the temperature in complex environments with current passing, narrow space, metal materials, high temperature and the like, and the accuracy and reliability of temperature measurement are improved. And meanwhile, the performance and adaptability of the tag are further improved through continuous field testing and optimization work. Passive and wireless signal transmission is realized, the problems of data acquisition, transmission and real-time performance are solved, and the problem of accuracy of temperature analysis and prediction is solved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of hydropower monitoring, and in particular to a method, system, equipment and medium for monitoring faults of electromechanical equipment in a hydropower plant. Background Art

[0002] The electromechanical equipment of a hydropower plant is the core part of the power generation of a hydropower station, and its temperature condition directly affects the operational safety and efficiency of the equipment. During long-term high-intensity operation, electromechanical equipment will experience abnormal temperature rise due to a variety of complex factors such as aging of electrical components, loose connection structure, and deterioration of ventilation and refrigeration environment. Such abnormal temperature rise points are mainly concentrated at the wire connection points, the equipment live busbar connection nuts, and the switch contact positions. Long-term temperature anomalies will accelerate equipment aging, reduce efficiency, and ultimately threaten operational safety, leading to equipment accidents and production interruptions. Traditional temperature monitoring methods usually use active sensors or infrared thermal imagers, but these methods are difficult to install, have high maintenance costs, are not easy to install and deploy in large quantities, cannot fully and real-time collect temperature data of on-site equipment, and are difficult to detect abnormal temperature rise points of equipment in a timely manner. Therefore, it is urgent to study new temperature monitoring technologies to ensure the safe and efficient operation of hydropower plant equipment. Summary of the invention

[0003] In view of the above problems, the present disclosure provides a method, system, device and medium for monitoring faults of electromechanical equipment in a hydropower plant, which are used to solve the problem that traditional equipment temperature monitoring technology and operation and maintenance strategies of hydropower plants are difficult to timely and accurately detect abnormal power generation locations of all equipment.

[0004] In a first aspect, a method for monitoring faults of electromechanical equipment in a hydropower plant comprises:

[0005] Real-time acquisition of various signals from electromechanical equipment, including current, voltage and temperature;

[0006] When the signal deviates from the standard threshold, fault detection is performed; the signal is aligned in time and space to obtain a correction signal; and fault diagnosis is performed by comparing the correction signal with the fault library.

[0007] Furthermore, the signals are aligned in time and space to unify all signals into the same time and space scale.

[0008] Furthermore, when the signal deviates from the standard threshold, it includes:

[0009] A standard threshold is established based on the historical record values ​​of the signal during normal operation of the electromechanical equipment.

[0010] Furthermore, the standard threshold is obtained by arithmetic average, moving average or weighted average.

[0011] Furthermore, various signals of electromechanical equipment are collected in real time, including:

[0012] Collect the current and voltage of each circuit to be tested, and collect the temperature of each part of the electromechanical equipment;

[0013] The temperatures of various parts of the electromechanical equipment, including: generator collector ring excitation carbon brushes, generator stator, generator outlet connection, excitation AC knife switch, excitation DC knife switch, excitation cable on the low-voltage side of the excitation transformer, thrust external circulation pump motor, water-guided external circulation cooling oil pump motor, speed regulator oil pressure device oil pump motor, plant leakage drainage pump motor and maintenance drainage pump motor.

[0014] Furthermore, the temperature of various parts of the electromechanical equipment is collected, including:

[0015] Use ceramic packaged UHF RFID temperature measurement tags for temperature measurement;

[0016] The RFID temperature measurement tag and the reader communicate using the EPC Class 1Gen 2 wireless communication interface protocol based on UHF RFID.

[0017] Furthermore, fault diagnosis is performed by comparing the correction signal with the fault library, including:

[0018] Collect the relevant current, voltage and temperature signals of a fault in the electromechanical equipment, correct them and form a fault feature vector, which is saved in the fault database;

[0019] When an electromechanical equipment fails, the relevant current, voltage and temperature signals are corrected to form a monitoring vector. By comparing the vector distance between the monitoring vector and the fault feature vector in the fault library, the fault feature vector with the closest vector distance is obtained as the fault diagnosis result, and on-site confirmation and troubleshooting are carried out.

[0020] In a second aspect, a hydropower plant electromechanical equipment fault monitoring system includes: a signal acquisition unit and a fault detection unit;

[0021] Signal acquisition unit, used to collect various signals of electromechanical equipment in real time, including current, voltage and temperature;

[0022] The fault detection unit is used to detect faults when the signal deviates from the standard threshold; to align the signal in time and space to obtain a correction signal; and to perform fault diagnosis by comparing the correction signal with the fault library.

[0023] In a third aspect, an electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0024] a memory storing a computer program;

[0025] The processor is used to implement the above-mentioned method for monitoring faults of electromechanical equipment in a hydropower plant when executing the computer program stored in the memory.

[0026] In a fourth aspect, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for monitoring faults of electromechanical equipment in a hydropower plant described above is implemented.

[0027] The present disclosure has at least the following beneficial effects:

[0028] The present invention adopts passive RFID temperature measurement tags suitable for electromechanical equipment in hydropower plants to meet the temperature measurement needs of various types, large quantities and electrified environments; realizes passive wireless transmission of signals; develops edge-cloud collaborative Internet of Things solutions to solve data collection, transmission and real-time problems; integrates multi-source information to solve the problem of temperature analysis and prediction accuracy; and solves the problems of low cloud computing resource utilization and unconcentrated data in hydropower stations.

[0029] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or be understood by implementing the present disclosure. The purpose and other advantages of the present disclosure can be realized and obtained by the structures indicated in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 This is a flow chart of the monitoring method according to an embodiment of the present disclosure;

[0032] Figure 2 This is a schematic diagram of the monitoring system architecture of an embodiment of the present disclosure;

[0033] Figure 3 A schematic diagram of the electronic device structure. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0035] like Figure 1 As shown, a method for monitoring faults of electromechanical equipment in a hydropower plant comprises:

[0036] S101, real-time collection of various signals of electromechanical equipment, including current, voltage and temperature;

[0037] S102, when the signal deviates from the standard threshold, fault detection is performed; the signal is aligned in time and space to obtain a correction signal; and fault diagnosis is performed by comparing the correction signal with a fault library.

[0038] In specific implementation, due to the nonlinearity, hysteresis, fuzziness, time-varying and uncertainty related characteristics of power generation systems in daily operation, there are usually many different fault symptoms when electromechanical equipment in power plants fails. If only a single method is used, it is difficult to make an accurate judgment on the fault that has occurred, which will lead to a high probability of false alarms or missed reports when the system is performing fault detection. Therefore, this project proposes a temperature monitoring technology based on multi-source information fusion. By analyzing the composition of the multi-dimensional temperature measurement system of the hydropower station, the heating principle of electromechanical equipment, and the relationship between temperature data and equipment failure characteristics, the project adds relevant factors such as ambient temperature, load curve and equipment operating conditions to the original temperature data, and uses multiple methods such as time series and data-driven to predict the equipment temperature in multiple dimensions and levels. According to the predicted temperature value, the temperature difference and temperature rise value of the equipment in the future are calculated to achieve the purpose of real-time monitoring of equipment operation status data, trend prediction and danger warning. In order to solve the problem of different detection scales and spatial positions of various multi-source heterogeneous sensors of hydropower equipment, multi-source detection information preprocessing and time and space alignment were carried out to unify all detection information into the same time and space scale, and then the data of multiple monitoring sources were comprehensively analyzed, which solved the influence of subjective and objective factors of a single detection method on the diagnosis results and improved the accuracy of equipment fault diagnosis.

[0039] The speed and accuracy of fault diagnosis based on multi-source information fusion are much greater than that of fault diagnosis based on single data. The diagnostic technology based on multi-source information fusion can overcome many problems that cannot be solved by traditional fault diagnosis methods. Information fusion can be divided into data layer fusion, feature layer fusion and decision layer fusion. The project determines the means of information fusion at different levels by processing and analyzing the characteristics of equipment monitoring data in view of the differences in the operating characteristics of various electromechanical equipment in power plants. For example, the generator is diagnosed and decided by feature layer fusion. When the generator has a demagnetization fault or a rotor inter-turn short circuit fault, the temperature of the rotor will double or decrease. Therefore, voltage, current, casing temperature and rotor temperature are selected as feature quantities. The collected original signals are first analyzed and processed to retain enough important information. Then, the data is integrated by reducing the dimension through information fusion technology as the input of the neural network. Then, the feature information is fused by the fault diagnosis algorithm to accurately judge the fault and obtain the status evaluation of the generator.

[0040] In one embodiment, the signals are temporally and spatially registered to unify all signals into the same temporal and spatial scales.

[0041] In one embodiment, when the signal deviates from the standard threshold, the method includes:

[0042] A standard threshold is established based on the historical record values ​​of the signal during normal operation of the electromechanical equipment.

[0043] In one embodiment, the standard threshold is obtained by arithmetic average, moving average or weighted average.

[0044] In one embodiment, various signals of electromechanical equipment are collected in real time, including:

[0045] Collect the current and voltage of each circuit to be tested, and collect the temperature of each part of the electromechanical equipment;

[0046] The temperatures of various parts of the electromechanical equipment, including: generator collector ring excitation carbon brushes, generator stator, generator outlet connection, excitation AC knife switch, excitation DC knife switch, excitation cable on the low-voltage side of the excitation transformer, thrust external circulation pump motor, water-guided external circulation cooling oil pump motor, speed regulator oil pressure device oil pump motor, plant leakage drainage pump motor and maintenance drainage pump motor.

[0047] In the specific implementation, the excitation carbon brush of the generator collector ring is taken as an example. During the operation of the generator, the carbon brush is one of the important conductive components. It is used in conjunction with the slip ring to transfer the current from the generator shaft to the external circuit. There are many excitation carbon brushes in large hydroelectric generators. The carbon brushes are in a high-temperature working environment during operation. Due to factors such as friction loss of the carbon brushes and heat caused by current transmission, the temperature of the carbon brushes will gradually increase, which may cause the carbon brushes to catch fire or melt in severe cases. RFID temperature measurement tags are installed on the brush holders of the generator excitation carbon brushes. The tags collect the temperature of the carbon brushes in real time when the hydroelectric generator is running. The reader-writer collects all temperature data within the signal coverage range through wireless radio frequency signals. In addition, the reader-writer, as an edge computing unit, parses and preprocesses the temperature data, and finally interacts with the back-end server through the 5G private network of the power plant. The temperature analysis system deployed in the server processes and analyzes the temperature data to realize real-time online monitoring and intelligent analysis and diagnosis of the excitation carbon brush temperature.

[0048] In one embodiment, collecting the temperature of various locations of the electromechanical equipment includes:

[0049] Use ceramic packaged UHF RFID temperature measurement tags for temperature measurement;

[0050] The RFID temperature measurement tag and the reader communicate using the EPC Class 1Gen 2 wireless communication interface protocol based on UHF RFID.

[0051] In practice, the temperature measurement work in the electromechanical equipment of the hydropower plant faces a series of challenges. Some temperature measurement parts have current passing through them, which may interfere with the temperature measurement tags. At the same time, some temperature measurement parts are located inside the equipment, with small space, which increases the difficulty of installation and operation. In addition, most of the temperature measurement parts are made of metal, and the temperature is high in some places, which puts higher requirements on the temperature measurement technology.

[0052] To solve these problems, the project developed a temperature measurement tag based on RFID technology. The tag uses UHF RFID technology and ceramic packaging, and uses the backscattering principle to transmit temperature data through wireless communication with the reader. This passive design eliminates the need for battery power, reducing maintenance costs and complexity.

[0053] The project has taken the following measures to ensure that the temperature measurement tag can accurately measure temperature in complex environments such as current flow, small space, metal materials and high temperature, and improve the accuracy and reliability of temperature measurement. At the same time, continuous field testing and optimization work will further improve the performance and adaptability of the tag to meet the temperature measurement needs of different devices:

[0054] 1. Anti-metal design: Through special antenna design or adding anti-metal materials, the interference of metal on the temperature measurement tag is reduced. This design can ensure that the tag can work normally in a metal environment and provide accurate temperature measurement results.

[0055] 2. Miniaturized design: To address the problem of small internal space of the equipment, the label is miniaturized. The size of the label is reduced so that it can be easily installed in a limited space without affecting the normal operation of the equipment.

[0056] 3. High temperature resistance and insulation performance: Ceramic packaging is used, which can work stably in high temperature environment and has good insulation performance.

[0057] 4. Accurate temperature measurement: Use high-precision thermistors, calibrate and compensate them to ensure the reliability of the measurement results.

[0058] 5. Stable data transmission: A dedicated communication protocol is used to ensure stable data transmission and enhance signal anti-interference capabilities.

[0059] 6. Field testing and optimization: In actual applications, the RFID temperature measurement tag is field tested and optimized. According to different equipment and environmental conditions, the parameters and settings of the tag are adjusted to ensure that it can provide accurate temperature monitoring in various situations.

[0060] It consists of a front-end temperature measurement tag, a reader / writer (edge ​​computing unit), and a temperature analysis system (cloud) deployed on a cloud server. The front-end temperature measurement tag uses UHF RFID technology and ceramic packaging, and uses the backscattering principle. It does not require battery power and is easy to install. It uses edge-cloud collaborative technology to improve the processing efficiency and quality of temperature data, reduce network latency and bandwidth consumption, and realize real-time analysis and optimization of temperature data. The system has been installed and deployed in hydropower stations, achieving significant economic benefits and has promotion value.

[0061] In the identification system, RFID technology uses electromagnetic waves to read, write and communicate electronic tags. Ultra-high frequency radio frequency identification (UHF RFID) is used to design a passive wireless temperature measurement system, which has the characteristics of "passive" and "wireless". It has the advantages of safety, reliability, low cost, good real-time performance and easy maintenance.

[0062] The temperature measurement tag adopts UHF RFID technology. The temperature sensor in it does not need to be powered by a power module, but relies on UHFRFID induction power supply to obtain power. The RFID temperature measurement tag and the reader use the EPC Class 1Gen2V1.2 wireless communication interface protocol based on UHF RFID, which increases the transmission distance of the collected data, enhances reliability and increases throughput. The developed RFID temperature measurement tag adopts a ceramic anti-metal design. It is a temperature measurement tag specially designed for complex environments such as live electricity. It has the characteristics of passive wireless, wide temperature measurement range, high accuracy, long reading distance, small size, and easy installation. It is especially suitable for temperature measurement applications in various live electricity environments and can be easily applied to power, energy, special process production lines and other scenes. The passive RFID temperature measurement device can realize the temperature measurement of the surface and internal locations of the live equipment of the hydropower station. The temperature measurement range is -40℃~+130℃, the environmental temperature resistance range is -40℃~+225℃, the measurement accuracy is ±1℃, and the resolution is 0.1℃. It is highly economical, and the cost of one measurement point is less than 200 yuan.

[0063] In one embodiment, fault diagnosis is performed by comparing the correction signal with a fault library, including:

[0064] Collect the relevant current, voltage and temperature signals of a fault in the electromechanical equipment, correct them and form a fault feature vector, which is saved in the fault database;

[0065] When an electromechanical equipment fails, the relevant current, voltage and temperature signals are corrected to form a monitoring vector. By comparing the vector distance between the monitoring vector and the fault feature vector in the fault library, the fault feature vector with the closest vector distance is obtained as the fault diagnosis result, and on-site confirmation and troubleshooting are carried out.

[0066] like Figure 2 As shown, a hydropower plant electromechanical equipment fault monitoring system includes: a signal acquisition unit 201 and a fault detection unit 202;

[0067] The signal acquisition unit 201 is used to collect various signals of the electromechanical equipment in real time, including current, voltage and temperature;

[0068] The fault detection unit 202 is used to perform fault detection when the signal deviates from the standard threshold; to align the signal in time and space to obtain a correction signal; and to perform fault diagnosis by comparing the correction signal with the fault library.

[0069] like Figure 3 As shown, the present disclosure provides an electronic device, including a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302 and the memory 303 communicate with each other through the communication bus 304;

[0070] Memory 303, storing computer programs;

[0071] The processor 301 is configured to implement the above method when executing the computer program stored in the memory 303 .

[0072] The present disclosure provides a computer-readable storage medium storing a computer program, wherein the computer program implements the above method when executed by a processor.

[0073] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0074] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0075] In order to enable those skilled in the art to better understand the present disclosure, the principles of the present disclosure are described as follows in conjunction with the accompanying drawings:

[0076] RFID temperature measurement tags can be applied to the surfaces and internal locations of live and non-live equipment in hydropower stations. They have been installed and applied in the collector ring excitation carbon brushes, generator outlet connections, excitation AC knife switches, excitation DC knife switches, excitation cables on the low-voltage side of excitation transformers, thrust external circulation pump motors, water-guided external circulation cooling oil pump motors, speed regulator oil pressure device oil pump motors, plant leakage drainage pump motors, and maintenance drainage pump motors of units 1 to 5 of Datang Guanyinyan Hydropower Station.

[0077] Taking a certain project as an example, the intelligent monitoring platform for hydropower station equipment is deployed in the cloud, using a B / S architecture, and includes two parts: a backend management system and a frontend monitoring display. The backend management system is developed based on the Springboot framework, responsible for interacting with the reader and writer for temperature data, and storing the data in a MySQL relational database. At the same time, it implements the management of user permissions and system logs. The frontend monitoring display system uses the Vue.js framework to obtain real-time temperature data through a Web request backend interface, and presents it visually on the web page. It has been successfully applied to Chongqing Pengshui Hydropower Station and Datang Guanyinyan Hydropower Station. At this stage, the main functions implemented are: multi-label temperature acquisition and display module, single-label temperature analysis module, multi-label temperature analysis module, fault warning module, and system log module.

[0078] Cloud computing is the distribution of computing on a large number of distributed computers rather than local computers or remote servers, making the operation of enterprise data centers more similar to the Internet. Enterprises can allocate more resources to required applications and access computers and storage systems according to demand. There are many types of electromechanical equipment in hydropower stations, and each device needs to monitor a large number of temperature measurement points. The local computer or server of the traditional monitoring system may not provide enough computing and storage resources to process a large amount of temperature measurement data, resulting in system performance degradation or failure to operate normally. At the same time, the temperature data of different devices is difficult to store and manage centrally, and the data may be scattered on different devices, making it difficult to achieve effective data integration, sharing and analysis.

[0079] By adopting cloud computing technology, we provide a high-availability, elastically scalable computing resource pool, enable the migration of various business systems to the cloud architecture, meet the elastic computing needs of various business systems, build a "cloud" data center for intelligent hydropower stations, centrally store and uniformly calculate data, and realize data communication and sharing among various systems.

[0080] The developed IoT platform for monitoring faults of electromechanical equipment in hydropower plants can connect front-end sensing devices, controllers, cloud servers, etc. through wired or wireless networks to achieve fast, instant and efficient information collection, information communication, and real-time monitoring, improve the application level of monitoring data, and provide guarantees for correct and comprehensive statistics and decision-making analysis. At the same time, the platform provides functions such as data storage, event analysis and alarm, status monitoring, and data visualization. By controlling real-time status data, it can be integrated with management cloud applications and use big data platforms to conduct intelligent analysis and diagnosis to enhance data value.

[0081] In order to achieve elastic resource allocation, the project first evaluated the scale of temperature data at all measurement points to determine the resource requirements of different units, different equipment and different stages. Then, the resource monitoring tool is used to monitor resource usage in real time and formulate elastic scaling strategies. The platform can automatically increase or decrease computing resources according to resource requirements. At the same time, the cloud computing platform also performs operations such as resource pooling and load balancing to improve resource utilization and system performance. Finally, when the system is running, through continuous optimization and evaluation, the gap between actual resource usage and expected goals is compared, the effect of resource allocation strategy is evaluated, and the rationality and effectiveness of resource allocation are ensured. By implementing cloud computing elastic resource allocation, hydropower stations can achieve the effects of improving resource utilization efficiency, reducing costs, enhancing system reliability, and realizing more intelligent operation and management.

[0082] The project has achieved significant economic benefits, mainly in the following aspects:

[0083] (1) Reduce the losses caused by equipment downtime due to abnormal temperature rise:

[0084] The hydropower station has a total of 5 units, each with a capacity of 600MW. Units 1 to 5 are equipped with temperature monitoring systems. Each unit in Guanyinyan has 94 carbon brushes. Assume that the probability of abnormal temperature rise of each carbon brush in a year is 0.1%. When the collector ring carbon brush abnormality is not discovered in time, it will take 3 days to repair the single unit shutdown for maintenance. Based on the full load operation of the unit and the on-grid electricity price of 0.2 yuan / kWh, the application of this temperature measurement system has avoided losses of 4.536 million yuan so far. The specific calculation is as follows:

[0085] The probability of abnormal carbon brush temperature rise in a single unit is calculated as: p = 1-(1-0.1%) 94 =0.090

[0086] Calculate the losses caused by abnormal carbon brush heating in 5 units in one year:

[0087] 5×p×0.2×60×10 4 kw / h×3×24h=3888000;

[0088] 3888000÷12×14=4536000.

[0089] (2) Save operation and maintenance costs:

[0090] The system realizes automatic temperature monitoring of equipment such as excitation carbon brushes, generator outlet connection, excitation AC knife switch, excitation DC knife switch, excitation cable on the low-voltage side of excitation transformer, thrust external circulation pump motor, water-guided external circulation cooling oil pump motor, speed regulator oil pressure device oil pump motor, plant leakage drainage pump motor, and maintenance drainage pump motor. There is no need to send people to measure the temperature manually, which can save the cost of manual inspection of 4 people each year. If the labor cost of inspection personnel is 150,000 per year, it can save 600,000 yuan, an average of 50,000 yuan per month. The project has been applied in Guanyinyan for 14 months, saving 5×14=700,000 yuan in operation and maintenance costs.

[0091] In summary, the temperature measurement system was installed on the generator excitation carbon brush as the key part. As of now, it has been used for 14 months and the total cost savings are 5.236 million yuan.

[0092] Although the present disclosure has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A method for monitoring faults of electromechanical equipment in a hydropower plant, characterized in that: include: Real-time acquisition of various signals from electromechanical equipment, including current, voltage and temperature; When the signal deviates from the standard threshold, fault detection is performed; The signal is aligned in time and space to obtain a correction signal; fault diagnosis is performed by comparing the correction signal with the fault library.

2. A method for monitoring faults of electromechanical equipment in a hydropower plant according to claim 1, characterized in that: The signals are aligned in time and space to unify all signals into the same time and space scale.

3. A method for monitoring faults of electromechanical equipment in a hydropower plant according to claim 1, characterized in that: When the signal deviates from the standard threshold, including: A standard threshold is established based on the historical record values ​​of the signal during normal operation of the electromechanical equipment.

4. A method for monitoring faults of electromechanical equipment in a hydropower plant according to claim 3, characterized in that: Standard threshold, obtained by arithmetic mean, moving average or weighted average.

5. A method for monitoring faults of electromechanical equipment in a hydropower plant according to claim 1, characterized in that: Real-time acquisition of various signals from electromechanical equipment, including: Collect the current and voltage of each circuit to be tested, and collect the temperature of each part of the electromechanical equipment; The temperatures of various parts of the electromechanical equipment, including: generator collector ring excitation carbon brushes, generator stator, generator outlet connection, excitation AC knife switch, excitation DC knife switch, excitation cable on the low-voltage side of the excitation transformer, thrust external circulation pump motor, water-guided external circulation cooling oil pump motor, speed regulator oil pressure device oil pump motor, plant leakage drainage pump motor and maintenance drainage pump motor.

6. A method for monitoring faults of electromechanical equipment in a hydropower plant according to claim 5, characterized in that: Collect the temperature of various parts of electromechanical equipment, including: Use ceramic packaged UHF RFID temperature measurement tags for temperature measurement; The RFID temperature measurement tag and the reader communicate using the EPC Class 1Gen 2 wireless communication interface protocol based on UHF RFID.

7. A method for monitoring faults of electromechanical equipment in a hydropower plant according to claim 1, characterized in that: Fault diagnosis is performed by comparing the correction signal with the fault library, including: Collect the relevant current, voltage and temperature signals of a fault in the electromechanical equipment, correct them and form a fault feature vector, which is saved in the fault database; When an electromechanical equipment fails, the relevant current, voltage and temperature signals are corrected to form a monitoring vector. By comparing the vector distance between the monitoring vector and the fault feature vector in the fault library, the fault feature vector with the closest vector distance is obtained as the fault diagnosis result, and on-site confirmation and troubleshooting are carried out.

8. A hydropower plant electromechanical equipment fault monitoring system, characterized in that: include: Signal acquisition unit and fault detection unit; Signal acquisition unit, used to collect various signals of electromechanical equipment in real time, including current, voltage and temperature; The fault detection unit is used to detect faults when the signal deviates from the standard threshold; to align the signal in time and space to obtain a correction signal; and to perform fault diagnosis by comparing the correction signal with the fault library.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; a memory storing a computer program; The processor is used to implement a method for monitoring electromechanical equipment faults in a hydropower plant as described in any one of claims 1 to 7 when executing a computer program stored in a memory.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a method for monitoring faults of electromechanical equipment in a hydropower plant according to any one of claims 1 to 7 is implemented.

Images