Comprehensive diagnosis method and system for ultrahigh-pressure converter station valve cooling system

Abstract

The invention relates to the technical field of ultrahigh-pressure converter station valve cooling system monitoring, in particular to an ultrahigh-pressure converter station valve cooling system comprehensive diagnosis method and system.The method comprises the steps that on-site sound signals are obtained and analyzed to generate a first analysis result, and a second analysis result is generated by combining meter image analysis; and the water leakage condition of the spraying pump is judged, a third analysis result is generated, and dynamic monitoring and deterioration trend analysis are conducted on abnormal points. According to the invention, the operation state and parameter abnormity of the valve cooling system can be rapidly identified through intelligent analysis of voiceprint features and meter images, a water leakage detection and abnormal point monitoring mechanism is introduced, the fault identification capability and the early warning level are improved, the monitoring efficiency and the intelligent degree are significantly improved, and the problem of low efficiency caused by dependence on manual operation in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of monitoring of valve cooling systems of super-high voltage converter stations, and particularly relates to a comprehensive diagnosis method and system for valve cooling systems of super-high voltage converter stations. BACKGROUND

[0002] With the rapid development of the power industry and the gradual advancement of smart grids, valve cooling systems of converter stations, as a key component of super-high voltage direct current transmission systems, have important significance for the stable operation of the entire power grid in terms of operational efficiency and safety. However, in the prior art, the monitoring and analysis of valve cooling systems mainly rely on the processing of data by workstations, which has certain limitations in terms of real-time performance and intelligence. For example, a large amount of manpower is required for manual transcription during data collection and analysis, which makes it difficult to fully meet the needs of efficient operation and maintenance. In addition, the traditional method has limited ability to identify abnormal states, which may affect the safety and stability of the system.

[0003] In summary, the prior art has the technical problem of low monitoring efficiency and insufficient intelligence level of valve cooling systems due to reliance on manual operation and traditional analysis methods. SUMMARY

[0004] The purpose of the present application is to provide a comprehensive diagnosis method and system for valve cooling systems of super-high voltage converter stations to solve the technical problem of low monitoring efficiency and insufficient intelligence level of valve cooling systems due to reliance on manual operation and traditional analysis methods in the prior art.

[0005] The present application provides a comprehensive diagnosis method for valve cooling systems of super-high voltage converter stations, which is realized by a comprehensive diagnosis system for valve cooling systems of super-high voltage converter stations. The comprehensive diagnosis method for valve cooling systems of super-high voltage converter stations includes: acquiring a field sound signal; if the field sound signal contains a preset sound wave characteristic quantity, analyzing the field sound signal to generate a first analysis result, which is used to indicate whether the valve cooling system is in a normal operating state; if the first analysis result indicates that the valve cooling system is operating abnormally, triggering an alarm mechanism based on the first analysis result; if the field sound signal contains the preset sound wave characteristic quantity, further acquiring an external meter image, analyzing the meter image to generate a second analysis result, which is used to indicate whether the operating parameters of the valve cooling system are within a normal range; if there is an abnormal operation of the main pump of the valve cooling system in the second analysis result, triggering an alarm mechanism based on the second analysis result.

[0006] In the method, the process of analyzing the on-site sound signal to generate a first analysis result comprises: extracting a voiceprint feature of the on-site sound signal, determining a frequency amplitude and a time length of the on-site sound signal; and determining that the valve cooling system is abnormal if the frequency amplitude or the time length is out of a set threshold range.

[0007] Further, the meter image of the valve cooling system comprises an indication of conductivity, pressure and water leakage of the valve cooling system; and correspondingly, the process of analyzing the meter image to generate a second analysis result comprises: determining whether an indicator of the main pump of the valve cooling system reaches a preset conductivity and pressure value; determining whether the flow rate is within a set first threshold interval; and generating the second analysis result based on the determination result.

[0008] In addition, the method further comprises analyzing a spray pump image of the valve cooling system to generate a third analysis result, and the specific process comprises: determining whether the spray pump has a water leakage phenomenon; and generating the third analysis result based on the determination result.

[0009] Further, the method further comprises the following steps: if it is detected that a meter value at any position of the valve cooling system on site is out of a set range, marking the position as an abnormal point; collecting meter values of the abnormal point at preset time intervals; performing difference calculation on the meter value collected at the current time and the value collected at the last time; and determining that the abnormal point has a deterioration trend if the difference is out of a set value range.

[0010] The application further provides a comprehensive diagnosis system for a valve cooling system of an ultrahigh-voltage converter station, which is used to execute the comprehensive diagnosis method for the valve cooling system of the ultrahigh-voltage converter station as described above, wherein the comprehensive diagnosis system for the valve cooling system of the ultrahigh-voltage converter station comprises: a signal acquisition module, which is used to acquire an on-site sound signal; a first analysis module, which is used to analyze the on-site sound signal to generate a first analysis result if the on-site sound signal contains a preset sound wave feature, the first analysis result being used to indicate whether a main pump of the valve cooling system is in a normal operation state; and an alarm mechanism being triggered based on the first analysis result if the first analysis result indicates that the main pump of the valve cooling system is abnormal; and a second analysis module, which is used to acquire a meter image of the valve cooling system if the on-site sound signal contains the preset sound wave feature, analyze the meter image to generate a second analysis result, and trigger the alarm mechanism based on the second analysis result if the second analysis result indicates that a parameter of the valve cooling system is abnormal, the second analysis result being used to indicate whether an operation parameter of the valve cooling system is in a normal range.

[0011] In the system, the first analysis module further comprises a voiceprint processing unit configured to extract voiceprint features of the field sound signal, determine a frequency amplitude and a time length of the field sound signal, and determine that the valve cooling system is abnormal if the frequency amplitude or the time length is out of a preset threshold range.

[0012] The second analysis module further comprises a meter image processing unit configured to determine whether an indicator of a main pump of the valve cooling system reaches preset conductivity and pressure values, determine whether the flow rate is within a preset first threshold range, and generate the second analysis result based on the determination results.

[0013] In addition, the system further comprises a spray pump image analysis module configured to determine whether the spray pump has a water leakage phenomenon, and generate the third analysis result based on the determination result.

[0014] Furthermore, the system further comprises an abnormal point monitoring module configured to mark a position as an abnormal point if a meter value at the position is detected to be out of a preset range, collect meter values of the abnormal point at preset time intervals, calculate a difference between a meter value collected at a current time and a meter value collected at a previous time, and determine that the abnormal point has a deterioration trend if the difference is out of a preset value range.

[0015] The one or more technical solutions provided by the present application have at least the following technical effects or advantages: the running state of the valve cooling system can be quickly and accurately identified by acquiring field sound signals and combining voiceprint feature analysis; whether the running parameters of the valve cooling system are within a normal range can be further verified by intelligent analysis of meter images; the identification ability of the system for potential faults is improved by introducing a spray pump water leakage detection mechanism; early warning of potential risks of the valve cooling system is realized by dynamic monitoring and deterioration trend analysis of abnormal points. These technical means work together to significantly improve the monitoring efficiency and intelligent level of the valve cooling system, and solve the low efficiency problem caused by relying on manual operation and traditional analysis methods in the prior art. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 FIG. 1 is a flowchart of a comprehensive diagnosis method for a valve cooling system of an ultrahigh voltage converter station in an embodiment of the present application, showing overall steps from sound signal acquisition to triggering of an alarm mechanism.

[0017] Figure 2 FIG. 2 is a detailed flowchart of a field sound signal analysis process in an embodiment of the present application, focusing on the extraction of voiceprint features and the determination logic of frequency amplitude and time length.

[0018] Figure 3 A flowchart of the meter image analysis process in an embodiment of the present application, including judgment steps for parameters such as conductivity, pressure, and flow.

[0019] Figure 4 A flowchart of the spray pump leakage detection process in an embodiment of the present application, showing the specific implementation of the leakage phenomenon judgment.

[0020] Figure 5 A flowchart of the abnormal point monitoring and deterioration trend analysis in an embodiment of the present application, detailing the processes of abnormal point marking, value collection, and difference calculation. DETAILED DESCRIPTION

[0021] The present application provides a comprehensive diagnosis method and system for valve cooling systems in EHV converter stations. By combining multi-dimensional data collection and analysis of on-site sound signal analysis, meter image processing, spray pump leakage detection, and abnormal point monitoring modules, comprehensive monitoring and intelligent diagnosis of valve cooling systems are achieved. The following describes the specific implementation of the present application in detail. Figure 1 to the accompanying drawings. Figure 5

[0022] In practical applications, the system of the present application mainly consists of a signal acquisition module, a first analysis module, a second analysis module, a spray pump image analysis module, and an abnormal point monitoring module. These modules work together through hardware devices and software algorithms to complete the comprehensive diagnosis task of the valve cooling system. First, the signal acquisition module is responsible for acquiring sound signals from the valve cooling system on site in the EHV converter station. This module usually includes a high-sensitivity microphone array and a signal acquisition circuit, which can capture various acoustic characteristic quantities generated during the operation of the valve cooling system. These sound signals may come from the running state of components such as the main pump, pipeline vibration, or cooling liquid flow. The signal acquisition module transmits the collected sound signals to the first analysis module for further processing.

[0023] The core function of the first analysis module is to analyze the on-site sound signals and generate a first analysis result. For example, the module can use advanced signal processing algorithms to identify and extract specific acoustic features from the sound signals. These features may include frequency components, amplitude variations, or other characteristics that are indicative of the health and performance of the valve cooling system. The first analysis result may include information such as the presence of abnormal sounds, the type of abnormal sound, or the severity of the abnormal sound. Figure 2 ​As shown, the module includes a voiceprint processing unit for extracting the voiceprint features of the sound signal and determining its frequency amplitude and duration. Specifically, the voiceprint processing unit first pre-processes the received sound signal, including filtering and de-noising and frame division operations, to ensure the accuracy of subsequent analysis. Subsequently, the voiceprint processing unit converts the time-domain signal into a frequency-domain signal through Fourier transform and extracts the main frequency components of the signal and their corresponding amplitudes. At the same time, by measuring the duration of the signal, the time length information of the sound signal is obtained. After completing the feature extraction, the voiceprint processing unit compares the frequency amplitude and duration with the preset threshold range. If the frequency amplitude or duration exceeds the set range, it is determined that the valve cooling system is running abnormally, and the alarm mechanism is triggered. For example, when the main pump produces abnormally high frequency noise or long duration abnormal noise, the first analysis module will immediately generate an alarm signal and notify the operation and maintenance personnel through the alarm device.

[0024] If the analysis result of the first analysis module shows that the valve cooling system is not abnormal, the system enters a deeper level of diagnosis process. At this time, the signal acquisition module further acquires the external meter image and transmits it to the second analysis module. The second analysis module is responsible for analyzing the meter image and generating a second analysis result. As shown, Figure 3 As shown, the meter image usually includes key parameters such as conductivity indicator, pressure indicator and flow indicator. The meter image processing unit in the second analysis module first pre-processes the received image, including grayscale, binary and edge detection operations, to accurately extract the meter readings. Subsequently, the meter image processing unit analyzes each parameter according to the preset judgment logic. For example, for the conductivity and pressure values, the processing unit will determine whether they reach the preset standard value; for the flow parameter, the processing unit will determine whether it is within the set first threshold interval. If any parameter does not meet the requirements, a second analysis result is generated and the alarm mechanism is triggered. For example, when the conductivity value exceeds the normal range or the flow is below the minimum threshold, the system will issue a corresponding alarm prompt.

[0025] After completing the meter image analysis, the system further calls the spray pump image analysis module to detect the running state of the spray pump. As shown, Figure 4 As shown, the spray pump image analysis module acquires real-time images of the spray pump through the camera and uses image recognition algorithms to determine whether there is water leakage. Specifically, the module first pre-processes the image, including background segmentation and target area extraction, to highlight the key parts of the spray pump. Subsequently, the module compares the changes between the historical image and the current image to determine whether there are signs of liquid leakage. For example, when there are abnormal water stains or wet areas in the image, the module will generate a third analysis result and trigger the alarm mechanism. This process not only improves the system's ability to identify potential faults, but also provides more comprehensive fault information for operation and maintenance personnel.

[0026] In addition, in order to realize early warning of potential risks of the valve cooling system, the present application also introduces an abnormal point monitoring module. As shown in Figure 5 the workflow of the abnormal point monitoring module includes three steps of abnormal point marking, value collection and difference calculation. First, the module judges whether there is a situation of exceeding the set range by monitoring the meter value of each position of the valve cooling system in real time. Once an abnormality is found, the position is marked as an abnormal point. Subsequently, the module collects the meter value of the abnormal point continuously according to the preset time interval. After each collection is completed, the module calculates the difference between the value at the current time and the value at the last time. If the difference exceeds the set value range, it is determined that the abnormal point has a deterioration trend, and a corresponding alarm signal is generated. For example, when the value of a pressure gauge at a certain position continuously decreases and the decrease rate exceeds the threshold, the system will determine that there is a risk of serious leakage at the position, and timely notify the operation and maintenance personnel to take measures.

[0027] In the cooperative work of the above-mentioned various modules, the signal acquisition module, as the starting point of data collection, undertakes the task of acquiring sound signals and image data. The first analysis module and the second analysis module analyze the running state of the valve cooling system from two dimensions of sound signals and meter images respectively, forming a multi-level diagnosis system. The spray pump image analysis module focuses on the leakage detection of the spray pump, further improving the fault recognition ability of the system. Finally, the abnormal point monitoring module realizes early warning of potential risks through dynamic monitoring and deterioration trend analysis of abnormal points. These modules are closely coordinated through data transmission and logical judgment, and together form a complete valve cooling system comprehensive diagnosis system.

[0028] In actual application scenarios, the technical solution of the present application can be widely applied in the daily operation and maintenance work of the ultra-high voltage converter station. For example, in a certain ultra-high voltage converter station, the operation and maintenance personnel can monitor the running state of the valve cooling system in real time by deploying the comprehensive diagnosis system of the present application. When the system detects that the main pump is running abnormally or the electrical conductivity is out of standard, it will immediately issue an alarm signal to remind the operation and maintenance personnel to check and maintain. At the same time, through dynamic monitoring of abnormal points, the system can discover potential risk points in advance, avoiding equipment damage or shutdown accidents caused by fault expansion. This intelligent monitoring method not only significantly improves the monitoring efficiency of the valve cooling system, but also greatly reduces the workload of manual operation, providing a strong guarantee for the safe and stable operation of the ultra-high voltage converter station.

[0029] In order to better enable relevant persons in the art to fully understand and implement the present application, the specific implementation principles of the present application are further supplemented in the following in combination with a specific application scenario.

[0030] In the actual operation and maintenance process of the ultra-high voltage converter station, the comprehensive diagnosis system of the application gradually completes the comprehensive monitoring and intelligent diagnosis of the valve cooling system through the cooperative work of multiple modules. First, the signal acquisition module, as the core component of data acquisition, is deployed near the main pump, pipeline and cooling liquid flow area of the valve cooling system, and uses a high-sensitivity microphone array to capture the sound signals generated during operation. These sound signals may come from the mechanical vibration of the main pump, the liquid flow in the pipeline or the abnormal noise of the cooling system. The signal acquisition module transmits the collected sound signals to the first analysis module for processing. The voiceprint processing unit in the first analysis module pre-processes the received sound signals, including filtering and denoising to remove environmental noise interference, and frame operation to improve signal analysis accuracy. Subsequently, the voiceprint processing unit converts the time domain signal into a frequency domain signal through Fourier transform, and extracts the main frequency component and its corresponding amplitude information of the signal. At the same time, by measuring the duration of the signal, its time length characteristics are obtained. If the extracted frequency amplitude or time length exceeds the preset threshold range, it is determined that the valve cooling system has an abnormal operating state, and an alarm mechanism is triggered. For example, when the main pump generates high-frequency noise and the duration exceeds the set threshold, the first analysis module will generate an alarm signal and notify the operation and maintenance personnel through the alarm device.

[0031] If the analysis result of the first analysis module shows that the valve cooling system does not have an abnormality, the system enters a deeper diagnosis process. At this time, the signal acquisition module further acquires the external meter image and transmits it to the second analysis module for processing. The meter image processing unit in the second analysis module first pre-processes the received image, including grayscale to simplify image information, binarization to highlight key features, and edge detection to accurately locate the meter reading. Subsequently, the meter image processing unit analyzes the conductivity, pressure and flow parameters one by one. For conductivity and pressure values, the processing unit determines whether they meet the preset standard values; for flow parameters, the processing unit determines whether they are within the set first threshold interval. If any parameter does not meet the requirements, a second analysis result is generated and an alarm mechanism is triggered. For example, when the conductivity value exceeds the normal range or the flow is below the minimum threshold, the system will issue a corresponding alarm prompt to remind the operation and maintenance personnel to check and maintain.

[0032] After completing the meter image analysis, the system further calls the spray pump image analysis module to detect the running state of the spray pump. The spray pump image analysis module collects real-time images of the spray pump through the camera and uses image recognition algorithms for preprocessing, including background segmentation to remove irrelevant information and target area extraction to highlight the key parts of the spray pump. Subsequently, the module compares the changes between historical images and current images to determine if there are signs of liquid leakage. For example, when abnormal water stains or wet areas appear in the image, the module generates a third analysis result and triggers the alarm mechanism. This process not only improves the system's ability to identify potential faults, but also provides more intuitive fault information for maintenance personnel, facilitating quick problem location.

[0033] In addition, to achieve early warning of potential risks in the valve cooling system, the present application introduces an abnormal point monitoring module. The module monitors the meter values at each position of the valve cooling system in real time to determine if they are outside the set range. Once an abnormality is found, the position is marked as an abnormal point, and the module continuously collects meter values at the abnormal point at preset time intervals. After each collection is complete, the module calculates the difference between the current time value and the previous time value. If the difference is outside the set value range, it is determined that the abnormal point has a deterioration trend, and an appropriate alarm signal is generated. For example, when the value of a pressure gauge at a certain location continuously decreases and the decrease rate exceeds the threshold, the system determines that there may be a serious leakage risk at that location and promptly notifies the maintenance personnel to take appropriate measures. This dynamic monitoring and deterioration trend analysis method can effectively prevent equipment damage or shutdown accidents caused by fault expansion.

[0034] The above-mentioned modules work closely together in actual application to form a complete valve cooling system comprehensive diagnosis system. The signal acquisition module serves as the starting point for data collection and is responsible for acquiring sound signals and image data from the field; the first analysis module and the second analysis module analyze the running state of the valve cooling system from two dimensions of sound signals and meter images, respectively, forming a multi-level diagnosis system; the spray pump image analysis module focuses on water leakage detection of the spray pump, further improving the system's fault recognition ability; the abnormal point monitoring module realizes early warning of potential risks through dynamic monitoring and deterioration trend analysis of abnormal points. These modules work closely together through data transmission and logical judgment to ensure efficient operation of the system.

[0035] In practical application scenarios, the technical solutions of the present application can be widely applied in the daily operation and maintenance work of the ultra-high voltage converter station. For example, in a certain ultra-high voltage converter station, the operation and maintenance personnel can monitor the running state of the valve cooling system in real time by deploying the comprehensive diagnostic system of the present application. When the system detects that the main pump is running abnormally or the electrical conductivity is out of standard, it will immediately issue an alarm signal to remind the operation and maintenance personnel to check and maintain. At the same time, through dynamic monitoring of abnormal points, the system can discover potential risk points in advance to avoid equipment damage or shutdown accidents caused by fault expansion. This intelligent monitoring method not only significantly improves the monitoring efficiency of the valve cooling system, but also greatly reduces the workload of manual operation, providing a strong guarantee for the safe and stable operation of the ultra-high voltage converter station.

[0036] It should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0037] Although embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A comprehensive diagnosis method for a valve cooling system of an ultra-high voltage converter station, characterized in that, The method comprises the following steps: acquiring a field sound signal; if the field sound signal contains a preset sound wave characteristic quantity, analyzing the field sound signal to generate a first analysis result, the first analysis result being used to indicate whether the valve cooling system is in a normal operation state; if the first analysis result indicates that the valve cooling system is abnormally operated, triggering an alarm mechanism based on the first analysis result; if the field sound signal contains the preset sound wave characteristic quantity, further acquiring an external meter image, analyzing the meter image to generate a second analysis result, the second analysis result being used to indicate whether an operation parameter of the valve cooling system is in a normal range; if there is an abnormal operation of a main pump of the valve cooling system in the second analysis result, triggering the alarm mechanism based on the second analysis result.

2. The ultra-high voltage converter station valve cooling system comprehensive diagnosis method of claim 1, wherein, The process of analyzing the field sound signal to generate the first analysis result comprises the following steps: extracting a voiceprint feature of the field sound signal, and determining a frequency amplitude and a time length of the field sound signal; if the frequency amplitude or the time length exceeds a set threshold range, determining that the valve cooling system is abnormally operated.

3. The method of claim 1, wherein the method further comprises: The meter image of the valve cooling system comprises an indicator of an electric conductivity, a pressure and a water leakage condition of the valve cooling system. The process of analyzing the meter image to generate the second analysis result comprises the following steps: judging whether an indicator plate of the main pump of the valve cooling system reaches a preset electric conductivity and pressure value; judging whether the flow rate is in a set first threshold interval; generating the second analysis result based on the judging result.

4. The method of claim 1, wherein the method further comprises: The method further comprises the following steps: if it is detected that a meter value at any position of the valve cooling system field exceeds a set range, marking the position as an abnormal point; collecting the meter value of the abnormal point at a preset time interval; 5. The method of claim 1, wherein the method further comprises: performing difference calculation on the meter value collected at a current time and a meter value collected at a previous time; if the difference exceeds a set value range, determining that the abnormal point has a deterioration trend. The method comprises the following steps: a signal acquisition module, which is used to acquire a field sound signal; a first analysis module, which is used to analyze the field sound signal to generate a first analysis result if the field sound signal contains a preset sound wave characteristic quantity, the first analysis result being used to indicate whether a main pump of a valve cooling system is in a normal operation state; if the first analysis result indicates that the main pump of the valve cooling system is abnormally operated, triggering an alarm mechanism based on the first analysis result; 6. An ultra-high voltage converter station valve cooling system comprehensive diagnosis system, characterized in that, a second analysis module, which is used to acquire a meter image of the valve cooling system if the field sound signal contains the preset sound wave characteristic quantity, and analyze the meter image to generate a second analysis result, the second analysis result being used to indicate whether an operation parameter of the valve cooling system is in a normal range; if there is an abnormal parameter of the valve cooling system in the second analysis result, triggering the alarm mechanism based on the second analysis result. The first analysis module further comprises the following steps: ​ ​ 7. The ultra-high voltage converter station valve cooling system comprehensive diagnosis system of claim 6, wherein, ​ The voiceprint processing unit is configured to extract voiceprint features of the live sound signal, determine a frequency amplitude and a time length of the live sound signal, and determine that the valve cooling system is operating abnormally if the frequency amplitude or the time length exceeds a preset threshold range.

8. The comprehensive diagnostic system for the valve cooling system of an EHV converter station as claimed in claim 6, wherein, The second analysis module further includes: The meter image processing unit is configured to determine whether an indicator of a main pump of the valve cooling system reaches a preset electrical conductivity and pressure value, determine whether the flow rate is within a preset first threshold range, and generate the second analysis result based on the determination results.

9. The comprehensive diagnostic system for the valve cooling system of an EHV converter station as claimed in claim 6, wherein, Further includes: The spray pump image analysis module is configured to determine whether the spray pump has a water leakage phenomenon. The third analysis result is generated based on the determination result.

10. The comprehensive diagnostic system for the valve cooling system of an EHV converter station as claimed in claim 6, wherein, Further includes: The abnormal point monitoring module is configured to mark a position as an abnormal point if a meter value at the position is detected to be out of a preset range. The meter value of the abnormal point is collected at preset time intervals. The meter value collected at a current time is subtracted from a meter value collected at a previous time. If the difference exceeds a preset value range, it is determined that the abnormal point has a deterioration trend.

Images