Multi-sensor array type equipment acoustic fingerprint adaptive acquisition device and method

Abstract

The invention relates to the field of data acquisition, in particular to a multi-sensor array type equipment acoustic fingerprint self-adaptive acquisition device and method, and the device comprises a track which is arranged around a transformer body and is provided with a plurality of acoustic sensors; the controller is responsible for receiving operation state information and environment parameters of the transformer equipment and acquiring the operation state information and the environment parameters through an interface of the transformer equipment monitoring system and the environment monitoring sensor; the controller is provided with a communication module, sends an instruction to the acoustic sensor array through the communication module, and adjusts the layout and parameters of the acoustic sensor; and the server is used for monitoring, analyzing and storing the acoustic fingerprint signals in real time. When the device is used, the layout and parameters of the acoustic sensor are automatically adjusted, so that accurate acquisition of acoustic fingerprint signals of the transformer equipment is realized. Meanwhile, the advanced signal fusion technology is utilized to improve the signal strength and reliability, and more accurate and more reliable data support is provided for state monitoring and fault diagnosis of transformer equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of data acquisition, and in particular to a device and method for adaptively acquiring acoustic fingerprints of multi-sensor array equipment. Background Art

[0002] With the continuous development of the power system, the safe and stable operation of transformer equipment, as a key equipment for power transmission and distribution, is of vital importance. Real-time monitoring of transformer equipment and timely detection of potential faults are of great significance to ensure the reliability of the power system. As a non-contact monitoring method, acoustic fingerprint monitoring has the advantages of not affecting the normal operation of transformer equipment and easy installation, and has gradually attracted attention.

[0003] At present, acoustic fingerprint monitoring of transformer equipment mainly uses a single sensor for signal collection. However, a single sensor has problems such as limited collection angle and susceptibility to environmental interference, making it difficult to fully and accurately obtain the acoustic fingerprint signal of the transformer equipment.

[0004] There are already some solutions that use multiple sensors to collect acoustic fingerprints of transformer equipment. These solutions usually fix multiple sensors at preset positions and cannot be adjusted according to changes in the operating status of the transformer equipment (such as load changes, local overheating, etc.) and environmental conditions (such as temperature, humidity, noise interference, etc.), resulting in inaccurate or incomplete acoustic fingerprint signals collected in some cases. Simple signal superposition or averaging processing methods fail to give full play to the advantages of multiple sensors, and the signal strength and reliability are limited. Summary of the invention

[0005] The purpose of the present invention is to address the problem in the background technology that the layout and parameters of multiple sensors cannot be automatically adjusted, and to propose a multi-sensor array device acoustic fingerprint adaptive acquisition device and method.

[0006] On the one hand, the present invention provides a multi-sensor array device acoustic fingerprint adaptive acquisition device, including a transformer body; and also including:

[0007] A track is arranged around the transformer body, a plurality of acoustic sensors are arranged on the track to form an acoustic sensor array, and a power device is arranged on the track to drive the acoustic sensor to rotate and adjust the angle and slide along the track to adjust the position;

[0008] The controller is responsible for receiving the transformer equipment operating status information and environmental parameters through the interface with the transformer equipment monitoring system and the environmental monitoring sensor; the controller analyzes the collected information and determines the current optimal sensor layout and parameters; the controller sets the communication module and sends instructions to the acoustic sensor array through the communication module to adjust the layout and parameters of the acoustic sensors;

[0009] and a server to achieve real-time monitoring, analysis and storage of acoustic fingerprint signals.

[0010] Preferably, the track is annular, and two tracks are provided. The two tracks are arranged around the transformer body and are perpendicular to each other, and an acoustic sensor array is deployed on each of the two annular tracks.

[0011] Preferably, a signal conditioning module is also included to process the acoustic fingerprint signal collected by the acoustic sensor to improve the signal quality and meet the requirements of subsequent processing, and transmit the processed signal to the controller.

[0012] Preferably, the acoustic sensor is adjusted according to the instructions transmitted by the communication module to achieve adaptive collection, and the adjustment methods include position adjustment, angle adjustment, sensitivity adjustment, filter parameter adjustment and gain adjustment.

[0013] Preferably, the server further analyzes and processes the received acoustic fingerprint signal to achieve status monitoring and fault diagnosis of the transformer equipment, using signal analysis technology and fault diagnosis algorithms.

[0014] Preferably, the acoustic fingerprint signals collected by multiple acoustic sensors are processed by signal fusion technology to improve the strength and reliability of the signals.

[0015] On the other hand, the present invention provides a collection method of an acoustic fingerprint adaptive collection device for a multi-sensor array device, comprising the following steps:

[0016] S1. Information collection: The acoustic sensor array collects acoustic data and obtains transformer equipment operating status information and environmental parameters through the interface with the transformer equipment monitoring system and the environmental monitoring sensor communication;

[0017] S2, analysis and decision-making: Analyze the acoustic data, transformer equipment operating status information and environmental parameters to determine the current optimal sensor layout and parameters;

[0018] S3, layout adjustment: issue adjustment instructions to the acoustic sensor, and the acoustic sensor performs layout and parameter adjustments.

[0019] Preferably, the method further comprises the following steps:

[0020] S4, effect verification: After adjusting the layout and parameters, the sensor continuously collects acoustic fingerprint signals and transmits the signals back to the controller. The controller conducts a preliminary analysis of the collected signals, evaluates the effect after adjustment, and determines whether the expected collection effect is achieved. If the effect is not ideal, it returns to the analysis and decision-making stage and readjusts the sensor layout and parameters until the collection requirements are met;

[0021] S5. Continuous monitoring and optimization: Continuously monitor the operating status of transformer equipment and changes in environmental parameters, regularly evaluate and adjust sensor layout and parameters, and continuously optimize preset algorithms and adjustment strategies based on long-term accumulated data analysis results to improve the accuracy and efficiency of sensor layout and parameter adjustment.

[0022] Compared with the prior art, the present invention has the following beneficial technical effects: by automatically adjusting the layout and parameters of the acoustic sensor, the accurate collection of the acoustic fingerprint signal of the transformer equipment is achieved. At the same time, the advanced signal fusion technology is used to improve the strength and reliability of the signal, providing more accurate and reliable data support for the condition monitoring and fault diagnosis of the transformer equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of the structure of an embodiment of the present invention;

[0024] Figure 2 The schematic diagram of track layout is shown in FIG.

[0025] Figure 3 Workflow diagram for sensor layout and parameter adjustment;

[0026] Figure 4 This is the workflow diagram for signal fusion using the Kalman filter method. DETAILED DESCRIPTION

[0027] Embodiment 1

[0028] like Figure 1 and Figure 2 As shown, the present invention proposes a multi-sensor array type equipment acoustic fingerprint adaptive acquisition device, including a transformer body; and also includes:

[0029] A track is arranged around the transformer body, a plurality of acoustic sensors are arranged on the track to form an acoustic sensor array, a power device is arranged on the track, and the power device drives the acoustic sensor to rotate and adjust the angle and slide and adjust the position along the track; in an optional embodiment, the track is annular, two tracks are arranged, the two tracks are arranged around the transformer body and are perpendicular to each other, and an acoustic sensor array is deployed on each of the two annular tracks;

[0030] The controller, as a core component, is responsible for receiving transformer equipment operating status information and environmental parameters, such as load current, voltage, temperature, etc., as well as environmental parameters such as temperature, humidity, noise level, etc. This information is obtained through the interface with the transformer equipment monitoring system and environmental monitoring sensors; the controller analyzes the collected information, extracts characteristic parameters such as frequency, amplitude, phase, etc., and determines the current optimal sensor layout and parameters. For example, when the load of the transformer equipment increases, it may be necessary to adjust the sensor closer to the transformer equipment body to better capture sound changes; when the environmental noise increases, it may be necessary to adjust the sensor parameters to improve anti-interference capabilities; the controller sets a communication module, sends instructions to the acoustic sensor array through the communication module, and adjusts the layout and parameters of the acoustic sensor; the acoustic sensor is adjusted according to the instructions transmitted by the communication module to achieve adaptive acquisition, and the adjustment methods include position adjustment, angle adjustment, sensitivity adjustment, filter parameter adjustment and gain adjustment;

[0031] The signal conditioning module amplifies, filters, and performs analog-to-digital conversion on the acoustic fingerprint signal collected by the acoustic sensor to improve the signal quality and meet the requirements of subsequent processing, and transmits the processed signal to the controller;

[0032] And the server realizes real-time monitoring, analysis and storage of acoustic fingerprint signals. The server further analyzes and processes the received acoustic fingerprint signals to realize status monitoring and fault diagnosis of transformer equipment, using signal analysis technology and fault diagnosis algorithms such as spectrum analysis, time-frequency analysis, pattern recognition, etc.

[0033] Embodiment 2

[0034] like Figure 4 As shown, the present invention proposes a multi-sensor array device acoustic fingerprint adaptive acquisition device. Compared with the first embodiment, this embodiment introduces in detail the processing method of the acoustic fingerprint signal.

[0035] The acoustic fingerprint signals collected by multiple acoustic sensors are processed by signal fusion technology to improve the strength and reliability of the signal. The specific fusion method is the Kalman filter method. You can also choose the appropriate signal fusion technology according to different application scenarios and requirements to achieve the best collection effect. The following are the steps for signal fusion using the Kalman filter method: S21. System modeling: First, model the transformer equipment acoustic fingerprint signal acquisition system. Determine the state variables of the system, which may include characteristic parameters such as amplitude, frequency, and phase of the acoustic fingerprint signal. Establish the state equation and observation equation of the system. The state equation describes the change law of the system state variables over time, and the observation equation describes the sensor's observation results of the system state; S22. Initialization: Set the initial state estimate. Determine the initial estimate of the system state variables based on prior knowledge or initial measurement values. Set the initial error covariance matrix. This matrix reflects the uncertainty of the initial state estimate; S23. State prediction: According to the system state equation, predict the system state at the next moment. That is, based on the state estimate at the current moment, predict the value of the state variable at the next moment. Calculate the prediction error covariance matrix. This matrix reflects the uncertainty of the predicted state and is obtained by updating the current error covariance matrix; S24, state update: When a new sensor measurement value arrives, the state is updated by combining the predicted value and the measured value. Calculate the Kalman gain. The Kalman gain is used to weigh the contribution of the predicted value and the measured value in the state update. Update the state estimate. The predicted value and the measured value are fused using the Kalman gain to obtain the updated state estimate. Update the error covariance matrix. According to the updated state estimate, the error covariance matrix is ​​updated to prepare for the next iteration; S25, loop and optimization: Repeat the prediction and update steps, continuously estimate and update the system state, and continuously optimize the state estimation results as new sensor measurements continue to arrive. According to the actual application scenario and requirements, adjust the parameters of the Kalman filter, such as the noise covariance, to achieve the best acquisition effect. Through the above steps, the Kalman filter method can effectively fuse the acoustic fingerprint signals of the transformer equipment collected by multiple sensors to improve the strength and reliability of the signal.

[0036] Embodiment 3

[0037] like Figure 3 As shown, the acquisition method based on the above-mentioned embodiment of the acoustic fingerprint adaptive acquisition device for a multi-sensor array device includes the following steps:

[0038] S1. Information collection: The acoustic sensor array collects acoustic data, and at the same time obtains transformer equipment operating status information and environmental parameters through the interface with the transformer equipment monitoring system and the environmental monitoring sensor communication; real-time acquisition of transformer equipment operating status information, including load current, voltage, temperature, etc., is achieved by installing corresponding sensors on the transformer equipment or exchanging data with the transformer equipment monitoring system. Environmental monitoring equipment is used to collect environmental parameters around the transformer equipment, such as temperature, humidity, noise level, etc., and multiple environmental sensors are arranged at different locations around the transformer equipment to fully understand the environmental conditions;

[0039] S2. Analysis and decision-making: Analyze the acoustic data, transformer equipment operating status information and environmental parameters to determine the current optimal sensor layout and parameters; specifically, the preset algorithm conducts a comprehensive analysis of the collected transformer equipment operating status information and environmental parameters, establishes a mathematical model, and associates different parameters with the sensor layout and parameter adjustment requirements. When the load of the transformer equipment increases, analyze its possible impact on the acoustic fingerprint to determine whether the sensor needs to be moved closer to the transformer equipment body to better capture sound changes; at the same time, consider the increase in environmental noise and determine whether the sensor parameters need to be adjusted to improve anti-interference capabilities. Based on the analysis results, determine the specific sensor layout adjustment direction and parameter adjustment value;

[0040] S3. Layout adjustment: Issue adjustment instructions to the acoustic sensor, and the acoustic sensor performs layout and parameter adjustments; specifically, position adjustment: If it is decided to move the sensor closer to the transformer equipment body, the controller sends a position adjustment instruction to the sensor array. The mechanical device electric guide rail in the sensor array moves the sensor to the specified position according to the instruction. For example, when the load current exceeds a certain threshold, move the sensor a certain distance closer to the transformer equipment. Angle adjustment: According to environmental factors (such as noise propagation direction, wind direction, etc.), adjust the angle of the sensor to better receive the acoustic fingerprint signal of the transformer equipment while reducing interference from environmental noise. The angle of the sensor can be adjusted by a motor-driven rotating device;

[0041] Parameter adjustments include the following:

[0042] Sensitivity adjustment: When the ambient noise increases, increasing the sensitivity of the sensor can enhance the ability to receive the acoustic fingerprint signal of the transformer equipment, but it may also increase the interference of the ambient noise. Therefore, it is necessary to optimize and adjust according to the specific situation. The controller sends a sensitivity adjustment instruction to the sensor, and the sensor adjusts the internal circuit parameters according to the instruction to achieve the change of sensitivity.

[0043] Filter parameter adjustment: Set appropriate filter parameters to remove environmental noise in a specific frequency range. For example, when the environmental noise is mainly concentrated in a certain frequency range, adjust the filter cutoff frequency so that the sensor attenuates the signal in that frequency range. The controller sends a filter parameter adjustment instruction to the sensor through the communication protocol, and the digital signal processing module inside the sensor sets the corresponding parameters.

[0044] Gain adjustment: According to the intensity change of the acoustic fingerprint signal of the transformer equipment, the gain of the sensor is appropriately increased or decreased. When the acoustic fingerprint signal is weak, the gain is increased to enhance the signal strength; when the signal is too strong, the gain is reduced to prevent signal saturation. The controller sends a gain adjustment instruction to the sensor, and the amplifier module of the sensor adjusts the gain value according to the instruction;

[0045] S4, effect verification: After adjusting the layout and parameters, the sensor continuously collects acoustic fingerprint signals and transmits the signals back to the controller. The controller performs a preliminary analysis on the collected signals and evaluates the effect after adjustment, for example, calculating the signal-to-noise ratio of the signal, analyzing the spectral characteristics of the signal, etc., to determine whether the expected collection effect has been achieved. If the effect is not ideal, return to the analysis and decision-making stage and readjust the sensor layout and parameters until the collection requirements are met;

[0046] S5. Continuous monitoring and optimization: Continuously monitor the operating status of transformer equipment and changes in environmental parameters, regularly evaluate and adjust sensor layout and parameters, and continuously optimize preset algorithms and adjustment strategies based on long-term accumulated data analysis results to improve the accuracy and efficiency of sensor layout and parameter adjustment.

[0047] In summary, when the present invention is used, the layout and parameters of the acoustic sensor are automatically adjusted to achieve accurate collection of the acoustic fingerprint signal of the transformer equipment. At the same time, advanced signal fusion technology is used to improve the strength and reliability of the signal, providing more accurate and reliable data support for the status monitoring and fault diagnosis of the transformer equipment. In order to improve stability and reliability, the following measures can also be implemented: select high-quality sensors and electronic components with good anti-interference ability and stability; perform strict electromagnetic compatibility design on the device to prevent the influence of electromagnetic interference on the collected signal; adopt redundant design, when a sensor fails, other sensors can still work normally to ensure the reliability of the collection device; regularly calibrate and maintain the collection device to ensure that its performance is always in the best condition.

[0048] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited thereto, and various changes can be made within the knowledge scope of technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A multi-sensor array device acoustic fingerprint adaptive acquisition device, comprising a transformer body; characterized in that: Also includes: A track is arranged around the transformer body, a plurality of acoustic sensors are arranged on the track to form an acoustic sensor array, and a power device is arranged on the track to drive the acoustic sensor to rotate and adjust the angle and slide along the track to adjust the position; The controller is responsible for receiving the transformer equipment operating status information and environmental parameters through the interface with the transformer equipment monitoring system and the environmental monitoring sensor; the controller analyzes the collected information and determines the current optimal sensor layout and parameters; the controller sets the communication module and sends instructions to the acoustic sensor array through the communication module to adjust the layout and parameters of the acoustic sensors; and a server to achieve real-time monitoring, analysis and storage of acoustic fingerprint signals.

2. The multi-sensor array device acoustic fingerprint adaptive acquisition device according to claim 1, characterized in that: The track is annular, and two tracks are arranged around the transformer body and are perpendicular to each other. An acoustic sensor array is deployed on each of the two annular tracks.

3. The multi-sensor array device acoustic fingerprint adaptive acquisition device according to claim 1, characterized in that: It also includes a signal conditioning module, which processes the acoustic fingerprint signal collected by the acoustic sensor to improve the signal quality and adapt to the requirements of subsequent processing, and transmits the processed signal to the controller.

4. The multi-sensor array device acoustic fingerprint adaptive acquisition device according to claim 1, characterized in that: The acoustic sensor is adjusted according to the instructions transmitted by the communication module to achieve adaptive collection. The adjustment methods include position adjustment, angle adjustment, sensitivity adjustment, filter parameter adjustment and gain adjustment.

5. The multi-sensor array device acoustic fingerprint adaptive acquisition device according to claim 1, characterized in that: The server further analyzes and processes the received acoustic fingerprint signal to realize the status monitoring and fault diagnosis of the transformer equipment, using signal analysis technology and fault diagnosis algorithm.

6. The multi-sensor array device acoustic fingerprint adaptive acquisition device according to claim 1, characterized in that: The acoustic fingerprint signals collected by multiple acoustic sensors are processed through signal fusion technology to improve the strength and reliability of the signal.

7. A collection method of the multi-sensor array device acoustic fingerprint adaptive collection device according to claim 1, characterized in that: The following steps are involved: S1. Information collection: The acoustic sensor array collects acoustic data and obtains transformer equipment operating status information and environmental parameters through the interface with the transformer equipment monitoring system and the environmental monitoring sensor communication; S2, analysis and decision-making: Analyze the acoustic data, transformer equipment operating status information and environmental parameters to determine the current optimal sensor layout and parameters; S3, layout adjustment: issue adjustment instructions to the acoustic sensor, and the acoustic sensor performs layout and parameter adjustments.

8. The collection method according to claim 7, characterized in that: The following steps are also included: S4, effect verification: After adjusting the layout and parameters, the sensor continuously collects acoustic fingerprint signals and transmits the signals back to the controller. The controller conducts a preliminary analysis of the collected signals, evaluates the effect after adjustment, and determines whether the expected collection effect is achieved. If the effect is not ideal, it returns to the analysis and decision-making stage and readjusts the sensor layout and parameters until the collection requirements are met; S5. Continuous monitoring and optimization: Continuously monitor the operating status of transformer equipment and changes in environmental parameters, regularly evaluate and adjust sensor layout and parameters, and continuously optimize preset algorithms and adjustment strategies based on long-term accumulated data analysis results to improve the accuracy and efficiency of sensor layout and parameter adjustment.

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