Transformer partial discharge positioning method and system based on distributed intelligent sensors

Abstract

The present application discloses a transformer partial discharge positioning method and system based on distributed intelligent sensors, which relates to the field of transformer fault monitoring. The method includes: broadcasting positioning instructions to distributed intelligent sensors according to external triggers, when each intelligent sensor receives the positioning instruction and captures the rising edge of the pulse signal, collecting the transformer partial discharge amplitude of the set time, and saving the transformer partial discharge amplitude and trigger time collected at that time to the memory of each intelligent sensor; when the trigger time of all intelligent sensors is less than the set time, generating multiple partial discharge waveforms according to the transformer partial discharge amplitude in the memory of each intelligent sensor; determining the reference pulse time and non-reference pulse time based on all partial discharge waveforms, and using the Jacobian matrix to calculate the spatial coordinates of the discharge source according to the pulse time difference and the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor. The present application accurately locates the spatial coordinates of the discharge source inside the transformer.

Description

Technical Field

[0001] The present application relates to the technical field of transformer fault monitoring, and in particular to a transformer partial discharge positioning method and system based on distributed intelligent sensors. Background Art

[0002] The transformer is one of the most important equipment in the power transmission and transformation system, and its operating status directly affects the safe operation of the power grid. Statistics and analysis of actual transformer failures show that insulation failure is the main reason affecting the normal operation of the transformer, and partial discharge is an important factor in transformer insulation degradation. Therefore, it is of great significance to monitor the partial discharge inside the transformer and locate the specific location of the discharge source.

[0003] At present, the transformer comprehensive monitoring system and partial discharge source ultrasonic location method have been widely used in transformer internal fault monitoring. It mainly evaluates the internal fault of the transformer and determines the fault location by studying the signal characteristics of ultrasound and the time difference of ultrasonic signals collected by multiple ultrasonic sensors. However, due to the poor sensitivity of the existing monitoring method, the accuracy of the location result of the internal discharge source of the transformer is low. Summary of the invention

[0004] The purpose of this application is to provide a transformer partial discharge positioning method and system based on distributed intelligent sensors, which can accurately locate the spatial coordinates of the discharge source inside the transformer.

[0005] To achieve the above objectives, this application provides the following solutions.

[0006] In the first aspect, the present application provides a transformer partial discharge positioning method based on distributed intelligent sensors, and the transformer partial discharge positioning method based on distributed intelligent sensors includes: selecting a positioning method of a distributed intelligent sensor; the distributed intelligent sensor includes multiple intelligent sensors of the same or different types; the positioning method includes: a first positioning method and a second positioning method; the first positioning method is a joint positioning method of an ultra-wideband current intelligent sensor and a broad-spectrum mechanical wave intelligent sensor; the second positioning method is a joint positioning method of multiple broad-spectrum mechanical wave intelligent sensors; according to the positioning method, the installation position of the distributed intelligent sensor on the transformer is determined, and the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor in the distributed intelligent sensor are obtained; the distributed intelligent sensor is linked to form a network, and a pulse signal is continuously output to the distributed intelligent sensor; a positioning instruction is broadcast to the distributed intelligent sensor according to an external trigger; wherein, when When each intelligent sensor receives the positioning instruction and captures the rising edge of the pulse signal, it starts to collect the transformer partial discharge amplitude of the set time, and saves the transformer partial discharge amplitude and trigger time collected this time into the memory of each intelligent sensor; the trigger time is the time interval from the intelligent sensor receiving the positioning instruction to capturing the rising edge of the pulse signal; reads the transformer partial discharge amplitude and trigger time in the memory of each intelligent sensor, and when the trigger time of all intelligent sensors is less than the set time, generates multiple partial discharge waveforms according to the transformer partial discharge amplitude in the memory of each intelligent sensor; determines the reference pulse time and non-reference pulse time based on all partial discharge waveforms; uses the reference pulse time and the non-reference pulse time to calculate the pulse time difference, and based on the pulse time difference and the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor, uses the Jacobian matrix calculation to determine the spatial coordinates of the discharge source inside the transformer.

[0007] In a second aspect, the present application also provides a computer system, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the transformer partial discharge locating method based on distributed intelligent sensors.

[0008] According to the specific embodiments provided in this application, this application discloses the following technical effects.

[0009] This application adopts the method of distributed intelligent sensor monitoring to effectively determine the location of the discharge source inside the transformer. In order to ensure the accuracy of the data collected by each intelligent sensor, this application continuously sends a pulse signal to the distributed intelligent sensor, and uses the pulse signal as a synchronization signal. At the same time, it broadcasts the positioning instruction to the distributed intelligent sensor according to the external trigger. Each intelligent sensor starts to collect the transformer partial discharge amplitude only when it receives the positioning instruction and captures the rising edge of the pulse signal. This setting method can ensure that the distributed intelligent sensor collects the transformer partial discharge amplitude at the same time and generates multiple effective partial discharge waveforms. Finally, all partial discharge waveforms are analyzed to determine the reference pulse time and non-reference pulse time, and the pulse time difference and Jacobian matrix are calculated to obtain the precise spatial coordinates of the discharge source inside the transformer. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0011] Figure 1 A flow chart of a transformer partial discharge locating method based on distributed intelligent sensors provided in an embodiment of the present application.

[0012] Figure 2 This is a network diagram of the connection between the background host and each smart sensor provided in the embodiment of the present application.

[0013] Figure 3 This is a partial discharge waveform diagram obtained by the ultra-wideband current intelligent sensor provided in an embodiment of the present application.

[0014] Figure 4 This is a flowchart for implementing transformer partial discharge positioning according to an embodiment of the present application.

[0015] Figure 5 This is a diagram showing the effect of arranging smart sensors on a transformer provided in an embodiment of the present application.

[0016] Figure 6 A diagram of the internal structure of a computer system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0018] The purpose of this application is to provide a transformer partial discharge positioning method and system based on distributed intelligent sensors, which can accurately locate the spatial coordinates of the discharge source inside the transformer.

[0019] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0020] Example 1

[0021] This embodiment provides a transformer partial discharge positioning method based on distributed intelligent sensors, and the execution subject of the transformer partial discharge positioning method based on distributed intelligent sensors is a background host. Figure 1 As shown, the transformer partial discharge positioning method based on distributed intelligent sensors is specifically as follows.

[0022] Step S1: Select a positioning method for a distributed intelligent sensor; the distributed intelligent sensor includes multiple intelligent sensors of the same or different types; the positioning methods include: a first positioning method and a second positioning method; the first positioning method is a joint positioning method of an ultra-wideband current intelligent sensor and a broad-spectrum mechanical wave intelligent sensor; the second positioning method is a joint positioning method of multiple broad-spectrum mechanical wave intelligent sensors.

[0023] In this embodiment, step S1 specifically includes the following.

[0024] Step S11: When the distributed intelligent sensor includes one ultra-wideband current intelligent sensor and at least three broad-spectrum mechanical wave intelligent sensors, a first positioning mode is selected.

[0025] Step S12: When the distributed intelligent sensor includes at least four broad-spectrum mechanical wave intelligent sensors, a second positioning mode is selected.

[0026] The distributed intelligent sensors selected in this embodiment mainly include: ultra-wideband current intelligent sensors and broad-spectrum mechanical wave intelligent sensors. Among them, the ultra-wideband current intelligent sensor is used to collect the current signal on the grounding wire induced by the partial discharge inside the transformer at high speed, and the current signal is filtered and compressed by the built-in chip of the sensor, and then converted into partial discharge amplitude data, and stored in the sensor memory; the broad-spectrum mechanical wave intelligent sensor is used to collect the ultrasonic signal radiated by the partial discharge source inside the transformer at high speed, and the ultrasonic signal is filtered and compressed by the built-in chip of the sensor, and then converted into partial discharge amplitude data, and stored in the sensor memory.

[0027] Furthermore, both the ultra-wideband current intelligent sensor and the broad-spectrum mechanical wave intelligent sensor have two working modes, namely the single-cycle mode and the positioning mode. In the single-cycle mode: the intelligent sensor cyclically collects 20ms of partial discharge amplitude data, and compresses each 20ms of partial discharge amplitude data into 720 floating-point data, which are transmitted to the background host through the network; in the positioning mode: the intelligent sensor starts to collect 20ms of partial discharge amplitude data only after receiving the positioning instruction and obtaining the rising edge of the pulse signal. After the collection is completed, it enters the waiting state, and the 20ms partial discharge amplitude data is no longer compressed, but transmitted to the background host through the network.

[0028] In one example, the model of the ultra-wideband current intelligent sensor is TWSCT-D50. Specifically, the ultra-wideband current intelligent sensor includes: a frequency domain complementary current sensing unit, a frequency band signal conditioning unit, a synchronous variable time base high-speed acquisition processing unit, a frequency band data processing compensation unit, a multi-band data feature analysis unit, a communication module, a synchronization module and a power supply. Among them, the frequency domain complementary current sensing unit couples more than two current signals of different frequency bands, the frequency band signal conditioning unit respectively conditions and amplifies multiple frequency band current signals, the synchronous variable time base high-speed acquisition and processing unit converts the analog signals conditioned and amplified by multiple channels into digital signals, the frequency band data processing and compensation unit compensates, fuses, and frequency domain synthesizes the converted digital signals to obtain wide-band signals, the multi-band data feature analysis unit extracts feature information of different frequency bands for analysis, the synchronization module achieves time synchronization through mutual communication, the communication module transmits data and analysis and diagnosis results to the background host, and the power supply provides working power for the frequency band signal conditioning unit, the synchronous variable time base high-speed acquisition and processing unit, the frequency band data processing and compensation unit, the multi-band data feature analysis unit, the synchronization module, and the communication module.

[0029] In one example, the model of the broad-spectrum mechanical wave intelligent sensor is TWSV-20. Specifically, the broad-spectrum mechanical wave intelligent sensor includes: a MEMS audio sensor, a broadband composite vibrator, a multi-channel signal conditioning unit, a high-speed synchronous sampling unit, a frequency-band data processing and compensation unit, a multi-band data feature analysis unit, a communication module, a synchronization module and a power supply. Among them, the MEMS audio sensor obtains air sound signals, the broadband composite vibrator obtains signals of each frequency band of the monitored equipment, the multi-channel signal conditioning unit respectively conditions and amplifies the coupled signals, the high-speed synchronous sampling unit converts the conditioned and amplified analog signals into digital signals, the frequency-band data processing and compensation unit fuses and compensates the digital signals collected by the high-speed synchronous sampling unit to obtain a broadband signal, the multi-band data feature analysis unit respectively extracts the features of different frequency bands for analysis, the synchronization module achieves time synchronization through mutual communication, the communication module transmits the data and the results of analysis and diagnosis to the background host, and the power supply provides working power for the frequency-band signal conditioning unit, the high-speed synchronous sampling unit, the frequency-band data processing and compensation unit, the multi-band data feature analysis unit, the communication module, and the synchronization module.

[0030] Step S2: determining the installation position of the distributed intelligent sensor on the transformer according to the positioning method, and obtaining the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor in the distributed intelligent sensor.

[0031] In this embodiment, step S2 is specifically as follows.

[0032] Step S21: When the positioning mode is the first positioning mode, the ultra-wideband current intelligent sensor is installed on the transformer core or the clamp grounding wire, and multiple broad-spectrum mechanical wave intelligent sensors are respectively installed on different side walls of the transformer.

[0033] Step S22: When the positioning mode is the second positioning mode, a plurality of broad-spectrum mechanical wave intelligent sensors are respectively installed on different side walls of the transformer.

[0034] Furthermore, the ultra-wideband current intelligent sensor is a snap-on structure. Since the transformer generally has a core grounding wire or a clamp grounding wire, the ultra-wideband current intelligent sensor can be conveniently fixed on the transformer using the snap-on structure; the broad-spectrum mechanical wave intelligent sensor is a magnetic structure. Since the transformer is made of metal, the magnetic characteristics can be used to conveniently fix the broad-spectrum mechanical wave intelligent sensor on the side wall outside the transformer. In order to ensure the effectiveness of data collected by the broad-spectrum mechanical wave intelligent sensor, multiple broad-spectrum mechanical wave intelligent sensors are arranged on different side walls as much as possible to facilitate dispersed collection.

[0035] Furthermore, since the spatial coordinates of the ultra-wideband current intelligent sensor do not participate in the subsequent calculation of the spatial coordinates of the discharge source, only the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor participate in the subsequent calculation of the spatial coordinates of the discharge source, there is no need to obtain the spatial coordinates of the ultra-wideband current intelligent sensor. In addition, the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor are not directly obtained, but first a three-dimensional model of the transformer to be monitored is established on the background host, and then different distributed intelligent sensors are dragged to the corresponding positions on the three-dimensional model by dragging the mouse. This position is the position where each distributed intelligent sensor needs to be actually fixed to the transformer to be monitored. Since the three-dimensional model is established in a virtual three-dimensional space, the spatial coordinate changes generated by dragging the distributed intelligent sensor with the mouse are also virtual spatial coordinate changes. In order to obtain the real spatial coordinates of each distributed intelligent sensor, it is only necessary to map the virtual spatial coordinates to the real spatial coordinates.

[0036] Step S3: Linking with the distributed intelligent sensors to form a network and continuously outputting pulse signals to the distributed intelligent sensors.

[0037] like Figure 2 As shown, in this embodiment, the background host and each smart sensor are linked to the same switch. Since the distributed smart sensors in this embodiment only support POE power supply, the switch should also have POE power supply function. Among them, the IP of the background host needs to be set to the same network segment as each smart sensor. For example: if the network port IPv4 of the background host is set to 192.168.0.10, the IP of each smart sensor is set to 192.168.0.x (x is a number in the range of 0~255 except 10).

[0038] In addition, after outputting the pulse signal to the distributed intelligent sensor, each intelligent sensor needs to be debugged. Specifically, the background host sends a mode switching instruction to the distributed intelligent sensor through the TCP / IP protocol, switches all intelligent sensors to the single-cycle mode, and adjusts the frequency band and gain of each intelligent sensor in the single-cycle mode, so that the transformer partial discharge amplitude can be collected as a clear and stable transformer partial discharge signal, and the transformer partial discharge amplitude is preferably within the current gain amplitude range of 20%~80%. After the above adjustments are completed, the mode switching instruction is sent to the distributed intelligent sensor again through the TCP / IP protocol, switching all intelligent sensors to the positioning mode, and each intelligent sensor is ready to start collecting the transformer partial discharge amplitude.

[0039] In one example, the pulse signal is a 50 Hz pulse signal and is sent every 20 ms, with a pulse width of 2 ms.

[0040] Step S4: broadcast positioning instructions to distributed intelligent sensors according to external triggers; wherein, when each intelligent sensor receives the positioning instruction and captures the rising edge of the pulse signal, it starts to collect the transformer partial discharge amplitude for a set time, and saves the transformer partial discharge amplitude and trigger duration collected at that time into the memory of each intelligent sensor; the trigger duration is the time interval from the intelligent sensor receiving the positioning instruction to capturing the rising edge of the pulse signal.

[0041] In this embodiment, only when the user triggers the "Request Positioning" button, the background host will broadcast the positioning instruction to the distributed intelligent sensors using the UDP protocol. At the same time, the time interval from each intelligent sensor receiving the positioning instruction to capturing the rising edge of the pulse signal is the above triggering time.

[0042] In one example, the set time length for each intelligent sensor to collect the transformer partial discharge amplitude each time is 20ms. At the same time, only when the triggering time length is less than 20ms, the transformer partial discharge amplitude collected by each intelligent sensor at that time is valid.

[0043] Step S5: reading the transformer partial discharge amplitude and triggering duration in the memory of each intelligent sensor, and when the triggering duration of all intelligent sensors is less than the set duration, generating multiple partial discharge waveforms according to the transformer partial discharge amplitude in the memory of each intelligent sensor.

[0044] In this embodiment, when the triggering time of any smart sensor is greater than or equal to the set time, the transformer partial discharge amplitude collected by the distributed smart sensor is determined to be invalid data, and the above step S4 is re-executed. Due to the existence of multiple smart sensors, as long as the triggering time of one smart sensor is greater than or equal to the set time, the transformer partial discharge amplitude collected by the remaining smart sensors will have no reference value, and all smart sensors need to prepare for the next data collection again until the triggering time of all smart sensors is less than the set time, so that the corresponding partial discharge waveform can be generated according to the partial discharge amplitude collected by each smart sensor.

[0045] Step S6: Determine a reference pulse time and a non-reference pulse time based on all partial discharge waveforms.

[0046] In this embodiment, step S6 is specifically as follows.

[0047] Step S61: Determine the positioning method of the distributed intelligent sensor.

[0048] Step S62: When the positioning mode is the first positioning mode, the time when the maximum pulse amplitude in the local discharge waveform of the ultra-wideband current intelligent sensor in the distributed intelligent sensor appears is determined as the reference pulse time, and the time when the maximum pulse amplitude in the local discharge waveform of the remaining broad-spectrum mechanical wave intelligent sensors appears is determined as the non-reference pulse time.

[0049] Step S63: When the positioning mode is the second positioning mode, compare the time when the maximum pulse amplitude in the local discharge waveform of all broad-spectrum mechanical wave intelligent sensors in the distributed intelligent sensors, and determine the earliest time when the maximum pulse amplitude appears as the reference pulse time, and determine the remaining times when the maximum pulse amplitude appears as non-reference pulse times.

[0050] In one example, Figure 3 The partial discharge waveform obtained by an ultra-wideband current intelligent sensor has a horizontal axis range of 2203310ns~2206320ns. There are 7 pulse signals in the partial discharge waveform. Among them, because the maximum pulse amplitude appears at about 2204340ns on the horizontal axis, it is considered that the pulse at about 2204340ns is collected when the transformer partial discharge amplitude is the largest. By moving the cursor left and right, the time when the maximum pulse amplitude appears is accurately located, and this time is determined as the reference pulse time. If the distributed intelligent sensor is positioned in the first positioning method, there must be an ultra-wideband current intelligent sensor and multiple broad-spectrum mechanical wave intelligent sensors. Regardless of the type of intelligent sensor, it is necessary to refer to the above process to determine the time when the maximum pulse amplitude occurs, except that the ultra-wideband current intelligent sensor is used as the reference channel, and the time when the corresponding maximum pulse amplitude occurs is determined as the reference pulse time; if the distributed intelligent sensor is positioned in the second positioning method, there must be no ultra-wideband current intelligent sensor. In the case that all distributed intelligent sensors are broad-spectrum mechanical wave intelligent sensors, in addition to determining the time when the maximum pulse amplitude occurs with reference to the above process, it is also necessary to compare the order of each time, and use the broad-spectrum mechanical wave intelligent sensor that appears the largest pulse amplitude first as the reference channel, and determine the time when the corresponding maximum pulse amplitude occurs as the reference pulse time.

[0051] Step S7: Calculate the pulse time difference using the reference pulse time and the non-reference pulse time, and determine the spatial coordinates of the discharge source inside the transformer using Jacobian matrix calculation based on the pulse time difference and the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor.

[0052] In this embodiment, step S7 is specifically as follows.

[0053] Step S71: Calculate the difference between the non-reference pulse time and the reference pulse time to obtain the pulse time difference.

[0054] = - .

[0055] In the formula, is the nth pulse time difference (corresponding to the number of non-reference pulse times), is the reference pulse time, is the nth non-reference pulse time.

[0056] Step S72: Based on the pulse time difference, the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor, and the propagation speed of the ultrasonic wave in the transformer oil medium, a target equation and Jacobian matrix about the spatial coordinates of the discharge source inside the transformer are constructed. The target equation is as follows.

[0057] .

[0058] In the formula, is the nth target equation, (x, y, z) is the spatial coordinate of the discharge source inside the transformer, ( , , ) is the spatial coordinate of the nth broad-spectrum mechanical wave intelligent sensor, and v is the actual propagation speed of ultrasonic waves in the transformer oil medium (v = 1400 m / s, constant).

[0059] The Jacobian matrix is ​​as follows.

[0060] YKB= .

[0061] Where YKB is the Jacobian matrix.

[0062] Step S73: Calculate the spatial coordinates of the discharge source inside the transformer based on the target equation and the Jacobian matrix.

[0063] .

[0064] In the formula, is the calculated value of ultrasonic velocity. The error E between the calculated value of ultrasonic velocity and the actual propagation velocity of ultrasonic wave in transformer oil medium is used to judge whether the calculated spatial coordinates of the internal discharge source of the transformer are valid. That is, when E≤10%, the (x, y, z) calculated this time is considered valid. The calculation formula of error E is as follows.

[0065] .

[0066] In summary, based on the powerful data processing capability of distributed intelligent sensors, this embodiment strictly controls the synchronous acquisition of each intelligent sensor, establishes a matrix model of three-dimensional space coordinates and pulse time difference, and realizes the precise positioning of the discharge source inside the transformer.

[0067] Example 2

[0068] This embodiment provides a practical application scenario of a transformer partial discharge location method based on distributed intelligent sensors. Take a transformer with a length of 5 meters, a width of 2 meters, and a height of 3 meters as an example. Enter the length, width, and height information of the transformer in the 3D model. After clicking the Save button, follow the steps below to locate the transformer partial discharge. Figure 4 The fault location experiment was started according to the process.

[0069] The positioning method is selected according to the configuration of the intelligent sensor. This embodiment adopts a joint positioning method of one ultra-wideband current intelligent sensor and three broad-spectrum mechanical wave intelligent sensors.

[0070] After determining the positioning method, we began to install the smart sensors. Among them, the ultra-wideband current smart sensor is an open-type design, which is directly stuck on the transformer grounding wire. The other three broad-spectrum mechanical wave smart sensors are magnetically adsorbed and directly attached to different positions on the outer wall of the main transformer box, and are kept dispersed.

[0071] like Figure 5 As shown in the figure, with the center of the bottom surface of the transformer as the origin, a three-dimensional space coordinate system is generated according to the length, width and height of the transformer box. If you click the smart sensor model with the left mouse button and do not release the mouse, you can move the position of the smart sensor model in the three-dimensional space to keep it consistent with the installation position of the actual smart sensor. As the mouse is dragged, the virtual space coordinates of the smart sensor model also change, and the actual space coordinates of the smart sensor model can be obtained only through the mapping of the three-dimensional space and the actual space. In addition, since the space coordinates of the ultra-wideband current smart sensor do not participate in the subsequent positioning calculation, there is no need to drag its model to move.

[0072] Networking with each smart sensor. Because all smart sensors in this embodiment only support POE power supply, the switch has POE power supply function, and the background host IP needs to be set to the same network segment as each smart sensor.

[0073] Debugging smart sensors, which have single-cycle mode and positioning mode. Through the TCP / IP protocol, the corresponding mode switching can be performed by issuing mode switching instructions. First, switch each smart sensor to single-cycle mode to collect data, adjust the frequency band and gain of each smart sensor, and collect clear and stable transformer partial discharge signals.

[0074] Start positioning and switch each smart sensor to positioning mode.

[0075] A 50Hz pulse signal is sent as a synchronization signal, which is input to each smart sensor through the switch. After receiving the positioning command broadcast by the background host, each smart sensor enters the pre-collection state. When the smart sensor captures the rising edge of the next square wave, it starts to collect 20ms transformer partial discharge amplitude data and saves it in the memory of each smart sensor.

[0076] Read the transformer partial discharge amplitude and triggering duration data in the memory of each intelligent sensor.

[0077] When the trigger duration is less than 20ms, the data collected by the smart sensor is deemed valid, and a partial discharge waveform is generated based on the transformer partial discharge amplitude collected by the smart sensor.

[0078] Analyze all partial discharge waveforms to determine the reference pulse time and non-reference pulse time.

[0079] Firstly, the difference between the non-reference pulse time and the reference pulse time is calculated to obtain the pulse time difference.

[0080] = - .

[0081] Then, based on the pulse time difference, the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor, and the propagation speed of ultrasound in the transformer oil medium, the target equation and Jacobian matrix about the spatial coordinates of the discharge source inside the transformer are constructed.

[0082] .

[0083] YKB= .

[0084] Finally, the spatial coordinates of the discharge source inside the transformer are calculated based on the target equation and the Jacobian matrix.

[0085] .

[0086] .

[0087] When E≤10%, the spatial coordinates (x, y, z) of the internal discharge source of the transformer obtained by this calculation are deemed valid.

[0088] Example 3

[0089] This embodiment provides a computer system, which may be a server or a terminal, and its internal structure diagram may be as follows: Figure 6As shown. The computer system includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer system is used to provide computing and control capabilities. The memory of the computer system includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer system is used to store video tag processing data. The input / output interface of the computer system is used to exchange information between the processor and an external device. The communication interface of the computer system is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a transformer partial discharge positioning method based on a distributed intelligent sensor is implemented.

[0090] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer system to which the scheme of the present application is applied. The specific computer system may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0091] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0092] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0093] In summary, the present application mainly has the following advantages.

[0094] (1) Simple architecture. Compared with the traditional central server data collection, analysis, processing, and calculation architecture, the distributed intelligent sensor positioning method realizes a decentralized architecture. Each intelligent sensor independently collects, analyzes, and processes data, and the background host is used for control and calculation of positioning results.

[0095] (2) Easy installation. Each smart sensor and the background host are connected only through a switch, and the network structure is simple; the ultra-wideband current smart sensor adopts an open-type snap-on installation method, and the broad-spectrum mechanical wave smart sensor adopts a magnetic suction installation method, which is simple and easy to operate.

[0096] (3) Strong anti-interference ability. Based on the powerful data processing capability of smart sensors, noise shielding and processing are completed on the smart sensor side.

[0097] (4) High positioning accuracy. The ultra-wideband current intelligent sensor adopts a 100M sampling rate, and the ultrasonic channel of the broad-spectrum mechanical wave intelligent sensor adopts a 1M sampling rate. The high sampling rate ensures the accuracy of positioning, and the positioning accuracy can reach 1 cm.

[0098] (5) Accurate positioning algorithm. The Jacobian matrix is ​​composed of three-dimensional spatial coordinates and reference time difference. The higher the matrix dimension, the higher the calculation accuracy.

[0099] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0100] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A transformer partial discharge location method based on distributed intelligent sensors, characterized in that: The transformer partial discharge positioning method based on distributed intelligent sensors includes: Select a positioning method for a distributed intelligent sensor; the distributed intelligent sensor includes multiple intelligent sensors of the same or different types; the positioning method includes: a first positioning method and a second positioning method; the first positioning method is a joint positioning method of an ultra-wideband current intelligent sensor and a broad-spectrum mechanical wave intelligent sensor; the second positioning method is a joint positioning method of multiple broad-spectrum mechanical wave intelligent sensors; when the distributed intelligent sensor includes one ultra-wideband current intelligent sensor and at least three broad-spectrum mechanical wave intelligent sensors, select the first positioning method; when the distributed intelligent sensor includes at least four broad-spectrum mechanical wave intelligent sensors, select the second positioning method; Determine the installation position of the distributed intelligent sensor on the transformer according to the positioning method, and obtain the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor in the distributed intelligent sensor; Linking to the distributed intelligent sensor to form a network, and continuously outputting pulse signals to the distributed intelligent sensor; According to external triggering, a positioning instruction is broadcast to the distributed intelligent sensor; wherein, when each intelligent sensor receives the positioning instruction and captures the rising edge of the pulse signal, it starts to collect the transformer partial discharge amplitude of the set time, and saves the transformer partial discharge amplitude and triggering time collected at that time into the memory of each intelligent sensor; the triggering time is the time interval from the intelligent sensor receiving the positioning instruction to capturing the rising edge of the pulse signal; when the triggering time of any intelligent sensor is greater than or equal to the set time, it is determined that the transformer partial discharge amplitude collected by the distributed intelligent sensor at that time is invalid data, and the step of "broadcasting the positioning instruction to the distributed intelligent sensor according to external triggering" is re-executed; Read the transformer partial discharge amplitude and trigger duration in the memory of each intelligent sensor, and when the trigger duration of all intelligent sensors is less than the set duration, generate multiple partial discharge waveforms according to the transformer partial discharge amplitude in the memory of each intelligent sensor; Determining the reference pulse time and the non-reference pulse time based on all local discharge waveforms specifically includes: determining the positioning method of the distributed intelligent sensor; when the positioning method is the first positioning method, determining the time when the maximum pulse amplitude in the local discharge waveform of the ultra-wideband current intelligent sensor in the distributed intelligent sensor appears as the reference pulse time, and determining the time when the maximum pulse amplitude in the local discharge waveform of the remaining broad-spectrum mechanical wave intelligent sensors appears as the non-reference pulse time; when the positioning method is the second positioning method, comparing the time when the maximum pulse amplitude in the local discharge waveform of all broad-spectrum mechanical wave intelligent sensors in the distributed intelligent sensor appears, and determining the earliest time when the maximum pulse amplitude appears as the reference pulse time, and determining the remaining times when the maximum pulse amplitude appears as the non-reference pulse time; The pulse time difference is calculated using the reference pulse time and the non-reference pulse time, and the spatial coordinates of the discharge source inside the transformer are determined by Jacobian matrix calculation based on the pulse time difference and the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor, specifically including: calculating the difference between the non-reference pulse time and the reference pulse time to obtain the pulse time difference; constructing a target equation and Jacobian matrix about the spatial coordinates of the discharge source inside the transformer based on the pulse time difference, the spatial coordinates of the broad-spectrum mechanical wave intelligent sensor, and the propagation speed of ultrasonic waves in the transformer oil medium; calculating the spatial coordinates of the discharge source inside the transformer based on the target equation and the Jacobian matrix; the calculation formula for the spatial coordinates of the discharge source inside the transformer is: ； In the formula, is the nth target equation, YKB is the Jacobian matrix, (x, y, z) is the spatial coordinate of the discharge source inside the transformer, is the calculated value of ultrasonic velocity; The target equation is: ； In the formula, ( , , ) is the spatial coordinate of the nth broad-spectrum mechanical wave intelligent sensor, v is the actual propagation speed of ultrasonic waves in the transformer oil medium, is the nth pulse time difference; The Jacobian matrix is: YKB= 。 2. The transformer partial discharge location method based on distributed intelligent sensors according to claim 1 is characterized in that: Determining the installation position of the distributed intelligent sensor on the transformer according to the positioning method specifically includes: When the positioning method is the first positioning method, the ultra-wideband current intelligent sensor is installed on the transformer core or the clamp grounding wire, and multiple broad-spectrum mechanical wave intelligent sensors are installed on different side walls of the transformer respectively; When the positioning method is the second positioning method, a plurality of broad-spectrum mechanical wave intelligent sensors are respectively installed on different side walls of the transformer.

3. A computer system comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the transformer partial discharge locating method based on distributed intelligent sensors as described in any one of claims 1 to 2.

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