CN-122017429-A - Intelligent state detection system for dry-type transformer

CN122017429ACN 122017429 ACN122017429 ACN 122017429ACN-122017429-A

Abstract

The invention relates to the technical field of transformer detection, in particular to an intelligent state detection system for a dry-type transformer, which comprises a data acquisition module, a load type determination module, a potential fault positioning module, a detection path planning module and a path adjustment module, wherein the data acquisition module is used for acquiring environmental parameters and operation parameters of the dry-type transformer, the load type determination module is used for determining the operation load type of the dry-type transformer based on the operation parameters, the potential fault positioning module is used for responding to the low load type and positioning the potential fault position based on the operation parameters, the detection path planning module is used for determining a detection path based on the potential fault position and a three-dimensional structure model, and the path adjustment module is used for determining a fault influence area corresponding to the detection position based on a fault detection result and adjusting a subsequent detection path based on the fault influence area. According to the method, through the technical means of combining the vibration distortion analysis of the iron core with the dynamic path planning and adjustment under the low-load working condition, the beneficial effects of accurately positioning potential faults and adaptively optimizing the detection path in the low-load period are realized.

Inventors

HE FENG
WANG ZHIHUA
TONG YU
SHEN ZHENGQING
TANG YINFEI
ZHOU ZHIGUO
LIU AIPING
ZHANG XINXIN
KONG LINGYANG
WANG HAO

Assignees

浙江通致电气有限公司

Dates

Publication Date: 20260512
Application Date: 20260310

Claims (10)

1. An intelligent state detection system for a dry-type transformer, comprising: The data acquisition module is used for acquiring the environmental parameters and the operation parameters of the dry-type transformer; a load type determining module connected with the data module for determining an operation load type of the dry-type transformer based on the operation parameter, wherein the load type comprises a high load type and a low load type; The potential fault positioning module is respectively connected with the data acquisition module and the load type determining module and is used for responding to the condition that the operation load type of the dry-type transformer is a low load type, acquiring a vibration signal of an iron core in the dry-type transformer from the operation parameter, determining a vibration distortion index of the dry-type transformer based on the vibration signal and positioning a potential fault position of the dry-type transformer based on the vibration distortion index; A detection path planning module connected with the potential fault location module for determining a detection path for the fault location based on the potential fault location of the dry transformer and a three-dimensional structural model of the dry transformer; The fault detection module is connected with the detection path planning module and used for carrying out fault detection on the dry-type transformer based on the detection path to obtain a fault detection result; And the path adjustment module is respectively connected with the detection path planning module and the fault detection module, and is used for determining a fault influence area of a detection position corresponding to the fault detection result based on the fault detection result and adjusting a subsequent detection path of the fault detection module based on the fault influence area.
2. The intelligent state detection system for a dry-type transformer of claim 1, wherein the load type determination module determines an operating load type of the dry-type transformer based on the operating parameter, wherein, The load type determining module determines a real-time load of the dry-type transformer based on the operating parameter; If the real-time load is greater than or equal to a preset real-time load, the load type determining module determines that the operation load type of the dry-type transformer is a high load type; and if the real-time load is smaller than the preset real-time load, the load type determining module determines that the operation load type of the dry-type transformer is a low load type.
3. The intelligent state detection system for a dry-type transformer of claim 1, wherein the latent fault localization module determines a vibration distortion index of the dry-type transformer based on the vibration signal, wherein, The potential fault locating module performs spectrum analysis on the vibration signal and extracts fundamental frequency component amplitude and harmonic component amplitude; the vibration distortion index is determined based on a ratio of the harmonic component amplitude to the fundamental component amplitude.
4. The intelligent state detection system for a dry transformer of claim 1, wherein the latent fault location module locates a latent fault location of the dry transformer based on the vibration distortion index, wherein, And if the vibration distortion index is greater than or equal to a preset vibration distortion index, the potential fault locating module determines that a potential fault exists in the dry-type transformer, and determines the potential fault position based on the acquisition position of the vibration signal.
5. The intelligent state detection system for a dry-type transformer according to claim 4, wherein the preset vibration distortion index is determined according to statistical characteristics of historical vibration signals of the dry-type transformer in a normal operation state.
6. The intelligent state detection system for a dry transformer according to claim 1, wherein the detection path planning module determines a detection path for a potential fault location of the dry transformer based on the fault location and a three-dimensional structural model of the dry transformer, wherein, The detection path planning module performs space accessibility analysis on the potential fault position based on the three-dimensional structure model, and determines at least one candidate observation point; the detection path planning module plans an initial moving path from the current position to the candidate observation point by taking the path length as an optimization target; The detection path planning module also optimizes the initial movement path based on detection efficiency constraint conditions to determine a final detection path.
7. The intelligent state detection system for a dry-type transformer according to claim 1, wherein the path adjustment module determines a failure influence area of the failure detection result corresponding to a detection position based on the failure detection result, wherein, A fault propagation mechanism model is prestored in the path adjustment module, and the fault propagation mechanism model comprises fault propagation rules and influence range determination rules corresponding to different fault types; The path adjustment module extracts fault type parameters and fault severity parameters from the fault detection result; The path adjustment module calculates a fault influence area of the corresponding detection position of the fault detection result based on the fault type parameter and the fault severity parameter by combining the fault propagation mechanism model and the three-dimensional structure model of the dry-type transformer.
8. The intelligent state detection system for a dry-type transformer according to claim 7, wherein the path adjustment module calculates a fault influence region of the fault detection result corresponding to a detection position based on the fault type parameter and the fault severity parameter in combination with the fault propagation mechanism model and the three-dimensional structure model of the dry-type transformer, wherein, The fault propagation mechanism model comprises an overheat fault propagation submodel, a discharge fault propagation submodel and a mechanical fault propagation submodel; If the fault type parameter indicates that the fault type is an overheat fault, the path adjustment module calls the overheat fault propagation submodel, determines the heat source intensity based on the fault severity parameter, and determines a heat affected zone by combining the heat conduction characteristics and the space distance of each component in the three-dimensional structure model; If the fault type parameter indicates that the fault type is a discharge fault, the path adjustment module calls the discharge fault propagation submodel, determines discharge energy based on a fault severity parameter, and determines a discharge influence area by combining the discharge resistance characteristic and the spatial distribution of the insulating material in the three-dimensional structure model; and if the fault type parameter indicates that the fault type is a mechanical fault, the path adjustment module calls the mechanical fault propagation submodel, determines the vibration source intensity based on the fault severity parameter, and determines a mechanical influence area by combining the mechanical connection relation and the vibration transmission characteristic of each component in the three-dimensional structure model.
9. The intelligent state detection system for a dry-type transformer according to claim 1, wherein the path adjustment module adjusts a subsequent detection path of the fault detection module based on the fault impact region, wherein, The path adjustment module performs space superposition analysis on the fault influence area and the detection path determined by the detection path planning module; if the path segment located in the fault influence area exists in the detection path, the path adjustment module triggers the detection path planning module to re-plan the path segment, and a correction path bypassing the fault influence area is generated; And if no path segment exists in the detection path, which is positioned in the fault influence area, the path adjustment module maintains the detection path unchanged.
10. The intelligent state detection system for a dry-type transformer according to claim 9, wherein the path adjustment module adjusts a subsequent detection path of the fault detection module based on the fault impact area, further based on the following condition: if the potential fault location is located in the fault influence area, the path adjustment module cancels independent detection of the potential fault location and marks the potential fault location as being covered by the current fault; and if the fault influence area covers a plurality of positions to be detected, the path adjustment module merges detection tasks of the positions to be detected, and comprehensively detects the boundary position of the fault influence area.

Description

Intelligent state detection system for dry-type transformer Technical Field The invention relates to the technical field of transformer detection, in particular to an intelligent state detection system for a dry-type transformer. Background The dry-type transformer is widely applied to places such as high-rise buildings, commercial centers, industrial parks and the like due to the advantages of oil free, fire prevention, environmental protection and the like. However, potential faults such as loosening of an iron core, insulation aging, poor contact of a connecting piece and the like of the dry type transformer are difficult to discover in time through conventional means in a long-term operation process, and if the potential faults cannot be identified and positioned early, sudden faults of equipment can be caused, so that the power supply reliability is affected. The traditional dry-type transformer state detection mainly relies on periodic power failure preventive tests and off-line detection, such as insulation resistance tests, partial discharge tests and the like. The method has the following defects that equipment is required to be shut down to influence normal power supply, the detection period is long, real-time monitoring and early warning cannot be realized, the detection result is greatly influenced by the load working condition, vibration and noise under high load easily cover fault characteristics, and fault signals are weak under low load, so that missed detection is easy to cause. The Chinese patent application publication No. CN102759670A discloses a comprehensive evaluation method for the operation state of a dry-type transformer, which synthesizes the influence of each parameter on the operation state of the dry-type transformer, performs reliable grade analysis on the operation state of the dry-type transformer so that an operator can grasp the operation state of the dry-type transformer in real time and perform state maintenance in time, and comprises the following steps of 1) detecting the operation condition and the parameter data of the operation environment of the dry-type transformer and obtaining the inherent characteristic and the parameter data of the operation history of the dry-type transformer, 2) carrying out normalization processing on the operation condition, the operation environment, the inherent characteristic and the parameter data of the operation history of the dry-type transformer, 3) obtaining the membership of corresponding comments of each parameter through the membership function of each parameter and comments and obtaining a single factor comment matrix, 4) combining the weight of each parameter to obtain the comprehensive comment matrix, 5) obtaining the comprehensive evaluation value of the operation state of the dry-type transformer, and reflecting the operation state of the dry-type transformer through the evaluation value. It follows that this prior art has the following problems: the comprehensive evaluation is only carried out based on multi-parameter data, the characteristic of weak fault signals under the low-load working condition cannot be accurately identified, and the detection path cannot be dynamically adjusted according to the detection result, so that the potential fault detection omission ratio and the detection efficiency are low. Disclosure of Invention Therefore, the invention provides an intelligent state detection system for a dry-type transformer, which is used for solving the problems that in the prior art, the accurate identification cannot be carried out aiming at the characteristic of weak fault signals under the low-load working condition, and the detection path cannot be dynamically adjusted according to the detection result, so that the potential fault detection omission ratio and the detection efficiency are low. In order to achieve the above object, the present invention provides an intelligent state detection system for a dry-type transformer, comprising: The data acquisition module is used for acquiring the environmental parameters and the operation parameters of the dry-type transformer; a load type determining module connected with the data module for determining an operation load type of the dry-type transformer based on the operation parameter, wherein the load type comprises a high load type and a low load type; The potential fault positioning module is respectively connected with the data acquisition module and the load type determining module and is used for responding to the condition that the operation load type of the dry-type transformer is a low load type, acquiring a vibration signal of an iron core in the dry-type transformer from the operation parameter, determining a vibration distortion index of the dry-type transformer based on the vibration signal and positioning a potential fault position of the dry-type transformer based on the vibration distortion index; A detection path planning module connected with the