Equipment abnormity identification method and device considering arc current transient characteristics
Through phase space reconstruction of current time domain waveforms and topological feature extraction, the blindness and complexity of power equipment diagnosis are solved, and effective identification of arc events and improved power network reliability are achieved.
Patent Information
- Application Number
- CN202411499727.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-25
- Publication Date
- 2025-01-07
AI Technical Summary
Small problems that are easily overlooked during long-term operation of power equipment lead to safety hazards and economic losses, and the power grid maintenance personnel lack sufficient fault diagnosis capabilities, resulting in blind diagnosis and imbalance in the diagnosis process, and the complexity increases the difficulty of diagnosis.
By obtaining the current time domain waveform, performing phase space reconstruction, converting it into binary images and two-dimensional matrices, topological structure features are extracted, and arc events are judged using arc samples to statistical thresholds, improving arc recognition capabilities.
Real-time health status monitoring of power equipment is realized, the reliability of power network is improved, the arc recognition ability is enhanced, and the blindness and complexity of power equipment diagnosis is solved.
Smart Images
Figure CN119272199A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to a method and a device for identifying equipment abnormality by taking into account transient characteristics of arc current, and belongs to the technical field of electric energy metering. Background Art
[0002] In the long-term operation of power equipment, some minor problems often occur, and these problems are easily overlooked in the maintenance, repair and inspection of the equipment, which will not only cause safety hazards to the equipment, but also may cause the substation to fail to operate normally, and even damage the economic benefits of the substation and affect the normal power supply of the city. Due to many professional limitations of power knowledge, the overall maintenance level of power grid maintenance personnel is uneven, many lack work experience, and there are very few workers with sufficient fault diagnosis capabilities and a single diagnostic method. Therefore, the company is very blind in the fault diagnosis process of power equipment, resulting in an imbalance between costs and revenues. At the same time, the lack of professional data mining diagnostic talents is also a key problem faced by power companies in the process of development. With the continuous development of power equipment, its complexity is getting higher and higher, and its diagnosis is becoming more and more difficult. Summary of the invention
[0003] The purpose of the present invention is to overcome the deficiencies in the prior art and to provide a method and device for identifying equipment abnormalities taking into account the transient characteristics of arc current, so as to monitor the health status of power supply and utilization equipment in real time and effectively improve the reliability of the power network in the substation area.
[0004] To achieve the above object, the present invention is implemented by adopting the following technical solutions: In a first aspect, the present invention provides a method for identifying equipment abnormality taking into account transient characteristics of arc current, comprising: Get the current time domain waveforms of different household appliances; Reconstruct the phase space according to the current time domain waveform and output the binary image of the current trajectory in the phase space; Converting the binary image of the current trajectory in the phase space into a two-dimensional matrix, and outputting a feature that can reflect the topological structure based on the two-dimensional matrix; Based on the received features reflecting the topological structure, the occurrence of an arc event is judged by using arc sample statistical thresholds.
[0005] Furthermore, the phase space reconstruction is performed according to the current time domain waveform to output a binary image of the current trajectory in the phase space, including: Calculate time-delayed signal ,in T For delay, T The value of is a natural number, For discrete time series =1,2,3... ; Constructing phase space vector ,in is a two-dimensional vector sequence, is the current time domain waveform; On a two-dimensional plane, the phase space is displayed as a binary image, and the pixel values are as follows: ; in, is the pixel value, x , y are the coordinates of the image pixels, t The value range of is the observation time interval of the arc. t=0 Represents the observation start time sequence number, t=N Represents the observation end time sequence.
[0006] Furthermore, the binary image of the current trajectory in the phase space is converted into a two-dimensional matrix, and based on the two-dimensional matrix, a feature that can reflect the topological structure is output, including: Convert the binary image of the current trajectory in phase space into a two-dimensional matrix; Generate anchor points in a two-dimensional matrix by using equal intervals or random uniform distribution; Based on the anchor points, multiple topological features are calculated in a multi-scale neighborhood around each anchor point; The calculated multiple topological features are processed to output a structural feature that can reflect the entire phase space binary image.
[0007] Furthermore, generating anchor points in the two-dimensional matrix in an equally spaced or randomly uniformly distributed manner specifically includes: Generate by equal interval or random uniform distribution M Anchor points , m is the anchor point subscript number, M is the total number of anchor points; This is an equally spaced distribution or a random uniform distribution on this interval: ; This is an equally spaced distribution or a random uniform distribution on this interval: .
[0008] Furthermore, based on the anchor points, multiple topological features are calculated in a multi-scale neighborhood around each anchor point, including: Multi-scale neighborhoods around anchor points In each case, multiple topological features are calculated. , Neighborhood The corresponding topological features are L is the number of neighbors; ,in represents the neighborhood, l represents the neighborhood number, Represents the pixel points of the phase space binary image, and Representative m The horizontal and vertical coordinates of the anchor point.
[0009] Furthermore, the structural characteristics of the binary image in the entire phase space can be reflected by the following formula: ; in, is the topological characteristic of the constructed phase space.
[0010] Furthermore, the method of determining the occurrence of an arc event based on the received features reflecting the topological structure and using an arc sample statistical threshold comprises: The received features reflecting the topological structure are constructed as discriminant feature vectors ; is the topological characteristic of the constructed phase space; According to the existing positive and negative sample sets, the probability distribution density function is calculated respectively; Based on the probability distribution density function, the Bayesian decision criterion is used to determine the decision threshold of each feature dimension: ; Compare vectors one by one The features of each dimension in the is compared with the corresponding decision threshold. If a feature dimension greater than the threshold appears, the sample is determined to be an arc event.
[0011] In a second aspect, the present invention provides a device for identifying equipment abnormality taking into account transient characteristics of arc current, comprising: An acquisition module, used to acquire the current time domain waveforms of different household appliances; The phase space reconstruction module is used to reconstruct the phase space according to the current time domain waveform and output a binary image of the current trajectory in the phase space; A conversion module, used for converting the binary image of the current trajectory in the phase space into a two-dimensional matrix, and outputting a feature that can reflect the topological structure based on the two-dimensional matrix; The judgment module is used to judge the occurrence of an arc event based on the received features reflecting the topological structure and using the arc sample statistical threshold.
[0012] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the aforementioned methods.
[0013] In a fourth aspect, the present invention provides a computer device / equipment / system, comprising: Memory, for storing computer programs / instructions; A processor is used to execute the computer program / instructions to implement the steps of any of the aforementioned methods.
[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a method and device for identifying equipment abnormalities taking into account the transient characteristics of arc current, studies the empirical mode feature extraction technology and the chaos index feature extraction technology, and obtains complex nonlinear features; at the same time, for complex arcs, the present invention innovatively proposes a nonlinear dynamic feature extraction technology based on phase space reconstruction parameters, which is beneficial to improving the recognition ability of arcs. At the same time, based on image recognition technology, the present invention studies the nonlinear feature extraction based on image recognition to achieve online recognition and learning of arc features. The present invention monitors the health status of power supply and use equipment in real time by considering the transient feature identification of arc current, and effectively improves the reliability of the power network in the substation area. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Figure 1 It is a flow chart of a method for identifying equipment abnormality taking into account transient characteristics of arc current provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0016] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.
[0017] Embodiment 1: This embodiment introduces a method for identifying equipment abnormality taking into account transient characteristics of arc current, including: Get the current time domain waveforms of different household appliances; Reconstruct the phase space according to the current time domain waveform and output the binary image of the current trajectory in the phase space; Converting the binary image of the current trajectory in the phase space into a two-dimensional matrix, and outputting a feature that can reflect the topological structure based on the two-dimensional matrix; Based on the received features reflecting the topological structure, the occurrence of an arc event is judged by using arc sample statistical thresholds.
[0018] The device abnormality identification method considering the transient characteristics of arc current provided in this embodiment specifically involves the following steps: The current time domain waveform of household appliances is collected through current transformers and recorded as ,in t For discrete time series t=1,2,3... ; Receive the current time waveform, output the binary image of the current trajectory in the phase space, and reconstruct the phase space. Calculate the time domain delay signal . Then construct the phase space vector ,in is a two-dimensional vector sequence, t is a time series. On a two-dimensional plane, the phase space is displayed as a binary image, and the pixel values are as follows: ; in, is the pixel value, x , y are the coordinates of the image pixels, t The value range of is the observation time interval of the arc. t=0 Represents the observation start time sequence number, t=N Represents the observation end time sequence.
[0019] The binary image of the current trajectory is received, converted into a two-dimensional matrix, and the features reflecting the topological structure of the structure are output.
[0020] 3.1 Generate anchor point: take the origin as the anchor point 3.2 Generate multi-scale domains: Set the pixels within a distance of no more than 0.2 from the anchor point to belong to the first domain, and the pixels within a distance of no more than 0.4 to belong to the second domain.
[0021] 3.3 Calculation of topological features: Structural features of phase space binary images: ; in ; The constructed topological structure feature is received, and the occurrence of an arc event is determined according to an arc sample statistical threshold.
[0022] 4.1 Constructing discriminant feature vector ; is the topological characteristic of the constructed phase space.
[0023] 4.2 Use the normal distribution model to calculate the mean and variance of the arc sample features. According to the Bayesian decision criterion, determine the decision threshold of each dimension of the feature vector: , when a sample greater than the threshold appears, it is determined to be an arc event. Example
[0024] This embodiment provides a device for identifying equipment abnormality taking into account transient characteristics of arc current, including: An acquisition module, used to acquire the current time domain waveforms of different household appliances; The phase space reconstruction module is used to reconstruct the phase space according to the current time domain waveform and output a binary image of the current trajectory in the phase space; A conversion module, used for converting the binary image of the current trajectory in the phase space into a two-dimensional matrix, and outputting a feature that can reflect the topological structure based on the two-dimensional matrix; The judgment module is used to judge the occurrence of an arc event based on the received features reflecting the topological structure and using the arc sample statistical threshold.
[0025] Embodiment 2: This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of any one of the methods described in Embodiment 1 are implemented.
[0026] Embodiment 3: This embodiment provides a computer device / equipment / system, including: Memory, for storing computer programs / instructions; A processor, configured to execute the computer program / instructions to implement the steps of any one of the methods described in Example 1.
[0027] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.
[0028] It should be understood by those skilled in the art that the embodiments of the present disclosure may be provided as methods, systems or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0029] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0030] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0031] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0032] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure rather than to limit its protection scope. Although the present disclosure has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present disclosure, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the disclosed claims to be approved.
Claims
1. A method for identifying equipment abnormality considering transient characteristics of arc current, characterized in that: include: Get the current time domain waveforms of different household appliances; Reconstruct the phase space according to the current time domain waveform and output the binary image of the current trajectory in the phase space; Converting the binary image of the current trajectory in the phase space into a two-dimensional matrix, and outputting a feature that can reflect the topological structure based on the two-dimensional matrix; Based on the received features reflecting the topological structure, the occurrence of an arc event is judged by using arc sample statistical thresholds.
2. The method for identifying equipment abnormality considering transient characteristics of arc current according to claim 1, characterized in that: The phase space reconstruction is performed according to the current time domain waveform to output a binary image of the current trajectory in the phase space, including: Calculate time-delayed signal ,in T For delay, T The value of is a natural number, For discrete time series =1,2,3... ; Constructing phase space vector ,in is a two-dimensional vector sequence, is the current time domain waveform; On a two-dimensional plane, the phase space is displayed as a binary image, and the pixel values are as follows: ； in, is the pixel value, x , y are the coordinates of the image pixels, t The value range of is the observation time interval of the arc. t=0 Represents the observation start time sequence number, t=N Represents the observation end time sequence.
3. The method for identifying equipment abnormality considering transient characteristics of arc current according to claim 2, characterized in that: The step of converting the binary image of the current trajectory in the phase space into a two-dimensional matrix and outputting a feature that can reflect the topological structure based on the two-dimensional matrix includes: Convert the binary image of the current trajectory in phase space into a two-dimensional matrix; Generate anchor points in a two-dimensional matrix by using equal intervals or random uniform distribution; Based on the anchor points, multiple topological features are calculated in a multi-scale neighborhood around each anchor point; The calculated multiple topological features are processed to output a structural feature that can reflect the entire phase space binary image.
4. The method for identifying equipment abnormality considering transient characteristics of arc current according to claim 3, characterized in that: The generating of anchor points in the two-dimensional matrix by using equal intervals or random uniform distribution specifically includes: Generate by equal interval or random uniform distribution M Anchor points , m is the anchor point subscript number, M is the total number of anchor points; This is an equally spaced distribution or a random uniform distribution on this interval: ; This is an equally spaced distribution or a random uniform distribution on this interval: .
5. The method for identifying equipment abnormality considering transient characteristics of arc current according to claim 4, characterized in that: Based on the anchor points, multiple topological features are calculated in a multi-scale neighborhood around each anchor point, including: Multi-scale neighborhoods around anchor points In each case, multiple topological features are calculated. , Neighborhood The corresponding topological features are L is the number of neighbors; ,in represents the neighborhood, l represents the neighborhood number, Represents the pixel points of the phase space binary image, and Representative m The horizontal and vertical coordinates of the anchor point.
6. The method for identifying equipment abnormality considering transient characteristics of arc current according to claim 5, characterized in that: The structural characteristics of the binary image in the entire phase space can be reflected by the following formula: ； in, is the topological characteristic of the constructed phase space.
7. The method for identifying equipment abnormality considering transient characteristics of arc current according to claim 6, characterized in that: The method of determining the occurrence of an arc event based on the received features reflecting the topological structure and using an arc sample statistical threshold comprises: The received features reflecting the topological structure are constructed as discriminant feature vectors ; According to the existing positive and negative sample sets, the probability distribution density function is calculated respectively; Based on the probability distribution density function, the Bayesian decision criterion is used to determine the decision threshold of each feature dimension: is the decision threshold for each dimension; Compare vectors one by one The features of each dimension in the is compared with the corresponding decision threshold. If a feature dimension greater than the threshold appears, the sample is determined to be an arc event.
8. A device for identifying equipment abnormality taking into account transient characteristics of arc current, characterized in that: include: An acquisition module, used to acquire the current time domain waveforms of different household appliances; The phase space reconstruction module is used to reconstruct the phase space according to the current time domain waveform and output a binary image of the current trajectory in the phase space; A conversion module, used for converting the binary image of the current trajectory in the phase space into a two-dimensional matrix, and outputting a feature that can reflect the topological structure based on the two-dimensional matrix; The judgment module is used to judge the occurrence of an arc event based on the received features reflecting the topological structure and using the arc sample statistical threshold.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.
10. A computer device / equipment / system, characterized in that: include: Memory, for storing computer programs / instructions; A processor, configured to execute the computer program / instructions to implement the steps of the method according to any one of claims 1 to 7.