Method and device for evaluating health condition of medium and low voltage switch cabinet

Abstract

The application provides a health condition evaluation method of a medium-low voltage switch cabinet, the evaluation method comprises the following steps: obtaining a data model of the medium-low voltage switch cabinet, the input of the data model is an environmental temperature and a measured temperature of a temperature sensor, and the output of the data model is a theoretical operating current of a main conducting loop; obtaining a real-time current of the main conducting loop, calculating a difference between the real-time current and the theoretical operating current, and generating an aging matrix according to the difference between the real-time current and the theoretical operating current; updating the data model according to the aging matrix, the input of the updated data model is an environmental temperature and a maximum working temperature of the medium-low voltage switch cabinet, and the output of the updated data model is a maximum working current of the medium-low voltage switch cabinet; and evaluating the health condition of the medium-low voltage switch cabinet according to the maximum working current and the real-time current of the main conducting loop.

Description

Technical Field

[0001] This invention relates primarily to the electrical field, and more particularly to a method and apparatus for assessing the health status of medium and low voltage switchgear. Background Technology

[0002] For medium and low voltage switchgear, the number of temperature sensors on the main conductive circuit is very limited. If temperature data from these sensors is used for single-threshold judgment, the assessment results of the health status will be very limited. To overcome the limitations of single-threshold assessment, existing technologies employ 3D thermal network simulation models to evaluate the healthy operating status of the main conductive circuit of medium and low voltage switchgear. This method uses the finite element method to establish a thermal network model of the switch, performs temperature analysis through numerical simulation, and compares the temperature limits of key points in the entire conductive circuit. However, 3D thermal network simulation models are commonly used in offline simulation environments, with long calculation and analysis times, making them unsuitable for engineering implementation, i.e., unsuitable for online switch temperature rise monitoring and analysis. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides a method and apparatus for assessing the health status of medium and low voltage switchgear, thereby improving the accuracy of health status assessment for medium and low voltage switchgear.

[0004] To achieve the above objectives, this invention proposes a method for assessing the health status of medium- and low-voltage switchgear. Temperature sensors are arranged at the connection points between components of the medium- and low-voltage switchgear, and a main conductive circuit is arranged within each component. The assessment method includes: acquiring a data model of the medium- and low-voltage switchgear, the input of which is the ambient temperature and the measured temperature of the temperature sensors, and the output of which is the theoretical operating current of the main conductive circuit; acquiring the real-time current of the main conductive circuit, calculating the difference between the real-time current and the theoretical operating current, and generating an aging matrix based on the difference; updating the data model based on the aging matrix, the input of which is the ambient temperature and the highest operating temperature of the medium- and low-voltage switchgear, and the output of which is the highest operating current of the medium- and low-voltage switchgear; and assessing the health status of the medium- and low-voltage switchgear based on the highest operating current and the real-time current of the main conductive circuit. Therefore, by introducing an aging matrix to update the data model of the medium- and low-voltage switchgear, the data model can more accurately represent the aging status of the switchgear, improving the accuracy of the data model and thus improving the accuracy of the health status assessment.

[0005] Optionally, obtaining the data model of the medium- and low-voltage switchgear includes: establishing a data model using historical data from the medium- and low-voltage switchgear. Therefore, by using historical data from the medium- and low-voltage switchgear to establish the data model, the data model becomes more targeted, thereby improving the accuracy of health status assessment.

[0006] Optionally, obtaining the data model of the medium- and low-voltage switchgear includes: determining the type of the medium- and low-voltage switchgear, and matching a data model in a data model database according to the type of the medium- and low-voltage switchgear. Therefore, matching similar or identical data models using medium- and low-voltage switchgear can improve the efficiency of data model acquisition, thereby improving the efficiency of health status assessment.

[0007] Optionally, generating an aging matrix based on the difference between the real-time current and the theoretical operating current includes: obtaining a basic transformation matrix, and generating the aging matrix based on the basic transformation matrix and the difference between the real-time current and the theoretical operating current. For this purpose, the basic transformation matrix enables the conversion between the difference between the real-time current and the theoretical operating current and the aging matrix.

[0008] Optionally, the method further includes: calculating the difference between the maximum operating current and the real-time current; updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current; and further updating the data model based on the updated aging matrix. Therefore, by updating the data model multiple times, the accuracy of the data model can be further improved, thereby improving the accuracy of the health status assessment.

[0009] This invention also proposes a health status assessment device for medium- and low-voltage switchgear. Temperature sensors are arranged at the connection points between the components of the medium- and low-voltage switchgear, and a main conductive circuit is arranged within each component. The assessment device includes: a first acquisition module, which acquires a data model of the medium- and low-voltage switchgear, wherein the input of the data model is the ambient temperature and the measured temperature of the temperature sensors, and the output of the data model is the theoretical operating current of the main conductive circuit; a second acquisition module, which acquires the real-time current of the main conductive circuit, calculates the difference between the real-time current and the theoretical operating current, and generates an aging matrix based on the difference between the real-time current and the theoretical operating current; an update module, which updates the data model based on the aging matrix, wherein the input of the updated data model is the ambient temperature and the highest operating temperature of the medium- and low-voltage switchgear, and the output of the updated data model is the highest operating current of the medium- and low-voltage switchgear; and an assessment module, which assesses the health status of the medium- and low-voltage switchgear based on the highest operating current and the real-time current of the main conductive circuit.

[0010] Optionally, the first acquisition module acquires the data model of the medium and low voltage switchgear by: establishing a data model using historical data of the medium and low voltage switchgear.

[0011] Optionally, the first acquisition module acquires the data model of the medium- and low-voltage switchgear by: determining the type of the medium- and low-voltage switchgear, and matching the data model in the data model database according to the type of the medium- and low-voltage switchgear.

[0012] Optionally, the second acquisition module generates an aging matrix based on the difference between the real-time current and the theoretical operating current by: acquiring a basic transformation matrix and generating the aging matrix based on the basic transformation matrix and the difference between the real-time current and the theoretical operating current.

[0013] Optionally, the apparatus further includes: calculating the difference between the maximum operating current and the real-time current, updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current, and further updating the data model based on the updated aging matrix.

[0014] The present invention also proposes an electronic device including a processor, a memory and instructions stored in the memory, wherein the instructions, when executed by the processor, implement the method described above.

[0015] The present invention also proposes a computer-readable storage medium having computer instructions stored thereon, which, when executed, perform the method described above.

[0016] The present invention also proposes a computer program product, characterized in that it includes a computer program, which, when executed by a processor, implements the method described above. Attached Figure Description

[0017] The following figures are intended only to illustrate and explain the invention and do not limit the scope of the invention.

[0018] Figure 1 This is a flowchart of a health status assessment method according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of a health status assessment method according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of a health status assessment device according to an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of an electronic device according to an embodiment of the present invention.

[0022] Explanation of reference numerals in the attached figures

[0023] 100 Health Status Assessment Methods

[0024] Steps 110-140

[0025] 21 Data Model

[0026] 22 computing units

[0027] 23 Aging Matrix

[0028] 24-Update Data Model

[0029] 300 Health Assessment Device

[0030] 310 First Acquisition Module

[0031] 320 Second Acquisition Module

[0032] 330 Update Module

[0033] 340 Assessment Module

[0034] 400 electronic devices

[0035] 410 processor

[0036] 420 memory Detailed Implementation

[0037] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described with reference to the accompanying drawings.

[0038] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the invention is not limited to the specific embodiments disclosed below.

[0039] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" are not specifically singular and may include plural forms. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0040] This invention proposes a method for assessing the health status of medium- and low-voltage switchgear. Medium- and low-voltage switchgear is a key piece of equipment in power distribution systems, and the main conductive circuit is a crucial component. To ensure the safe and reliable operation of the entire power distribution system, it is necessary to monitor and assess the operating status of the main conductive circuit of the medium- and low-voltage switchgear. Temperature sensors are arranged at the connection points between limited components of the medium- and low-voltage switchgear, and the main conductive circuit is located within each component; that is, the temperature sensors are in indirect contact with the main conductive circuit. Figure 1 This is a flowchart of a method for assessing the health status of medium and low voltage switchgear according to an embodiment of the present invention, as shown below. Figure 1 As shown, evaluation method 100 includes:

[0041] Step 110: Obtain the data model of the medium and low voltage switchgear. The inputs to the data model are the ambient temperature and the measured temperature of the temperature sensor. The output of the data model is the theoretical operating current of the main conductive circuit.

[0042] In the data model of medium and low voltage switchgear, one input to the data model is the ambient temperature T. a The other input is the measured temperature T from a temperature sensor located at the connection point. m The output of the data model is the theoretical operating current I of the main conductive loop. i The theoretical operating current represents the output operating current of a non-aged medium- and low-voltage switchgear, and the data model can be expressed as I. i =f(T) a ,T m ). Figure 2 This is a schematic diagram of a health status assessment method according to an embodiment of the present invention, as shown below. Figure 2 As shown, the inputs to the data model 21 of the medium and low voltage switchgear include the ambient temperature T. a and the temperature sensor measures the temperature T m The output includes the theoretical operating current I of the main conductive circuit. i .

[0043] In some embodiments, obtaining a data model for medium- and low-voltage switchgear includes: establishing a data model using historical data from the medium- and low-voltage switchgear. Specifically, historical data is collected from non-aging medium- and low-voltage switchgear, including ambient temperature under certain conditions, measured temperatures from temperature sensors located at connection points, and operating current in the main conductive circuit. Mathematical analysis is performed using this historical data to establish a data model for the medium- and low-voltage switchgear. Therefore, by using historical data from medium- and low-voltage switchgear to establish a data model, the model becomes more targeted, thereby improving the accuracy of health status assessment.

[0044] In some embodiments, obtaining a data model for medium- and low-voltage switchgear includes: determining the type of medium- and low-voltage switchgear, and matching a data model in a data model database based on the type of medium- and low-voltage switchgear. Specifically, determining the type of medium- and low-voltage switchgear can be based on a classification according to the operating current range or the operating temperature range. Matching is then performed in a data model database, such as on a server or in the cloud, to find existing data models of the same or similar types of medium- and low-voltage switchgear as the data model for the medium- and low-voltage switchgear to be evaluated. Therefore, matching the same or similar data models using medium- and low-voltage switchgear can improve the efficiency of data model acquisition, thereby improving the efficiency of health status assessment.

[0045] Step 120: Obtain the real-time current of the main conductive circuit, calculate the difference between the real-time current and the theoretical operating current, and generate an aging matrix based on the difference between the real-time current and the theoretical operating current.

[0046] The real-time current in the main conductive circuit can be obtained through the ammeter on the main conductive circuit. It can be understood that the current in the main conductive circuit is the three-phase current (A, B, C), and the obtained real-time current is also the three-phase real-time current (A, B, C). Step 110 obtained data model I. i =f(T) a ,T m Next, the ambient temperature under the current conditions and the measured temperature of the temperature sensors placed at the connection points are input into the data model. The data model outputs the theoretical operating current under these conditions, calculates the difference between the real-time current and the theoretical operating current, that is, the difference between the real-time current and the theoretical operating current of the three phases ABC, and generates an aging matrix M based on the difference between the real-time current and the theoretical operating current. d .like Figure 2 As shown, the real-time current I r The theoretical operating current I output by data model 21 i The data is input into the calculation unit 22, which calculates the real-time current I. r and theoretical operating current I i The difference is calculated, and an aging matrix M is generated based on the difference. d .

[0047] In some embodiments, generating an aging matrix based on the difference between the real-time current and the theoretical operating current includes: obtaining a basic transformation matrix, and generating the aging matrix based on the basic transformation matrix and the difference between the real-time current and the theoretical operating current. Specifically, the differences between each phase of the three-phase real-time current and the theoretical operating current can form a 3*1 matrix. The basic transformation matrix is ​​used to align the 3*1 matrix with the data model, and the aligned matrix is ​​the aging matrix M. dTo this end, a conversion between the difference between the real-time current and the theoretical operating current and the aging matrix was achieved through a basic change matrix.

[0048] Step 130: Update the data model based on the aging matrix. The inputs to the updated data model are the ambient temperature and the maximum operating temperature of the medium and low voltage switchgear. The output of the updated data model is the maximum operating current of the medium and low voltage switchgear.

[0049] Medium and low voltage switchgear will age after a period of use. In the embodiments of this invention, the aging matrix is ​​used to characterize the aging condition of the main conductive circuit. The data model is updated according to the aging matrix, which can be achieved by updating the aging matrix M. d and data model f(T) a ,T m Perform mathematical calculations to obtain M. d ·f(T a ,T m This refers to the updated data model, M. d ·f(T a ,T m The inputs are the ambient temperature and the maximum operating temperature of the medium- and low-voltage switchgear. The maximum operating temperature of the medium- and low-voltage switchgear can be obtained from the operating parameters of the medium- and low-voltage switchgear. The updated data model M d ·f(T a ,T m The output of ) is the highest operating current of the medium and low voltage switchgear. For example Figure 2 As shown, an updated data model 24 can be obtained based on the aging matrix 23 and data model 21. The input of the updated data model 24 is the highest operating temperature T of the medium and low voltage switchgear. l and ambient temperature T a The updated data model 24 outputs the maximum operating current I of the medium and low voltage switchgear. p .

[0050] Step 140: Assess the health status of the medium and low voltage switchgear based on the highest operating current and the real-time current of the main conductive circuit.

[0051] By comparing the maximum operating current with the real-time current of the main conductive circuit, if the real-time current is less than the maximum operating current, it indicates that the main conductive circuit is operating in a safe range and the health condition of the medium and low voltage switchgear is good. If the real-time current is greater than or equal to the maximum operating current, it indicates that the main conductive circuit is operating at a high level and the health condition of the medium and low voltage switchgear is at risk, requiring subsequent maintenance. This enables predictive maintenance of the medium and low voltage switchgear.

[0052] In some embodiments, the method further includes: calculating the difference between the maximum operating current and the real-time current; updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current; and further updating the data model based on the updated aging matrix. Specifically, after updating the data model, the previous steps can be repeated: calculating the difference between the maximum operating current and the real-time current; updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current; and further updating the data model based on the updated aging matrix. Therefore, by updating the data model multiple times, the accuracy of the data model can be further improved, thereby improving the accuracy of the health status assessment.

[0053] The embodiments of the present invention provide a method for assessing the health status of medium and low voltage switchgear. By introducing an aging matrix to update the data model of medium and low voltage switchgear, the data model can more accurately represent the aging status of medium and low voltage switchgear, thereby improving the accuracy of the data model and thus improving the accuracy of the health status assessment.

[0054] This invention also proposes a health status assessment device for medium and low voltage switchgear, wherein temperature sensors are arranged at the connection points between components of the medium and low voltage switchgear, and a main conductive circuit is arranged within each component. Figure 3 This is a schematic diagram of a health status assessment device 300 according to an embodiment of the present invention, as shown below. Figure 3 As shown, the evaluation device 300 includes:

[0055] The first acquisition module 310 acquires the data model of the medium and low voltage switchgear. The input of the data model is the ambient temperature and the measured temperature of the temperature sensor. The output of the data model is the theoretical operating current of the main conductive circuit.

[0056] The second acquisition module 320 acquires the real-time current of the main conductive circuit, calculates the difference between the real-time current and the theoretical operating current, and generates an aging matrix based on the difference between the real-time current and the theoretical operating current.

[0057] The update module 330 updates the data model based on the aging matrix. The input of the updated data model is the ambient temperature and the maximum operating temperature of the medium and low voltage switchgear. The output of the updated data model is the maximum operating current of the medium and low voltage switchgear.

[0058] Evaluation module 340 assesses the health status of medium and low voltage switchgear based on the highest operating current and the real-time current of the main conductive circuit.

[0059] In some embodiments, the first acquisition module 310 acquires the data model of the medium and low voltage switchgear by: establishing a data model using historical data of the medium and low voltage switchgear.

[0060] In some embodiments, the first acquisition module 310 acquires the data model of the medium and low voltage switchgear by: determining the type of the medium and low voltage switchgear, and matching the data model in the data model database according to the type of the medium and low voltage switchgear.

[0061] In some embodiments, the second acquisition module 320 generates an aging matrix based on the difference between the real-time current and the theoretical operating current by: acquiring a basic transformation matrix and generating the aging matrix based on the basic transformation matrix and the difference between the real-time current and the theoretical operating current.

[0062] In some embodiments, the apparatus 300 further includes: calculating the difference between the maximum operating current and the real-time current, updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current, and further updating the data model based on the updated aging matrix.

[0063] The present invention also proposes an electronic device 400. Figure 4 This is a schematic diagram of an electronic device 400 according to an embodiment of the present invention. Figure 4 As shown, the electronic device 400 includes a processor 410 and a memory 420. The memory 420 stores instructions, which, when executed by the processor 410, implement the method 100 described above.

[0064] The present invention also proposes a computer-readable storage medium having computer instructions stored thereon, which, when executed, perform the method 100 described above.

[0065] The present invention also proposes a computer program product, including a computer program that, when executed by a processor, performs the method 100 described above.

[0066] Some aspects of the methods and apparatus of this invention can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The aforementioned hardware or software may be referred to as a "data block," "module," "engine," "unit," "component," or "system." The processor may be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLCs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. Furthermore, aspects of this invention may be embodied as computer products residing in one or more computer-readable media, including computer-readable program code. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, magnetic tapes, etc.), optical discs (e.g., compact discs (CDs), digital multifunction discs (DVDs), etc.), smart cards, and flash memory devices (e.g., cards, sticks, key drives, etc.).

[0067] Flowcharts are used herein to illustrate the operations performed by the method according to embodiments of this application. It should be understood that the preceding operations are not necessarily performed in exact order. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from them.

[0068] It should be understood that although this specification is described according to various embodiments, not every embodiment contains only one independent technical solution. This way of describing the specification is only for clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

[0069] The above description is merely an illustrative embodiment of the present invention and is not intended to limit the scope of the invention. Any equivalent changes, modifications, and combinations made by those skilled in the art without departing from the concept and principles of the present invention should fall within the scope of protection of the present invention.

Claims

1. A method for assessing the health status of a medium- and low-voltage switchgear (100), wherein temperature sensors are arranged at the connection points between components of the medium- and low-voltage switchgear, and a main conductive circuit is arranged within each component, characterized in that... The evaluation method (100) includes: The data model of the medium and low voltage switchgear is obtained. The input of the data model is the ambient temperature and the measured temperature of the temperature sensor. The output of the data model is the theoretical operating current (110) of the main conductive circuit. Obtain the real-time current of the main conductive circuit, calculate the difference between the real-time current and the theoretical operating current, and generate an aging matrix (120) based on the difference between the real-time current and the theoretical operating current. The data model is updated according to the aging matrix. The input of the updated data model is the ambient temperature and the maximum operating temperature of the medium and low voltage switchgear. The output of the updated data model is the maximum operating current (130) of the medium and low voltage switchgear. The health status of the medium and low voltage switchgear is assessed based on the maximum operating current and the real-time current of the main conductive circuit (140).

2. The evaluation method (100) according to claim 1, characterized in that, Obtaining the data model of the medium and low voltage switchgear includes: establishing a data model using historical data of the medium and low voltage switchgear.

3. The evaluation method (100) according to claim 1, characterized in that, Obtaining the data model of the medium- and low-voltage switchgear includes: determining the type of the medium- and low-voltage switchgear, and matching the data model in the data model database according to the type of the medium- and low-voltage switchgear.

4. The evaluation method (100) according to claim 2 or 3, characterized in that, Generating an aging matrix based on the difference between the real-time current and the theoretical operating current includes: obtaining a basic transformation matrix, and generating the aging matrix based on the basic transformation matrix and the difference between the real-time current and the theoretical operating current.

5. The evaluation method (100) according to claim 1, characterized in that, The method (100) further includes: calculating the difference between the maximum operating current and the real-time current, updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current, and further updating the data model based on the updated aging matrix.

6. A health status assessment device (300) for medium- and low-voltage switchgear, wherein temperature sensors are arranged at the connection points between components of the medium- and low-voltage switchgear, and a main conductive circuit is arranged within each component, characterized in that... The evaluation device (300) includes: The first acquisition module (310) acquires the data model of the medium and low voltage switchgear. The input of the data model is the ambient temperature and the measured temperature of the temperature sensor. The output of the data model is the theoretical operating current of the main conductive circuit. The second acquisition module (320) acquires the real-time current of the main conductive circuit, calculates the difference between the real-time current and the theoretical operating current, and generates an aging matrix based on the difference between the real-time current and the theoretical operating current. The update module (330) updates the data model according to the aging matrix. The input of the updated data model is the ambient temperature and the maximum operating temperature of the medium and low voltage switchgear. The output of the updated data model is the maximum operating current of the medium and low voltage switchgear. The evaluation module (340) evaluates the health status of the medium- and low-voltage switchgear based on the maximum operating current and the real-time current of the main conductive circuit.

7. The evaluation apparatus (300) according to claim 6, characterized in that, The first acquisition module (310) acquires the data model of the medium and low voltage switchgear by: establishing a data model using the historical data of the medium and low voltage switchgear.

8. The evaluation apparatus (300) according to claim 6, characterized in that, The first acquisition module (310) acquires the data model of the medium and low voltage switchgear by: determining the type of the medium and low voltage switchgear, and matching the data model in the data model database according to the type of the medium and low voltage switchgear.

9. The evaluation apparatus (300) according to claim 7 or 8, characterized in that, The second acquisition module (320) generates an aging matrix based on the difference between the real-time current and the theoretical operating current by: acquiring a basic transformation matrix and generating the aging matrix based on the basic transformation matrix and the difference between the real-time current and the theoretical operating current.

10. The evaluation apparatus (300) according to claim 6, characterized in that, The device (300) further includes: calculating the difference between the maximum operating current and the real-time current, updating the aging matrix based on the calculated difference between the maximum operating current and the real-time current, and further updating the data model based on the updated aging matrix.

11. An electronic device (400) comprising a processor (410), a memory (420) and instructions stored in the memory (420), wherein the instructions, when executed by the processor (410), implement the method (100) as claimed in any one of claims 1-5.

12. A computer-readable storage medium having stored thereon computer instructions that, when executed, perform the method (100) according to any one of claims 1-5.

13. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, performs the method (100) of any one of claims 1-5.

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