Circuit breaker abnormal heating state identification method and system based on temperature rise inversion, computer equipment and storage medium

Abstract

The invention relates to the technical field of circuit breaker fault identification, and discloses a circuit breaker abnormal heating state identification method and system based on temperature rise inversion, computer equipment and a storage medium. The sum of the three-phase load rates of the circuit breaker is input into the parallel inversion model which is established by utilizing a grid search and support vector machine method and combining a Spark parallel calculation framework, so that whether the circuit breaker is in an abnormal heating state or not can be judged according to the temperature rise inversion value, output by the parallel inversion model, of the contact of the circuit breaker, the method is efficient and accurate, and the working efficiency of the circuit breaker is improved. According to the method, the operation state of the circuit breaker can be comprehensively and accurately evaluated, the existence of the overheating fault can be identified in the first time, and the method is of great importance for ensuring stable operation of a power system and improving the fault processing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of circuit breaker fault identification, and in particular to a method, system, computer equipment and storage medium for identifying abnormal heating state of a circuit breaker based on temperature rise inversion. Background Art

[0002] In the complex operating environment of the power system, abnormal heating of circuit breakers constitutes a frequently encountered failure mode. Specifically, when an abnormal heating fault condition occurs in the internal structure of the circuit breaker, its overall temperature will show a continuous and stable upward trend compared to the circuit breaker in normal operation under the same load conditions. More importantly, as the heating power of the fault point continues to increase, this temperature rise trend will also increase accordingly.

[0003] In view of this, a technical challenge that needs to be solved urgently is how to use efficient and accurate methods to comprehensively and accurately evaluate the operating status of circuit breakers and identify the existence of overheating faults in the first place. Solving this problem is crucial to ensuring the stable operation of the power system and improving the efficiency of fault handling.

[0004] The above information is presented as background information only to assist with understanding the present disclosure and no determination or admission is made as to whether any of the above may be used as prior art with respect to the present disclosure. Summary of the invention

[0005] The present invention provides a method, system, computer equipment and storage medium for identifying abnormal heating state of a circuit breaker based on temperature rise inversion, so as to solve the problems existing in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion, the method comprising:

[0008] The sum of the three-phase load rates of the circuit breaker is input into a parallel inversion model, wherein the parallel inversion model is established by using a grid search and support vector machine method in combination with a Spark parallel computing framework;

[0009] According to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model, it is judged whether the circuit breaker is in an abnormal heating state.

[0010] Furthermore, in the method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion, the method further includes:

[0011] Constructing parallel inversion models;

[0012] The parallel inversion model is trained and tested using a training set and a test set respectively to obtain the trained parallel inversion model.

[0013] Furthermore, in the circuit breaker abnormal heating state identification method based on temperature rise inversion, the step of constructing a parallel inversion model is:

[0014] A parallel inversion model is constructed by using grid search and support vector machine methods combined with the Spark parallel computing framework.

[0015] Furthermore, in the method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion, the method further includes:

[0016] The collected sample set of the contact temperature rise of the circuit breaker is divided into a training set and a test set according to a preset ratio; the sample set includes normal operation samples and abnormal heating samples;

[0017] The normal operating sample is data of the circuit breaker in a normal working state, excluding any abnormal heat source;

[0018] The abnormal heating samples are data of the circuit breaker under abnormal heating states of different degrees, including different abnormal heating powers under the same load rate.

[0019] Furthermore, in the method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion, the step of judging whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model comprises:

[0020] Comparing the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model with the actual measured value, and determining whether the actual measured value is higher than the temperature rise inversion value and the deviation exceeds a preset threshold;

[0021] If yes, it is determined that the circuit breaker is in an abnormal heating state;

[0022] If not, it is determined that the circuit breaker is in a normal operating state.

[0023] Furthermore, in the method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion, taking into account the temperature rise inversion error of the contacts of the circuit breaker, the preset threshold is 2.9K.

[0024] Furthermore, in the method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion, after the step of determining that the circuit breaker is in an abnormal heating state, the method further includes:

[0025] The degree of abnormal heating state of the circuit breaker is determined according to the deviation between the actual measured value and the temperature rise inversion value.

[0026] In a second aspect, the present invention provides a circuit breaker abnormal heating state identification system based on temperature rise inversion, the system comprising:

[0027] A data input module, used for inputting the sum of the three-phase load factors of the circuit breaker into a parallel inversion model, wherein the parallel inversion model is established by using a grid search and support vector machine method in combination with a Spark parallel computing framework;

[0028] The abnormality judgment module is used to judge whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model.

[0029] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion as provided in the first aspect above is implemented.

[0030] In a fourth aspect, the present invention provides a storage medium comprising computer executable instructions, wherein the computer executable instructions are executed by a computer processor to implement the method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion as provided in the first aspect above.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The present invention provides a method, system, computer device and storage medium for identifying the abnormal heating state of a circuit breaker based on temperature rise inversion. By inputting the sum of the three-phase load rates of the circuit breaker into a parallel inversion model established by using a grid search and support vector machine method in combination with a Spark parallel computing framework, it is possible to judge whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contacts of the circuit breaker output by the parallel inversion model. This method is not only efficient and accurate, but can also comprehensively and accurately evaluate the operating state of the circuit breaker, and can identify the existence of an overheating fault in the first time, which is crucial to ensuring the stable operation of the power system and improving the efficiency of fault handling.

[0033] The present invention has other features and advantages, which will be apparent from or will be described in detail in the accompanying drawings and the following detailed description incorporated herein, which together serve to explain the specific principles of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 It is a flow chart of a method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion provided in Embodiment 1 of the present invention;

[0036] Figure 2 This is a diagram of the contact temperature rise inversion mentioned in the first embodiment of the present invention;

[0037] Figure 3 It is a functional module diagram of a circuit breaker abnormal heating state identification system based on temperature rise inversion provided in Embodiment 2 of the present invention;

[0038] Figure 4 It is a structural diagram of a computer device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0039] In order to explain in detail the possible application scenarios, technical principles, specific schemes that can be implemented, and the purposes and effects that can be achieved, the following is a detailed description of the specific embodiments listed in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0040] Reference to "embodiment" herein means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The term "embodiment" appearing in various places in the specification does not necessarily refer to the same embodiment, nor does it particularly limit its independence or association with other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the various technical features mentioned in the embodiments can be combined in any way to form a corresponding implementable technical solution.

[0041] Unless otherwise defined, the technical terms used in this document have the same meanings as those generally understood by those skilled in the art to which this application belongs; the use of relevant terms in this document is only for describing specific embodiments and is not intended to limit this application.

[0042] In the description of this application, the term "and / or" is an expression used to describe the logical relationship between objects, indicating that three relationships may exist, for example, A and / or B, which means: A exists, B exists, and A and B exist at the same time. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" logical relationship.

[0043] In the present application, terms such as “first” and “second” are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship of quantity, priority or sequence between these entities or operations.

[0044] Without further limitations, in this application, the words "include", "comprises", "has" or other similar expressions used in the sentences are intended to cover non-exclusive inclusion. These expressions do not exclude the presence of additional elements in the process, method or product including the elements, so that the process, method or product including a series of elements may include not only those limited elements, but also other elements not explicitly listed, or also include elements inherent to such process, method or product.

[0045] In this application, expressions such as "greater than", "less than", "exceed" and the like are understood to exclude the number itself; expressions such as "above", "below", "within" and the like are understood to include the number itself. In addition, in the description of the embodiments of this application, "multiple" means more than two (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups", "multiple times", etc., unless otherwise clearly and specifically limited.

[0046] In the description of the embodiments of the present application, space-related expressions used, such as "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "vertical", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicate the orientation or position relationship based on the orientation or position relationship shown in the specific embodiments or drawings, and are only for the convenience of describing the specific embodiments of the present application or facilitating the reader's understanding, and do not indicate or imply that the referred device or component must have a specific position, a specific orientation, or be constructed or operated in a specific orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0047] Unless otherwise expressly specified or limited, in the description of the embodiments of the present application, the terms such as "install", "connect", "connect", "fix", "set", etc. used should be understood in a broad sense. For example, the "connection" can be a fixed connection, a detachable connection, or an integrated setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For technicians in the technical field to which the present application belongs, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0048] Embodiment 1

[0049] In view of the above-mentioned defects in the prior art, the applicant, based on many years of rich practical experience and professional knowledge in design and manufacturing in this field, and in conjunction with the application of theory, actively conducts research and innovation in the hope of creating a technology that can solve the defects in the prior art. After continuous research and design, and after repeated trial production and improvement, the present invention with real practical value was finally created.

[0050] Please refer to Figure 1 , is a flow chart of a method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion provided in Embodiment 1 of the present invention. The method is applicable to identifying abnormal heating of a circuit breaker. The method is executed by a system for identifying abnormal heating state of a circuit breaker based on temperature rise inversion. The system can be implemented by software and / or hardware. The method specifically comprises the following steps:

[0051] S101. Inputting the sum of the three-phase load rates of the circuit breaker into a parallel inversion model, wherein the parallel inversion model is established by using a grid search and support vector machine method in combination with a Spark parallel computing framework.

[0052] It should be noted that this step is to import the sum of the three-phase load factors of the circuit breaker as input data into a carefully constructed parallel inversion model. This model uses the deep integration of advanced grid search (GS) algorithm and support vector machine (SVR) technology, and integrates Spark, an efficient parallel computing framework, to achieve high-speed processing capabilities for large-scale data.

[0053] S102: Determine whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model.

[0054] It should be noted that this step is based on the precise results output by the parallel inversion model, namely the temperature rise inversion value of the circuit breaker contacts. The system will conduct a detailed analysis of the current state of the circuit breaker to determine whether it is in a critical or dangerous state of abnormal heating.

[0055] The embodiment of the present invention can quickly and accurately evaluate the operating status of the circuit breaker based on the inversion value of the contact temperature rise by cleverly inputting the sum of the three-phase load rate of the circuit breaker into the parallel inversion model. This solution not only significantly improves the detection efficiency and accuracy, but also can immediately identify overheating in the early stage of a fault, which is of immeasurable value in ensuring the stable operation of the power system, optimizing the fault response mechanism and improving the overall operation and maintenance efficiency.

[0056] In one implementation of this embodiment, the circuit breaker abnormal heating state identification method based on temperature rise inversion also incorporates the key link of building and optimizing a parallel inversion model, which is crucial to the effectiveness and accuracy of the entire method. In detail, the extended process of the method is as follows:

[0057] First, we enter the model building phase, that is, building a parallel inversion model. The design of this model fully considers the complexity and diversity of the circuit breaker's operating status and the need for efficient data processing. It is based on grid search and support vector machine methods, combined with the Spark parallel computing framework, to achieve fast and accurate inversion of circuit breaker temperature changes.

[0058] Next, in order to verify the performance of the parallel inversion model, a scientific training and testing process was adopted. Specifically, this embodiment prepared circuit breaker data containing various load conditions and temperature response characteristics as a training set, and used these data to train the parallel inversion model so that it can learn the temperature response law of the circuit breaker under different conditions. At the same time, another set of independent test sets was prepared to evaluate the accuracy and reliability of the trained model in practical applications.

[0059] Through this series of steps, a fully trained and tested parallel inversion model was obtained. This model not only has efficient data processing capabilities, but also can accurately invert the temperature rise of the circuit breaker contacts, thus providing strong support for subsequent state identification and fault warning.

[0060] In one implementation of this embodiment, the circuit breaker abnormal heating state identification method based on temperature rise inversion further incorporates the sample set preparation and division process, which is crucial to ensure the training effect and test accuracy of the parallel inversion model. The specific process is as follows:

[0061] First, this embodiment collects a large amount of sample data on the temperature rise of circuit breaker contacts, which covers the temperature response of the circuit breaker under normal working conditions and the temperature changes under different degrees of abnormal heating conditions. These sample data are carefully sorted and constitute a comprehensive sample set.

[0062] Then, in order to effectively utilize these sample data, the sample set is divided into a training set and a test set according to a preset ratio. The training set is used to train the parallel inversion model so that it can learn the temperature response law of the circuit breaker under different conditions; while the test set is used to evaluate the accuracy and reliability of the trained model in practical applications.

[0063] It is worth noting that the sample set contains two types of samples: normal operation samples and abnormal heating samples. Normal operation samples represent the data of the circuit breaker under normal working conditions. These data do not contain the influence of any abnormal heat source, so they can reflect the temperature characteristics of the circuit breaker under normal conditions. Abnormal heating samples represent the data of the circuit breaker under different degrees of abnormal heating conditions. These data cover different abnormal heating powers under the same load rate, so they can fully reflect the temperature response characteristics of the circuit breaker under abnormal heating conditions.

[0064] Through this series of steps, it is ensured that the parallel inversion model can fully learn the temperature response law of the circuit breaker under normal and abnormal heating conditions during the training process, thereby improving the accuracy and reliability of the model in practical applications. This process not only reflects the scientific data processing method, but also provides strong data support for subsequent state identification and fault warning.

[0065] In order to fully consider the three-phase unbalanced operating conditions, the established training samples for identifying abnormal heating states of circuit breakers are shown in Table 1, and the established test samples for identifying abnormal heating states of circuit breakers are shown in Table 2. The test samples No. 3-5 were obtained by the actual temperature rise test method, and the remaining samples were obtained by the simulation test method.

[0066] Table 1 Training samples

[0067]

[0068] Table 2 Test samples

[0069]

[0070] In a specific implementation scheme of this embodiment, the step of constructing the parallel inversion model is exhaustively planned as the following key processes:

[0071] This embodiment uses a deep fusion of grid search and support vector machine methods, and cleverly combines Spark, a powerful parallel computing framework, to jointly build an efficient and accurate parallel inversion model. This model aims to achieve rapid and accurate inversion of the temperature rise of circuit breaker contacts, providing strong support for subsequent abnormal heating state identification.

[0072] In the data preparation stage, the advantages of the distributed storage system were fully utilized to efficiently read the data set of circuit breaker contact temperature rise. In order to ensure the efficiency and scalability of data processing, the data set was divided into multiple independent partitions, which will be processed in parallel on the subsequent Spark cluster. This step not only improves the efficiency of data processing, but also provides rich data resources for subsequent model training.

[0073] Entering the data preprocessing stage, relying on the powerful computing power of the Spark cluster, the data is processed comprehensively and carefully. This includes key steps such as data cleaning and feature extraction to ensure that the data input into the model is accurate and effective. At the same time, the data is also standardized or normalized, which is crucial to improving the stability and accuracy of model training.

[0074] Finally, in the model training phase, Spark MLlib or Spark's machine learning library was fully utilized to train the GS-SVR (Grid Search-Support Vector Regression) inversion model in parallel for each data partition. This step not only improves the efficiency of model training, but also fully utilizes the computing resources of the cluster through parallel computing, thus ensuring the accuracy and efficiency of model training.

[0075] In summary, the method proposed in this embodiment not only includes the construction process of the parallel inversion model, but also covers key links such as data preparation, data preprocessing and model training, forming a complete and efficient solution. This solution not only improves the accuracy and efficiency of identifying abnormal heating status of circuit breakers, but also provides strong technical support for the stable operation and fault warning of power systems.

[0076] In a more detailed and in-depth implementation of this embodiment, the judgment process of step S102 is further refined and optimized. This step aims to accurately judge the operating state of the circuit breaker by comparing the inversion value of the circuit breaker contact temperature rise output by the parallel inversion model with the actual measured value. The specific details are as follows:

[0077] Comparing the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model with the actual measured value, and determining whether the actual measured value is higher than the temperature rise inversion value and the deviation exceeds a preset threshold;

[0078] If yes, it is determined that the circuit breaker is in an abnormal heating state;

[0079] If not, it is determined that the circuit breaker is in a normal operating state.

[0080] It should be noted that, first, the inversion value of the circuit breaker contact temperature rise output by the parallel inversion model is compared one by one with the actual measured value obtained by actual measurement means such as sensors. This step is crucial to verify the accuracy of the model prediction and discover potential abnormal conditions.

[0081] Next, a preset threshold is set to determine whether the deviation between the actual measured value and the temperature rise inversion value is within an acceptable range. This threshold is set based on the normal operating characteristics and potential fault characteristics of the circuit breaker, combined with actual conditions and expert experience.

[0082] Then, make a judgment based on the comparison results and the preset threshold:

[0083] If the actual measured value is higher than the temperature rise inversion value, and this deviation exceeds the preset threshold, the circuit breaker is considered to be in an abnormal heating state. This may be due to internal faults, overload or environmental factors that cause the temperature to rise, and immediate measures need to be taken to troubleshoot and deal with the fault.

[0084] If the deviation between the actual measured value and the temperature rise inversion value is within the preset threshold range, or the actual measured value is not higher than the temperature rise inversion value, the circuit breaker is determined to be in normal operation. This means that the temperature response of the circuit breaker is in line with normal expectations and no additional troubleshooting or processing is required.

[0085] Through this series of judgment steps, the abnormal heating state of the circuit breaker can be identified more accurately and timely, so that corresponding measures can be taken to prevent and deal with faults and ensure the stable operation and safety of the power system. This refinement process not only improves the accuracy of judgment, but also provides strong support for subsequent status monitoring and fault warning.

[0086] The temperature rise of the circuit breaker contact is related to the total energy inside the circuit breaker. Therefore, the training samples and test samples use the load characteristic quantity of the sum of the three-phase load rate as input and the circuit breaker contact temperature rise as output. The inversion model of the circuit breaker contact temperature rise was established using the GS-SVR method. The contact temperature rise of the test sample during normal operation is shown in Table 3 and Figure 2 shown.

[0087] Table 3 Inversion results of contact temperature rise of test samples

[0088]

[0089] From the inversion results, it can be seen that under normal operating conditions, such as test samples 1, 2, 3, and 7, the difference in contact temperature rise between the inversion value and the calculated value or test value is within 1K. 4, 5, and 6 are test samples, all working under rated conditions, but containing abnormal heat sources. Test sample 4 is obtained from the actual temperature rise test.

[0090] The abnormal heat source heating power is 100 W, and the measured value of the contact temperature rise is 1.6 K higher than the inversion value. Test sample 6 is obtained by simulation calculation. The abnormal heat source heating power is 500 W, and the simulated value of the contact temperature rise is 7.2 K higher than the inversion value, indicating that there is an abnormal heat source inside the circuit breaker. At the same time, the greater the heating power of the abnormal heat source in the circuit breaker, the greater the temperature difference between the calculated value or measured value of the contact temperature rise and the inversion value.

[0091] When the actual measured value of the contact temperature rise is higher than the inversion value of 1K, it indicates that the circuit breaker is in an abnormal heating state. Therefore, by comparing the inversion value of the contact temperature rise with the calculated value or measured value of the test sample, it can be judged that test samples 4, 5, 6 and test samples 8, 9, 10 are in an abnormal heating state, and the degree of abnormal heating is deepening. The inversion identification results of the abnormal heating state of the test samples in this embodiment are consistent with the actual situation, proving the effectiveness and accuracy of the circuit breaker contact temperature rise inversion model in identifying abnormal heating states and distinguishing the heating degree of the circuit breaker.

[0092] In this embodiment, considering the temperature rise inversion error of the contacts of the circuit breaker, the preset threshold is 2.9K (Kelvin).

[0093] It should be noted that the maximum absolute temperature difference between the calculated value and the test value of the circuit breaker contact temperature is 1.9K. When using the inversion model to judge the abnormal heating state of the circuit breaker, in order to avoid misjudgment, the contact temperature rise inversion error caused by the calculation error in the thermal fluid field calculation of the circuit breaker should be considered. Therefore, it is necessary to correct the originally set contact temperature rise deviation limit (1K) to identify the abnormal heating state. The corrected basis for judging the abnormal heating state of the circuit breaker is as follows: When the measured value of the contact temperature rise is 2.9K higher than the inversion value, it means that the circuit breaker is in an abnormal heating state, and the greater the deviation between the measured value of the contact temperature rise and the inversion value, the deeper the abnormal heating degree of the internal fault part.

[0094] In this embodiment, after the step of determining that the circuit breaker is in an abnormal heating state, the method further includes:

[0095] The degree of abnormal heating state of the circuit breaker is determined according to the deviation between the actual measured value and the temperature rise inversion value.

[0096] It should be noted that this step aims to quantitatively evaluate the degree of abnormal heating of the circuit breaker by comparing the deviation between the two. The size of the deviation directly reflects the severity of the abnormal temperature of the circuit breaker. The larger the deviation, the more serious the abnormal heating state of the circuit breaker, and the more urgent the countermeasures to be taken.

[0097] Through this step, not only can we accurately determine whether the circuit breaker is in an abnormal heating state, but also we can quantitatively evaluate the degree of abnormal heating. This information is of great significance for guiding subsequent fault handling, maintenance decisions and ensuring the stable operation of the power system.

[0098] Although the terms such as temperature rise, inversion, circuit breaker, etc. are used more frequently in this application, the possibility of using other terms is not excluded. These terms are used only to more conveniently describe and explain the essence of the present invention; interpreting them as any additional restrictions is contrary to the spirit of the present invention.

[0099] An embodiment of the present invention provides a method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion. By inputting the sum of the three-phase load rates of the circuit breaker into a parallel inversion model established by using a grid search and support vector machine method in combination with a Spark parallel computing framework, it is possible to judge whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contacts of the circuit breaker output by the parallel inversion model. This method is not only efficient and accurate, but can also comprehensively and accurately evaluate the operating state of the circuit breaker, and can identify the existence of an overheating fault in the first time, which is crucial to ensuring the stable operation of the power system and improving the efficiency of fault handling.

[0100] Embodiment 2

[0101] Please refer to Figure 3 , Figure 3 This is a functional module diagram of a circuit breaker abnormal heating state identification system based on temperature rise inversion provided in Embodiment 2 of the present invention. The system is suitable for executing the circuit breaker abnormal heating state identification method based on temperature rise inversion provided in Embodiment 2 of the present invention. The system specifically includes the following modules:

[0102] A data input module 201 is used to input the sum of the three-phase load factors of the circuit breaker into a parallel inversion model, wherein the parallel inversion model is established by using a grid search and support vector machine method in combination with a Spark parallel computing framework;

[0103] The abnormality judgment module 202 is used to judge whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model.

[0104] An embodiment of the present invention provides a circuit breaker abnormal heating state identification system based on temperature rise inversion. By inputting the sum of the three-phase load rates of the circuit breaker into a parallel inversion model established by using a grid search and support vector machine method in combination with a Spark parallel computing framework, it is possible to judge whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the circuit breaker contacts output by the parallel inversion model. This system is not only efficient and accurate, but can also comprehensively and accurately evaluate the operating state of the circuit breaker, and can identify the existence of an overheating fault in the first time, which is crucial to ensuring the stable operation of the power system and improving the efficiency of fault handling.

[0105] The above system can execute the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0106] Embodiment 3

[0107] Figure 4 A schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention. Figure 4 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 4 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0108] like Figure 4 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0109] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0110] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0111] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0112] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0113] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 22. In addition, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the computer device 12 via a bus 18. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0114] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, for example, implementing the circuit breaker abnormal heating state identification method based on temperature rise inversion provided in the embodiment of the present invention.

[0115] Embodiment 4

[0116] Embodiment 4 of the present invention provides a computer-readable storage medium having computer-executable instructions stored thereon. When the instructions are executed by a processor, a method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion as provided in all the embodiments of the present application is implemented.

[0117] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0118] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0119] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0120] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0121] Finally, it should be noted that although the above embodiments have been described in the specification and drawings of this application, this does not limit the scope of patent protection of this application. All technical solutions generated by replacing or modifying equivalent structures or equivalent processes based on the essential concept of this application using the contents recorded in the specification and drawings of this application, as well as directly or indirectly implementing the technical solutions of the above embodiments in other related technical fields, are included in the scope of patent protection of this application.

Claims

1. A method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion, characterized in that: The method comprises: The sum of the three-phase load rates of the circuit breaker is input into a parallel inversion model, wherein the parallel inversion model is established by using a grid search and support vector machine method in combination with a Spark parallel computing framework; According to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model, it is judged whether the circuit breaker is in an abnormal heating state.

2. The method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion according to claim 1, characterized in that: The method further comprises: Constructing parallel inversion models; The parallel inversion model is trained and tested using a training set and a test set respectively to obtain the trained parallel inversion model.

3. The method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion according to claim 2, characterized in that: The steps of constructing the parallel inversion model are: A parallel inversion model is constructed by using grid search and support vector machine methods combined with the Spark parallel computing framework.

4. The method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion according to claim 2, characterized in that: The method further comprises: The collected sample set of the contact temperature rise of the circuit breaker is divided into a training set and a test set according to a preset ratio; the sample set includes normal operation samples and abnormal heating samples; The normal operating sample is data of the circuit breaker in a normal working state, excluding any abnormal heat source; The abnormal heating samples are data of the circuit breaker under abnormal heating states of different degrees, including different abnormal heating powers under the same load rate.

5. The method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion according to claim 1, characterized in that: The step of judging whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model comprises: Comparing the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model with the actual measured value, and determining whether the actual measured value is higher than the temperature rise inversion value and the deviation exceeds a preset threshold; If yes, it is determined that the circuit breaker is in an abnormal heating state; If not, it is determined that the circuit breaker is in a normal operating state.

6. The method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion according to claim 5, characterized in that: Taking into account the temperature rise inversion error of the contacts of the circuit breaker, the preset threshold is 2.9K.

7. The method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion according to claim 5, characterized in that: After the step of determining that the circuit breaker is in an abnormal heating state, the method further includes: The degree of abnormal heating state of the circuit breaker is determined according to the deviation between the actual measured value and the temperature rise inversion value.

8. A circuit breaker abnormal heating state identification system based on temperature rise inversion, characterized in that: The system comprises: A data input module, used for inputting the sum of the three-phase load factors of the circuit breaker into a parallel inversion model, wherein the parallel inversion model is established by using a grid search and support vector machine method in combination with a Spark parallel computing framework; The abnormality judgment module is used to judge whether the circuit breaker is in an abnormal heating state according to the temperature rise inversion value of the contact of the circuit breaker output by the parallel inversion model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method for identifying an abnormal heating state of a circuit breaker based on temperature rise inversion according to any one of claims 1 to 7 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are executed by a computer processor to implement the method for identifying abnormal heating state of a circuit breaker based on temperature rise inversion as described in any one of claims 1 to 7.

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