Current cabinet wireless temperature measurement method and system

Abstract

The invention discloses a wireless temperature measurement method and system for a current cabinet, and belongs to the technical field of current cabinet temperature measurement, and the method comprises the steps: carrying out the feature analysis based on the temperature data of the current cabinet to determine the operation state of the current cabinet, and reversely converging the temperature data of the current cabinet based on the operation state of the current cabinet to obtain converged temperature data; current cabinet abnormity types are determined based on the converged temperature data and current cabinet historical data, and arrangement is carried out based on the current cabinet abnormity types to obtain current cabinet operation and maintenance information; an emergency strategy is constructed based on the operation and maintenance information of the current cabinet, and a corresponding operation and maintenance participant responds to the emergency strategy to execute an operation and maintenance action; according to the invention, the problem of poor emergency strategy practicability caused by the fact that the incidence relation between the temperature data of the current cabinet and the topological structure of the current cabinet is not considered in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of current cabinet temperature measurement, and in particular to a current cabinet wireless temperature measurement method and system. Background Art

[0002] With the development of the power system, more and more current cabinets are involved in the control and protection of high-voltage circuits. The high current brought by the high-voltage circuits can easily cause the current cabinets to generate abnormally high temperatures, so it is necessary to monitor the temperature of the current cabinets in real time; and when the temperature of the current cabinet is abnormal and a power outage is required for maintenance, the power outage of some current cabinets will affect other current cabinets or other equipment, especially the power outage of some important current cabinets, which will cause a power outage in an area.

[0003] Chinese patent, publication number: CN114326881A, publication date: April 12, 2022, discloses a temperature and humidity intelligent operation and maintenance system for a substation equipment box, including: a temperature and humidity acquisition terminal, a wireless aggregator, a wireless transceiver and a host computer; the temperature and humidity acquisition terminal is arranged inside the equipment box, for obtaining the temperature and humidity data inside the equipment box, and has a wireless communication function; the wireless aggregator is arranged at a high place away from the ground, for aggregating the wireless signals of the nearby temperature and humidity acquisition terminals and then communicating with the wireless transceiver; the wireless transceiver is arranged on the roof of the monitoring room, and is communicatively connected with the wireless aggregator and the host computer; the host computer is used to obtain the temperature and humidity data collected by the temperature and humidity acquisition terminal; however, the invention only realizes the wireless transmission monitoring of the current cabinet temperature data, and does not consider the correlation between the current cabinet temperature data and the current cabinet topology structure, resulting in the inability to propose suitable emergency strategies during operation and maintenance. Summary of the invention

[0004] The purpose of the present invention is to address the problem that the prior art does not consider the correlation between the temperature data of the current cabinet and the topological structure of the current cabinet, resulting in poor practicality of the emergency strategy; a wireless temperature measurement method and system for a current cabinet are proposed, based on the current cabinet operating status determined by characteristic analysis of the current cabinet temperature data, the current cabinet temperature data is reversely converged to obtain converged temperature data, and then the current cabinet abnormality type is determined based on the converged temperature data and the current cabinet historical data, and an emergency strategy is constructed based on the current cabinet operation and maintenance information sorted by the current cabinet abnormality type, which significantly improves the practicality of the emergency strategy, and the corresponding operation and maintenance participants perform operation and maintenance actions in response to the emergency strategy, which can avoid the chain power outage caused by the current cabinet maintenance.

[0005] In a first aspect, a technical solution provided in an embodiment of the present invention is a method for wireless temperature measurement of a current cabinet, comprising the following steps: Performing feature analysis based on the current cabinet temperature data to determine the current cabinet operation state, and reversely converging the current cabinet temperature data based on the current cabinet operation state to obtain converged temperature data; Determine the abnormal type of the current cabinet based on the aggregated temperature data and the historical data of the current cabinet, and obtain the operation and maintenance information of the current cabinet based on the abnormal type of the current cabinet; An emergency strategy is constructed based on the current cabinet operation and maintenance information, and the corresponding operation and maintenance participants perform operation and maintenance actions in response to the emergency strategy.

[0006] In this solution, feature analysis is performed based on the temperature data of the current cabinet. The characteristics of the temperature data of the current cabinet are deeply analyzed from two directions: the data topology characteristics associated with the topological structure of the current cabinet and the temperature characteristics associated with the operating time of the current cabinet. Whether the operating status of the current cabinet is abnormal can be accurately judged under complex current cabinet working conditions; the current cabinet temperature data is reversely converged according to the operating status of the current cabinet to obtain converged temperature data, and abnormal temperature data and normal temperature data can be distinguished according to the operating status of the current cabinet, and then the computing resources can be reasonably allocated according to the positive and negative ratios of the temperature data, so that the converged temperature data can be combined with the historical data of the current cabinet to determine the abnormal type of the current cabinet, and then the corresponding current cabinet operation and maintenance information can be sorted out according to the causes of the abnormal types of the current cabinet, and emergency strategies for the real-time operating status, real-time working conditions, and working environment of the current cabinet are established, which significantly improves the practicality of the emergency strategies, and the corresponding operation and maintenance participants perform operation and maintenance actions in response to the emergency strategies, which can avoid the chain power outage caused by the maintenance of the current cabinet.

[0007] Preferably, the specific process of determining the operating state of the current cabinet by performing feature analysis based on the current cabinet temperature data is as follows: Preprocess the current cabinet temperature data to obtain complete data and data topology features, and calculate temperature features based on the time scale of the complete data and the complete data; The operating status of the current cabinet is judged based on the data topology characteristics and temperature characteristics. If the temperature characteristic is less than the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be normal. If the temperature characteristic is equal to the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be critical. If the temperature characteristic is greater than the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be abnormal.

[0008] In this solution, when the current cabinet is abnormal due to different reasons, the change characteristics of the corresponding current cabinet temperature data are different, and the temperature data collected at different nodes in the current cabinet topology structure also have different change characteristics. The operating status of the current cabinet is judged based on the temperature characteristics and the temperature change threshold corresponding to the data topology characteristics, and the data topology characteristics are directly related to the current cabinet topology structure. The abnormal cause of the current cabinet and the current cabinet topology structure can be integrated as conditions in the judgment process of the operating status of the current cabinet, effectively improving the accuracy of the judgment of the operating status of the current cabinet.

[0009] Preferably, the specific process of preprocessing the current cabinet temperature data to obtain complete data and data topology features is: The current cabinet temperature data is statistically analyzed based on the statistical method to obtain abnormal values ​​and missing values, and the data corresponding to the abnormal values ​​in the current cabinet temperature data are deleted to obtain the missing data; The data corresponding to the missing values ​​in the missing data are filled based on the linear interpolation method to obtain complete data; Data labels are established based on the current cabinet topology structure and the current cabinet temperature data acquisition source, and data topology features are constructed based on the corresponding relationship between the data labels and the complete data.

[0010] Preferably, the temperature feature calculation formula corresponding to the temperature feature calculated based on the time scale of the complete data and the complete data is specifically: Where A is the temperature characteristic, t1 is the start time of the current cabinet temperature data collection, t2 is the end time of the current cabinet temperature data collection, t is the collection period of the current cabinet temperature data, and f(t) is the trend function of the current cabinet temperature data changing with time.

[0011] Preferably, before executing the method of judging the operating state of the current cabinet based on the data topology characteristics and the temperature characteristics, the method further includes: Establishing a temperature topology feature based on the data topology feature and the corresponding relationship between the temperature feature and the complete data, and selecting a temperature change threshold based on the temperature topology feature; The temperature change threshold is matched with the temperature characteristic, and after the matching is completed, the operation state of the current cabinet is determined based on the temperature change threshold and the temperature characteristic.

[0012] In this scheme, in view of the fact that the data topology characteristics are directly related to the complete data, a correspondence between the temperature characteristics and the data topology characteristics can be established based on the correspondence between the data topology characteristics and the temperature characteristics and the complete data, that is, the temperature topology characteristics. Combined with the fact that the data topology characteristics are directly related to the current cabinet topology structure, the temperature topology characteristics essentially characterize the association between the temperature characteristics and the current cabinet topology structure, and then the temperature change threshold for different nodes of the current cabinet topology structure can be selected according to the temperature topology characteristics.

[0013] Preferably, the specific process of reversely converging the current cabinet temperature data based on the current cabinet operation state to obtain the converged temperature data is: Determine the urgency of the current cabinet temperature data based on the current cabinet operation status, and select a current cabinet temperature data aggregation method based on the urgency to obtain active aggregation data and passive aggregation data; Based on the active converged data and the passive converged data, the data topology features corresponding to the current cabinet temperature data are classified to obtain active data topology features and passive data topology features; The active converged data, the passive converged data, the active data topological features and the passive data topological features are sorted to obtain converged temperature data.

[0014] In this scheme, after the operating status of the current cabinet is determined, the urgency of the current cabinet temperature data corresponding to the abnormal operating status current cabinet that needs to be repaired is marked as the first level urgency, the urgency of the current cabinet temperature data corresponding to the critical operating status current cabinet that needs to be observed is marked as the second level urgency, and the urgency of the current cabinet temperature data corresponding to the normal operating status current cabinet that does not require additional processing is marked as the third level urgency, wherein the first level urgency and the second level urgency correspond to the actively triggered aggregation method, and the third level urgency corresponds to the passive polling aggregation method, and the current cabinet temperature data aggregated by the actively triggered aggregation method is marked as actively aggregated data, and the current cabinet temperature data aggregated by the passive polling aggregation method is marked as passively aggregated data, which can ensure that the urgent data, that is, the temperature data corresponding to the abnormal operating status current cabinet and the critical operating status current cabinet can be processed first, and the data topology structure is classified, so that the current cabinet topology information corresponding to the urgent data can be obtained, which supports the subsequent construction of emergency strategies.

[0015] Preferably, the specific process of determining the abnormal type of the current cabinet based on the converged temperature data and the current cabinet historical data is: Based on the active data topological features and passive data features in the converged temperature data, the current cabinet historical data is classified to obtain active historical data and passive historical data; Based on the active historical data and the active converged data in the converged temperature data, the growth rate analysis is performed to obtain the active growth rate feature, and based on the active data topological feature in the converged temperature data, the active growth rate feature is located to obtain the active growth rate position; Based on the passive historical data and the passive converged data in the converged temperature data, the passive acceleration feature is analyzed to obtain the passive acceleration feature, and based on the passive data topological feature in the converged temperature data, the passive acceleration feature is located to obtain the passive acceleration position; The abnormality type of the current cabinet is determined based on the active speed-up characteristics, the active speed-up position, the passive speed-up characteristics and the passive speed-up position.

[0016] In this scheme, by comparing the active converged data with the active historical data of the same historical period, and comparing the passive converged data with the passive historical data of the same historical period, the change trend and change speed of the converged temperature data compared with the current cabinet historical data, that is, the active growth rate feature and the passive growth rate feature, can be obtained. The comparison, that is, the growth rate analysis can be drawn to fit the corresponding data curve; then, based on the data topological features in the converged temperature data, the active growth rate feature and the passive growth rate feature are located to obtain the specific positions of the active growth rate feature and the passive growth rate feature in the current cabinet topological structure, that is, the active growth rate position and the passive growth rate position; finally, based on the active growth rate feature, the active growth rate position, the passive growth rate feature and The passive speed increase position determines the type of current cabinet abnormality. If the active speed increase characteristics and the passive speed increase characteristics show an upward trend, and the position with a fast change speed, that is, the active speed increase position and the passive speed increase position are concentrated, it is determined that the current cabinet may have problems such as poor contact, overload, and poor heat dissipation. If the active speed increase characteristics and the passive speed increase characteristics show a steady upward trend, it is determined that the current cabinet may have problems such as equipment aging and reduced insulation performance. If the active speed increase characteristics and the passive speed increase characteristics show a downward trend, or even exceed the lowest bit of the historical data, it is determined that the current cabinet may have problems such as low voltage and power outage. If the active speed increase characteristics and the passive speed increase characteristics show that the trend of change is unstable for a long time, it is determined that the voltage of the current cabinet is unstable.

[0017] Preferably, the specific process of obtaining the current cabinet operation and maintenance information by sorting out the abnormal types of the current cabinet is as follows: determining the operation and maintenance equipment and operation and maintenance personnel based on the abnormal types of the current cabinet and the current cabinet related information database, and extracting the active speed-up position and the passive speed-up position corresponding to the abnormal types of the current cabinet; Based on the active speed-up position and the passive speed-up position, corresponding current cabinet topology information is acquired, and the current cabinet topology information is matched with operation and maintenance equipment and operation and maintenance personnel to obtain current cabinet operation and maintenance information.

[0018] In this solution, in order to avoid power outages in other current cabinets or related circuits when the current cabinet is shut down for maintenance, the specific operation and maintenance personnel and the operation and maintenance equipment are identified, and an alternative circuit is formed through the operation and maintenance equipment to isolate the current cabinet. The operation and maintenance equipment includes at least a switch and a backup current cabinet, and the backup current cabinet can be a current cabinet in normal operating state.

[0019] Preferably, the specific process of constructing an emergency strategy based on the current cabinet operation and maintenance information is as follows: Establishing a crisis degree of the current cabinet based on the abnormality type corresponding to the current cabinet in the current cabinet operation and maintenance information, and determining a topological crisis area based on the crisis degree and the current cabinet topology information in the current cabinet operation and maintenance information; Crisis correlation characteristics are determined based on the current path and topological crisis area corresponding to the current cabinet topology information, and operation and maintenance equipment and operation and maintenance personnel in the current cabinet operation and maintenance information are classified and sorted based on the crisis correlation characteristics to obtain an emergency strategy.

[0020] In this scheme, when the temperature of the current cabinet is abnormal, due to its cascading power outage characteristics, it will also cause temperature abnormalities in other current cabinets. In order to reduce the troubleshooting time of operation and maintenance, the topological crisis area is first determined based on the crisis degree established based on the abnormal type of the current cabinet and the current cabinet topology information, and then the crisis correlation characteristics are determined based on the topological crisis area and the corresponding current cabinet current path, and the current cabinets that are mutually affected are clearly identified; secondly, since the operation and maintenance managers and operation and maintenance equipment in different areas are different, when the areas that need to be repaired are related, the operation and maintenance managers and operation and maintenance equipment in the related topological crisis areas need to cooperate with each other, so it is necessary to classify and sort the operation and maintenance equipment and operation and maintenance personnel based on the crisis correlation characteristics to obtain an emergency strategy.

[0021] On the other hand, a technical solution also provided in an embodiment of the present invention is a current cabinet wireless temperature measurement system, comprising: a wireless transceiver, a wireless convergence device, and an information management device; The wireless transceiver performs feature analysis on the acquired current cabinet temperature data and sends it to the wireless convergence device in a passive polling or active triggering manner; The wireless convergence device determines the abnormal type of the current cabinet based on the historical data of the current cabinet and the temperature data of the current cabinet sent by the wireless transceiver, and reports the abnormal type of the current cabinet to the information management device; The information management device constructs an emergency strategy based on the reported abnormality type of the current cabinet.

[0022] Beneficial effects of the present invention: (1) The present application can accurately judge the operating status of the current cabinet under complex working conditions by performing feature analysis on the temperature data of the current cabinet, and reversely converge the temperature data of the current cabinet based on the operating status of the current cabinet to obtain converged temperature data, and can distinguish abnormal temperature data from normal temperature data according to the operating status of the current cabinet, and then reasonably allocate computing resources according to the positive and negative ratios of the temperature data, so that the converged temperature data can be combined with the historical data of the current cabinet to determine the abnormal type of the current cabinet, and then the corresponding current cabinet operation and maintenance information can be sorted out according to the cause of the abnormal type of the current cabinet, and an emergency strategy for the real-time operating status, real-time working conditions, and working environment of the current cabinet is established, which significantly improves the practicality of the emergency strategy, and the corresponding operation and maintenance participants respond to the emergency strategy to perform operation and maintenance actions, which can avoid the chain power outage caused by the maintenance of the current cabinet; (2) This application first determines the topological crisis area based on the crisis degree established by the abnormal type of the current cabinet and the current cabinet topology information, and then determines the crisis correlation characteristics based on the topological crisis area and the corresponding current cabinet current path, and clarifies the current cabinets that are mutually related and affected; secondly, since the operation and maintenance managers and operation and maintenance equipment in different areas are different, when the areas that need to be repaired are related, the operation and maintenance managers and operation and maintenance equipment in the related topological crisis areas need to cooperate with each other. Therefore, it is necessary to classify and sort the operation and maintenance equipment and operation and maintenance personnel based on the crisis correlation characteristics to obtain an emergency strategy, which significantly improves the scientific nature of the emergency strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0024] Figure 1 It is a flow chart of a method for wireless temperature measurement of a current cabinet; Figure 2 The figure is a structural diagram of a current cabinet wireless temperature measurement system. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the operations (or steps) as sequential processes, many of the operations (or steps) therein can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the drawings; the process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0027] Embodiment 1: like Figure 1 As shown, this embodiment provides a current cabinet wireless temperature measurement method, including the following steps: Performing feature analysis based on the current cabinet temperature data to determine the current cabinet operation state, and reversely converging the current cabinet temperature data based on the current cabinet operation state to obtain converged temperature data; Determine the abnormal type of the current cabinet based on the aggregated temperature data and the historical data of the current cabinet, and obtain the operation and maintenance information of the current cabinet based on the abnormal type of the current cabinet; An emergency strategy is constructed based on the current cabinet operation and maintenance information, and the corresponding operation and maintenance participants perform operation and maintenance actions in response to the emergency strategy.

[0028] In this embodiment, the operating state of the current cabinet is usually affected by its load current, electrical components, and working environment, and the change in the operating state of the current cabinet will cause its temperature to change accordingly. Therefore, feature analysis can be performed based on the current cabinet temperature data. The characteristics of the current cabinet temperature data can be deeply analyzed from two directions: the data topology characteristics associated with the current cabinet topology structure and the temperature characteristics associated with the current cabinet operating time, to determine the operating state of the current cabinet under complex working conditions and environments; secondly, the number of current cabinets is related to actual needs. There may be only one current cabinet or there may be many current cabinets, which leads to a large volume of current cabinet temperature data. However, more data in the current cabinet temperature data is normal temperature data corresponding to normal current cabinets, which is of limited help in the formulation of emergency strategies. At this time, the current cabinet temperature data is reversely converged according to the determined operating state of the current cabinet. The abnormal data and normal data in the temperature data can be distinguished according to the operating state of the current cabinet, and more computing resources can be selectively allocated to the abnormal data; at this time, only the abnormal current cabinet and the corresponding abnormal data characteristics are known. The same abnormal data feature may have multiple different causes. For example, when the temperature of the current cabinet rises steadily, the abnormal data feature shows that the temperature value is getting higher and higher in a certain period of time. The possible causes include serious dust accumulation in the current cabinet, poor ventilation, and radiator failure. In order to further determine the cause of the current cabinet abnormality, the current cabinet historical data can be compared with the temperature data, and the difference between the historical data change trend and the temperature data change trend can be analyzed to determine the type of current cabinet abnormality, that is, the most likely cause. Then, the current cabinet operation and maintenance information can be sorted out according to the most likely cause, including at least operation and maintenance personnel, operation and maintenance equipment, etc. However, when the number of current cabinets is large and the covered power lines are large, it is also necessary to consider whether it will cause a chain of power outages when the current cabinet is overhauled. Then, it is necessary to further process the current cabinet operation and maintenance information in combination with the current cabinet topology information to obtain an emergency strategy, which significantly improves the practicality of the emergency strategy; finally, the corresponding operation and maintenance participants respond to the emergency strategy to perform operation and maintenance actions, which can avoid chain power outages caused by current cabinet maintenance.

[0029] The specific process of determining the operating status of the current cabinet by performing feature analysis based on the current cabinet temperature data is as follows: Preprocess the current cabinet temperature data to obtain complete data and data topology features, and calculate temperature features based on the time scale of the complete data and the complete data; The operating status of the current cabinet is judged based on the data topology characteristics and temperature characteristics. If the temperature characteristic is less than the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be normal. If the temperature characteristic is equal to the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be critical. If the temperature characteristic is greater than the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be abnormal.

[0030] The specific process of preprocessing the current cabinet temperature data to obtain complete data and data topology features is: statistically analyzing the current cabinet temperature data based on the statistical method to obtain abnormal values ​​and missing values, and deleting the data corresponding to the abnormal values ​​in the current cabinet temperature data to obtain missing data; The data corresponding to the missing values ​​in the missing data are filled based on the linear interpolation method to obtain complete data; Data labels are established based on the current cabinet topology structure and the current cabinet temperature data acquisition source, and data topology features are constructed based on the corresponding relationship between the data labels and the complete data.

[0031] In this embodiment, in order to introduce the current cabinet topology information in the subsequent analysis process, a data topology feature is established, and when the current cabinet topology structure and the current cabinet temperature data acquisition source remain unchanged, the data topology feature is also fixed. Therefore, the data topology feature can be used to locate abnormal faults and establish a corresponding relationship between historical data and temperature data, thereby effectively improving the accuracy of the analysis.

[0032] The temperature characteristic calculation formula corresponding to the temperature characteristic calculated according to the time scale of the complete data and the complete data is specifically: Where A is the temperature characteristic, t1 is the start time of the current cabinet temperature data collection, t2 is the end time of the current cabinet temperature data collection, t is the collection period of the current cabinet temperature data, and f(t) is the trend function of the current cabinet temperature data changing with time.

[0033] Before executing the method of judging the operating state of the current cabinet based on the data topology characteristics and the temperature characteristics, it also includes: Establishing a temperature topology feature based on the data topology feature and the corresponding relationship between the temperature feature and the complete data, and selecting a temperature change threshold based on the temperature topology feature; The temperature change threshold is matched with the temperature characteristic, and after the matching is completed, the operation state of the current cabinet is determined based on the temperature change threshold and the temperature characteristic.

[0034] In this embodiment, in view of the fact that the data topology feature is directly related to the complete data, a correspondence between the temperature feature and the data topology feature can be established based on the correspondence between the data topology feature and the temperature feature and the complete data, that is, the temperature topology feature. Combined with the fact that the data topology feature is directly related to the current cabinet topology structure, the temperature topology feature essentially characterizes the association between the temperature feature and the current cabinet topology structure, and then the temperature change threshold for different nodes of the current cabinet topology structure can be selected according to the temperature topology feature.

[0035] The specific process of reversely converging the current cabinet temperature data based on the current cabinet operation status to obtain the converged temperature data is: determining the urgency of the current cabinet temperature data based on the current cabinet operation status, and selecting the convergence method of the current cabinet temperature data based on the urgency to obtain active converged data and passive converged data; Based on the active converged data and the passive converged data, the data topology features corresponding to the current cabinet temperature data are classified to obtain active data topology features and passive data topology features; The active converged data, the passive converged data, the active data topological features and the passive data topological features are sorted to obtain converged temperature data.

[0036] In this embodiment, after the operating status of the current cabinet is determined, the urgency of the current cabinet temperature data corresponding to the abnormal operating status current cabinet that needs to be repaired is marked as the first level urgency, the urgency of the current cabinet temperature data corresponding to the critical operating status current cabinet that needs to be observed is marked as the second level urgency, and the urgency of the current cabinet temperature data corresponding to the normal operating status current cabinet that does not require additional processing is marked as the third level urgency, wherein the first level urgency and the second level urgency correspond to the actively triggered aggregation method, and the third level urgency corresponds to the passive polling aggregation method, and the current cabinet temperature data aggregated by the actively triggered aggregation method is marked as actively aggregated data, and the current cabinet temperature data aggregated by the passive polling aggregation method is marked as passively aggregated data, which can ensure that the urgent data, that is, the temperature data corresponding to the abnormal operating status current cabinet and the critical operating status current cabinet can be processed first, and the data topology structure is classified, so that the current cabinet topology information corresponding to the urgent data can be obtained to support the subsequent construction of emergency strategies.

[0037] The specific process of determining the abnormal type of the current cabinet based on the converged temperature data and the current cabinet historical data is as follows: Based on the active data topological features and passive data features in the converged temperature data, the current cabinet historical data is classified to obtain active historical data and passive historical data; Based on the active historical data and the active converged data in the converged temperature data, the growth rate analysis is performed to obtain the active growth rate feature, and based on the active data topological feature in the converged temperature data, the active growth rate feature is located to obtain the active growth rate position; Based on the passive historical data and the passive converged data in the converged temperature data, the passive acceleration feature is analyzed to obtain the passive acceleration feature, and based on the passive data topological feature in the converged temperature data, the passive acceleration feature is located to obtain the passive acceleration position; The abnormality type of the current cabinet is determined based on the active speed-up characteristics, the active speed-up position, the passive speed-up characteristics and the passive speed-up position.

[0038] In this embodiment, by comparing the active converged data with the active historical data of the same historical period, and comparing the passive converged data with the passive historical data of the same historical period, the change trend and change speed of the converged temperature data compared with the current cabinet historical data, that is, the active acceleration feature and the passive acceleration feature, can be obtained. The comparison, that is, the acceleration analysis can be drawn to fit the corresponding data curve; then, based on the data topological features in the converged temperature data, the active acceleration feature and the passive acceleration feature are located to obtain the specific positions of the active acceleration feature and the passive acceleration feature in the current cabinet topological structure, that is, the active acceleration position and the passive acceleration position; finally, based on the active acceleration feature, the active acceleration position and the passive acceleration feature and passive speed-up position to determine the type of current cabinet abnormality. If the active speed-up characteristic and the passive speed-up characteristic show an upward trend and the position with a fast change speed, that is, the active speed-up position and the passive speed-up position are concentrated, then it is determined that the current cabinet may have problems such as poor contact, overload, and poor heat dissipation. If the active speed-up characteristic and the passive speed-up characteristic show a steady upward trend, then it is determined that the current cabinet may have problems such as equipment aging and reduced insulation performance. If the active speed-up characteristic and the passive speed-up characteristic show a downward trend, or even exceed the lowest bit of the historical data, then it is determined that the current cabinet may have problems such as low voltage and power outage. If the active speed-up characteristic and the passive speed-up characteristic show that the trend of change is unstable for a long time, then it is determined that the voltage of the current cabinet is unstable.

[0039] The specific process of obtaining the current cabinet operation and maintenance information by sorting out the abnormal types of the current cabinet is as follows: Determine the operation and maintenance equipment and operation and maintenance personnel based on the abnormal type of the current cabinet and the current cabinet related information database, and extract the active speed-up position and passive speed-up position corresponding to the abnormal type of the current cabinet; Based on the active speed-up position and the passive speed-up position, corresponding current cabinet topology information is acquired, and the current cabinet topology information is matched with operation and maintenance equipment and operation and maintenance personnel to obtain current cabinet operation and maintenance information.

[0040] In this embodiment, in order to avoid power outages in other current cabinets or related circuits when the current cabinet is shut down for maintenance, the specific operation and maintenance personnel are identified while the operation and maintenance equipment is identified, and an alternative circuit is formed by the operation and maintenance equipment to isolate the current cabinet. The operation and maintenance equipment includes at least a switch and a backup current cabinet, and the backup current cabinet can be a current cabinet in normal operating state.

[0041] The specific process of building an emergency strategy based on the current cabinet operation and maintenance information is as follows: Establishing a crisis degree of the current cabinet based on the abnormality type corresponding to the current cabinet in the current cabinet operation and maintenance information, and determining a topological crisis area based on the crisis degree and the current cabinet topology information in the current cabinet operation and maintenance information; Crisis correlation characteristics are determined based on the current path and topological crisis area corresponding to the current cabinet topology information, and operation and maintenance equipment and operation and maintenance personnel in the current cabinet operation and maintenance information are classified and sorted based on the crisis correlation characteristics to obtain an emergency strategy.

[0042] In this embodiment, when a temperature abnormality occurs in a current cabinet, due to its cascading power outage characteristics, it will also cause temperature abnormalities in other current cabinets. In order to reduce the troubleshooting time for operation and maintenance, the topological crisis area is first determined based on the crisis level established based on the type of current cabinet abnormality and the current cabinet topology information, and then the crisis correlation characteristics are determined based on the topological crisis area and the corresponding current cabinet current path, and the current cabinets that are mutually affected are clearly identified; secondly, since the operation and maintenance persons in charge and operation and maintenance equipment in different areas are different, when the areas that need to be repaired are related, the operation and maintenance persons in charge and operation and maintenance equipment in the related topological crisis areas need to cooperate with each other, so it is necessary to classify and sort the operation and maintenance equipment and operation and maintenance personnel based on the crisis correlation characteristics to obtain an emergency strategy.

[0043] On the other hand, Figure 2 As shown, a technical solution also provided in the embodiment of the present invention is that a current cabinet wireless temperature measurement system includes: a wireless transceiver, a wireless convergence device, and an information management device; The wireless transceiver performs feature analysis on the acquired current cabinet temperature data and sends it to the wireless convergence device in a passive polling or active triggering manner; The wireless convergence device determines the abnormal type of the current cabinet based on the historical data of the current cabinet and the temperature data of the current cabinet sent by the wireless transceiver, and reports the abnormal type of the current cabinet to the information management device; The information management device constructs an emergency strategy based on the reported abnormality type of the current cabinet.

[0044] In this embodiment, when the current cabinet temperature data is actively aggregated data, the wireless transceiver sends the data to the wireless aggregation device in an actively triggered manner; when the current cabinet temperature data is passively aggregated data, the wireless transceiver sends the data to the wireless aggregation device in a passive polling manner.

[0045] The wireless transceiver device includes: a collection module, a wired communication module, a radio module, and an antenna; The input end of the wired communication module is electrically connected to the current cabinet temperature measuring device, the output end of the wired communication module is electrically connected to the input end of the acquisition module, the output end of the acquisition module is electrically connected to the input end of the radio module, the output end of the radio module is electrically connected to the antenna, and the antenna serves as the output end of the wireless transceiver and is wirelessly connected to the wireless convergence device.

[0046] The acquisition module includes: a microcontroller, a crystal oscillator, a first capacitor, a second capacitor, a third capacitor, a first resistor, a second resistor, and a third resistor; The oscillation output end of the microcontroller is electrically connected to the first end of the crystal oscillator, the oscillation input end of the microcontroller is electrically connected to the second end of the crystal oscillator, the first end of the first capacitor is electrically connected to the first end of the crystal oscillator, the second end of the first capacitor is grounded, the first end of the second capacitor is electrically connected to the second end of the crystal oscillator, the second end of the second capacitor is grounded, the first end of the third capacitor is electrically connected to the power supply end of the microcontroller, the second end of the third capacitor is electrically connected to the ground end of the microcontroller, the first end of the first resistor is electrically connected to the startup configuration end of the microcontroller, the second end of the first resistor is grounded, the first end of the second resistor is electrically connected to the power supply end of the microcontroller, the second end of the second resistor is electrically connected to the first serial configuration end of the microcontroller, the first end of the third resistor is electrically connected to the power supply end of the microcontroller, the second end of the third resistor is electrically connected to the second serial configuration end of the microcontroller, the input end of the microcontroller is electrically connected to the output end of the wired communication module as the input end of the acquisition module, and the output end of the microcontroller is electrically connected to the input end of the radio module as the output end of the acquisition module.

[0047] The wired communication module includes: a first fuse, a second fuse, a gas discharge tube, a first terminal, a second terminal, a fourth resistor, a fifth resistor, a sixth resistor, a transient voltage suppressor, a fourth capacitor, and a transceiver; the first end of the first fuse is electrically connected to the first end of the first terminal, the second end of the first fuse is electrically connected to the first end of the gas discharge tube, the first end of the second fuse is electrically connected to the second end of the first terminal, the second end of the second fuse is electrically connected to the second end of the gas discharge tube, the second end of the first fuse is electrically connected to the first end of the fourth resistor, the second end of the fourth resistor is electrically connected to the power supply end of the transceiver, the first end of the fourth resistor is electrically connected to the in-phase transmission end of the transceiver, the second end of the second fuse is electrically connected to the first end of the second terminal, and the second end of the second terminal is electrically connected to the first end of the fourth resistor. The first ends of the five resistors are electrically connected, the second end of the fifth resistor is electrically connected to the first end of the transient voltage suppressor, the first end of the transient voltage suppressor is electrically connected to the in-phase transmission end of the transceiver, the first end of the second wiring terminal is electrically connected to the first end of the sixth resistor, the second end of the sixth resistor is grounded, the first end of the sixth resistor is electrically connected to the second end of the transient voltage suppressor, the second end of the transient voltage suppressor is electrically connected to the inverting transmission end of the transceiver, the third end of the transient voltage suppressor is grounded, the power supply end of the transceiver is electrically connected to the first end of the fourth capacitor, the second end of the fourth capacitor is grounded, the first end of the fourth capacitor is connected to the power supply, the first wiring terminal is electrically connected to the current cabinet temperature measuring device as the input end of the wired communication module, and the output end of the transceiver is electrically connected to the input end of the acquisition module as the output end of the wired communication module.

[0048] The first fuse and the second fuse are both self-recovering fuses.

[0049] The radio module includes: a fifth capacitor, a sixth capacitor, and a wireless communicator; A first end of the fifth capacitor is electrically connected to a power supply end of the wireless communicator, a second end of the fifth capacitor is electrically connected to a ground end of the wireless communicator, a first end of the sixth capacitor is electrically connected to a power supply end of the wireless communicator, a second end of the sixth capacitor is electrically connected to a ground end of the wireless communicator, the power supply end of the wireless communicator is connected to a power source, the ground end of the wireless communicator is grounded, an output end of the wireless communicator is electrically connected to an input end of the radio module as an output end of the acquisition module, and an input end of the wireless communicator is electrically connected to an antenna as an output end of the radio module.

[0050] The wireless convergence device comprises: a convergence module, a radio module, an antenna, and an Ethernet module; The antenna is wirelessly connected to the wireless transceiver device as the input end of the wireless convergence device, the input end of the radio module is electrically connected to the antenna, the output end of the radio module is electrically connected to the input end of the convergence module, the output end of the convergence module is electrically connected to the input end of the Ethernet module, and the output end of the Ethernet module is wirelessly connected to the information management device as the output end of the wireless convergence device.

[0051] The radio module in the wireless convergence device has the same structure as the radio module in the wireless transceiver device, but they are separate radio modules that are not connected to each other.

[0052] The Ethernet module includes: a seventh capacitor, an eighth capacitor, and a network device; The first end of the seventh capacitor is electrically connected to the power supply end of the network device, the second end of the seventh capacitor is electrically connected to the second end of the eighth capacitor, the first end of the eighth capacitor is electrically connected to the power supply end of the network device, the second end of the eighth capacitor is grounded, the power supply end of the network device is connected to the power supply, the ground end of the network device is grounded, the input end of the network device serves as the input end of the Ethernet module and is electrically connected to the output end of the aggregation module, and the output end of the network device serves as the output end of the Ethernet module and is wirelessly connected to the information management device.

[0053] The information management device includes: a manifestation module and a server module; The display module is wirelessly connected to the server module via the MIS intranet, and the server module is wirelessly connected to the wireless convergence device via the MIS intranet.

[0054] This embodiment has at least the following substantial effects: (1) The present application can accurately judge the operating status of the current cabinet under complex working conditions by performing feature analysis on the temperature data of the current cabinet, and reversely converge the temperature data of the current cabinet based on the operating status of the current cabinet to obtain converged temperature data, and can distinguish abnormal temperature data from normal temperature data according to the operating status of the current cabinet, and then reasonably allocate computing resources according to the positive and negative ratios of the temperature data, so that the converged temperature data can be combined with the historical data of the current cabinet to determine the abnormal type of the current cabinet, and then the corresponding current cabinet operation and maintenance information can be sorted out according to the cause of the abnormal type of the current cabinet, and an emergency strategy for the real-time operating status, real-time working conditions, and working environment of the current cabinet is established, which significantly improves the practicality of the emergency strategy, and the corresponding operation and maintenance participants respond to the emergency strategy to perform operation and maintenance actions, which can avoid the chain power outage caused by the maintenance of the current cabinet; (2) This application first determines the topological crisis area based on the crisis degree established by the abnormal type of the current cabinet and the current cabinet topology information, and then determines the crisis correlation characteristics based on the topological crisis area and the corresponding current cabinet current path, and clarifies the current cabinets that are mutually related and affected; secondly, since the operation and maintenance managers and operation and maintenance equipment in different areas are different, when the areas that need to be repaired are related, the operation and maintenance managers and operation and maintenance equipment in the related topological crisis areas need to cooperate with each other. Therefore, it is necessary to classify and sort the operation and maintenance equipment and operation and maintenance personnel based on the crisis correlation characteristics to obtain an emergency strategy, which significantly improves the scientific nature of the emergency strategy.

[0055] The above specific embodiments are preferred embodiments of the present invention, and are not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific embodiments. All equivalent changes made in accordance with the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A wireless temperature measurement method for a current cabinet, characterized in that: The method comprises the following steps: Performing feature analysis based on the current cabinet temperature data to determine the current cabinet operation state, and reversely converging the current cabinet temperature data based on the current cabinet operation state to obtain converged temperature data; Determine the abnormal type of the current cabinet based on the aggregated temperature data and the historical data of the current cabinet, and obtain the operation and maintenance information of the current cabinet based on the abnormal type of the current cabinet; An emergency strategy is constructed based on the current cabinet operation and maintenance information, and the corresponding operation and maintenance participants perform operation and maintenance actions in response to the emergency strategy.

2. A current cabinet wireless temperature measurement method according to claim 1, characterized in that: The specific process of determining the operating status of the current cabinet by performing feature analysis based on the current cabinet temperature data is as follows: Preprocess the current cabinet temperature data to obtain complete data and data topology features, and calculate temperature features based on the time scale of the complete data and the complete data; The operating status of the current cabinet is judged based on the data topology characteristics and temperature characteristics. If the temperature characteristic is less than the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be normal. If the temperature characteristic is equal to the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be critical. If the temperature characteristic is greater than the temperature change threshold corresponding to the data topology characteristic, the operating status of the current cabinet is determined to be abnormal.

3. A current cabinet wireless temperature measurement method according to claim 2, characterized in that: The specific process of preprocessing the current cabinet temperature data to obtain complete data and data topology features is as follows: The current cabinet temperature data is statistically analyzed based on the statistical method to obtain abnormal values ​​and missing values, and the data corresponding to the abnormal values ​​in the current cabinet temperature data are deleted to obtain the missing data; The data corresponding to the missing values ​​in the missing data are filled based on the linear interpolation method to obtain complete data; Data labels are established based on the current cabinet topology structure and the current cabinet temperature data acquisition source, and data topology features are constructed based on the corresponding relationship between the data labels and the complete data.

4. A current cabinet wireless temperature measurement method according to claim 2, characterized in that: The temperature characteristic calculation formula corresponding to the temperature characteristic calculated according to the time scale of the complete data and the complete data is specifically: Where A is the temperature characteristic, t1 is the start time of the current cabinet temperature data collection, t2 is the end time of the current cabinet temperature data collection, t is the collection period of the current cabinet temperature data, and f(t) is the trend function of the current cabinet temperature data changing with time.

5. A current cabinet wireless temperature measurement method according to claim 2, characterized in that: Before executing the method of judging the operating state of the current cabinet based on the data topology characteristics and the temperature characteristics, it also includes: Establishing a temperature topology feature based on the data topology feature and the corresponding relationship between the temperature feature and the complete data, and selecting a temperature change threshold based on the temperature topology feature; The temperature change threshold is matched with the temperature characteristic, and after the matching is completed, the operation state of the current cabinet is determined based on the temperature change threshold and the temperature characteristic.

6. A current cabinet wireless temperature measurement method according to claim 1, characterized in that: The specific process of reversely converging the current cabinet temperature data based on the current cabinet operation status to obtain the converged temperature data is as follows: Determine the urgency of the current cabinet temperature data based on the current cabinet operation status, and select a current cabinet temperature data aggregation method based on the urgency to obtain active aggregation data and passive aggregation data; Based on the active converged data and the passive converged data, the data topology features corresponding to the current cabinet temperature data are classified to obtain active data topology features and passive data topology features; The active converged data, the passive converged data, the active data topological features and the passive data topological features are sorted to obtain converged temperature data.

7. A current cabinet wireless temperature measurement method according to claim 1, characterized in that: The specific process of determining the abnormal type of the current cabinet based on the converged temperature data and the current cabinet historical data is as follows: Based on the active data topological features and passive data features in the converged temperature data, the current cabinet historical data is classified to obtain active historical data and passive historical data; Based on the active historical data and the active converged data in the converged temperature data, the growth rate analysis is performed to obtain the active growth rate feature, and based on the active data topological feature in the converged temperature data, the active growth rate feature is located to obtain the active growth rate position; Based on the passive historical data and the passive converged data in the converged temperature data, the passive acceleration feature is analyzed to obtain the passive acceleration feature, and based on the passive data topological feature in the converged temperature data, the passive acceleration feature is located to obtain the passive acceleration position; The abnormality type of the current cabinet is determined based on the active speed-up characteristics, the active speed-up position, the passive speed-up characteristics and the passive speed-up position.

8. A current cabinet wireless temperature measurement method according to claim 1, characterized in that: The specific process of obtaining the current cabinet operation and maintenance information by sorting out the abnormal types of the current cabinet is as follows: Determine the operation and maintenance equipment and operation and maintenance personnel based on the abnormal type of the current cabinet and the current cabinet related information database, and extract the active speed-up position and passive speed-up position corresponding to the abnormal type of the current cabinet; Based on the active speed-up position and the passive speed-up position, corresponding current cabinet topology information is acquired, and the current cabinet topology information is matched with operation and maintenance equipment and operation and maintenance personnel to obtain current cabinet operation and maintenance information.

9. A current cabinet wireless temperature measurement method according to claim 1, characterized in that: The specific process of building an emergency strategy based on the current cabinet operation and maintenance information is as follows: Establishing a crisis degree of the current cabinet based on the abnormality type corresponding to the current cabinet in the current cabinet operation and maintenance information, and determining a topological crisis area based on the crisis degree and the current cabinet topology information in the current cabinet operation and maintenance information; Crisis correlation characteristics are determined based on the current path and topological crisis area corresponding to the current cabinet topology information, and operation and maintenance equipment and operation and maintenance personnel in the current cabinet operation and maintenance information are classified and sorted based on the crisis correlation characteristics to obtain an emergency strategy.

10. A current cabinet wireless temperature measurement system, characterized in that: Including: wireless transceiver, wireless convergence device, information management device; The wireless transceiver performs feature analysis on the acquired current cabinet temperature data and sends it to the wireless convergence device in a passive polling or active triggering manner; The wireless convergence device determines the abnormal type of the current cabinet based on the historical data of the current cabinet and the temperature data of the current cabinet sent by the wireless transceiver, and reports the abnormal type of the current cabinet to the information management device; The information management device constructs an emergency strategy based on the reported abnormality type of the current cabinet.

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