Detection method, device, electronic device and storage medium

Abstract

Embodiments of the present application disclose a detection method and device, electronic equipment and a storage medium. The method comprises: obtaining first temperature data and first current data of a switch cabinet contact within a first set time; performing data fitting to obtain a target curve according to historical data, the first temperature data and the first current data; determining a target current value corresponding to a preset temperature threshold according to the target curve, and performing abnormality detection on the first current data according to the target current value. The method can obtain a relationship curve between the temperature of the switch cabinet contact and the current by performing data fitting on the obtained historical data, the first temperature data and the first current data. The target current value corresponding to the preset temperature threshold can be obtained according to the relationship curve, so as to detect whether the first current data is abnormal according to the target current value. Time-consuming, data lag and personnel insecurity caused by manual detection are avoided, and the safety and reliability of the switch cabinet detection are improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of power electronics technology, and in particular to a detection method, device, electronic equipment, and storage medium. Background Art

[0002] High-current switchgear (abbreviated as "switchgear") is an electrical equipment used in power systems. It can be mainly used in key locations such as the transformer low-side and busbars. During peak power consumption periods, the temperature of the switchgear will rise sharply. Abnormal temperature rise (i.e., temperature rise) may cause heating defects in the switchgear, and may even cause explosions, thereby endangering the safety of other power equipment and related personnel, causing large-scale power outages. At present, the traditional working mode for detecting the safety of switchgear is to obtain the temperature changes of the switchgear during operation through manual on-site temperature measurement. However, due to the large number of sites, long distances, and data lags, the relevant operation and maintenance personnel cannot accurately grasp the operating status of the switchgear in real time, and cannot guarantee the safety and reliability of the switchgear power supply. Summary of the Invention

[0003] Embodiments of the present invention provide a detection method, device, electronic device, and storage medium to improve the safety and reliability of switchgear detection.

[0004] According to one aspect of the present invention, a detection method is provided, comprising:

[0005] Acquire first temperature data and first current data of the switch cabinet contact within a first set time;

[0006] Performing data fitting based on the historical data, the first temperature data, and the first current data to obtain a target curve, wherein the target curve is a temperature-current relationship curve, and the historical data is the historical temperature data and the historical current data of the switch cabinet contact acquired and stored before a first set time;

[0007] A target current value corresponding to a preset temperature threshold is determined according to the target curve, and an abnormality detection is performed on the first current data according to the target current value.

[0008] According to another aspect of the present invention, there is provided a detection device comprising:

[0009] An acquisition module, configured to acquire first temperature data and first current data of a switch cabinet contact within a first set time;

[0010] a fitting module configured to perform data fitting to obtain a target curve according to historical data, the first temperature data and the first current data, the target curve being a temperature-current relationship curve, the historical data being historical temperature data and historical current data of the switch cabinet contact acquired and stored before a first setting time;

[0011] a determining module configured to determine a target current value corresponding to a preset temperature threshold according to the target curve, and perform abnormality detection on the first current data according to the target current value.

[0012] According to another aspect of the present application, an electronic device is provided, the electronic device comprising:

[0013] at least one processor; and

[0014] a memory connected to the at least one processor in communication; wherein,

[0015] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the detection method according to any one of the embodiments of the present application.

[0016] According to another aspect of the present application, a computer readable storage medium is provided, the computer readable storage medium stores computer instructions for enabling a processor to perform the detection method according to any one of the embodiments of the present application when executed.

[0017] The technical solution of the embodiments of the present application first acquires first temperature data and first current data of a switch cabinet contact within a first setting time; then performs data fitting to obtain a target curve according to historical data, the first temperature data and the first current data, the target curve being a temperature-current relationship curve, the historical data being historical temperature data and historical current data of the switch cabinet contact acquired and stored before the first setting time; finally, determines a target current value corresponding to a preset temperature threshold according to the target curve, and performs abnormality detection on the first current data according to the target current value. This method can obtain a relationship curve between temperature and current associated with the switch cabinet contact by performing data fitting on the acquired historical data, the first temperature data and the first current data of the switch cabinet contact, and can obtain a target current value corresponding to a preset temperature threshold according to the obtained relationship curve, so as to detect whether the acquired first current data of the switch cabinet contact is abnormal according to the target current value, thereby avoiding problems such as long time consumption, data lag and personnel insecurity caused by manual detection, and improving the safety and reliability of switch cabinet detection.

[0018] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0020] Figure 1 A flow chart of a detection method provided in Example 1 of the present invention;

[0021] Figure 2 A flow chart of a detection method provided in Example 2 of the present invention;

[0022] Figure 3 A schematic diagram of implementing a target curve provided in the second embodiment of the present invention;

[0023] Figure 4 A schematic structural diagram of a detection device provided in Example 3 of the present invention;

[0024] Figure 5 This is a structural diagram of an electronic device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Example 1

[0028] Figure 1 This is a flow chart of a detection method provided in the first embodiment of the present invention. This embodiment is applicable to the case of detecting and processing data sequence in a multi-threaded environment. The method can be executed by a detection device, which can be implemented in the form of hardware and / or software. The detection device can be configured in an electronic device. In this embodiment, the electronic device includes but is not limited to: a server, a computer, a laptop, or a tablet computer. Figure 1 As shown, the method includes:

[0029] S110 : Acquire first temperature data and first current data of a switch cabinet contact within a first set time.

[0030] In this embodiment, a switch cabinet contact may refer to a device in a switch cabinet used to connect or disconnect a circuit. For example, a switch cabinet contact may include a static contact and a movable contact. It is understood that a switch cabinet may include one or more switch cabinet contacts. A first set time may refer to a pre-set time for acquiring switch cabinet contact-related data. For example, the first set time may be one day, two days, or one week, and this is not limited herein. The first temperature data may be understood as the switch cabinet contact temperature value acquired within the first set time. The first current data may be understood as the switch cabinet contact current value acquired within the first set time.

[0031] This embodiment does not specifically limit how to obtain the first temperature data and the first current data of the switch cabinet contact within the first set time.

[0032] In one embodiment, within a first set time, the temperature values ​​and current values ​​of all switch cabinet contacts can be obtained once at fixed intervals (i.e., in this process, one switch cabinet contact corresponds to one temperature value and one current value), and on this basis, all temperature values ​​obtained within the first set time are stored as first temperature data, and all current values ​​obtained within the first set time are stored as first current data.

[0033] In one embodiment, within a first set time, the temperature values ​​and current values ​​of all switch cabinet contacts can be obtained once at fixed intervals; in each acquisition process, a temperature value with the largest value can be selected from all the acquired temperature values ​​as the first temperature value of the time and stored, and the current value corresponding to the temperature value with the largest value (that is, it can be understood as the current value corresponding to the switch cabinet contact corresponding to the temperature value with the largest value) can be selected as the first current value of the time and stored; on this basis, all the stored temperature values ​​and corresponding current values ​​are used as the first temperature data and the first current data.

[0034] S120 : Perform data fitting based on historical data, the first temperature data, and the first current data to obtain a target curve.

[0035] In this embodiment, historical data can be understood as the historical temperature data and historical current data of the switch cabinet contact acquired and stored before the first set time. The historical temperature data can be understood as the temperature value of the switch cabinet contact acquired and stored before the first set time. The historical current data can be understood as the current value of the switch cabinet contact acquired and stored before the first set time. For example, assuming that the first set time is 1 day (such as from 7 am today to 7 am tomorrow is 1 day), it can be understood that the operation of acquiring the first temperature data and first current data of the switch cabinet contact within the first set time will be performed once every day before today, so the corresponding first temperature data and first current data will be stored every day. After the acquisition of this day is completed, the corresponding first temperature data and first current data of the day can be considered as the historical temperature data and historical current data of the day; on this basis, the historical data can be understood as all historical temperature data and historical current data stored before today. There is no limitation on how to acquire historical data here, such as it can be acquired from a database that stores historical data.

[0036] Based on the historical data, the first temperature data, and the first current data, a series of points consisting of temperature values ​​and current values ​​can be determined; data fitting can be understood as the mathematical process of fitting these points into a curve. This embodiment does not specifically limit the method of data fitting; for example, it can be a polynomial fit or a least squares fit. If a polynomial fit is used, the polynomial fit is also not specifically limited here; for example, it can be a cubic polynomial fit or a quartic polynomial fit. The target curve can be understood as the relationship curve between temperature and current.

[0037] Specifically, data fitting is performed based on the historical data, the first temperature data, and the first current data to obtain a relationship curve between the temperature and current of the switch cabinet contact, ie, a target curve.

[0038] For example, the two current values ​​with the largest and smallest current values ​​can be selected from the historical current data and the first current data as a horizontal axis interval (or a vertical axis interval, which is not limited here). Then, all current values ​​within the horizontal axis interval are sampled, such as every 10 amperes (i.e., 10A) as a sampling point to obtain at least one corresponding sampling interval; for each sampling interval, the average of the current values ​​corresponding to the boundary points on both sides of the sampling interval can be used as the horizontal coordinate of the point corresponding to the sampling interval (the average of all historical current data and the first current data falling within the sampling interval can also be used as the horizontal coordinate of the point corresponding to the sampling interval, which is not limited here). Correspondingly, the average of all historical temperature data and the first temperature data falling within the sampling interval can be used as the vertical coordinate of the point corresponding to the sampling interval (the average between the maximum temperature value and the minimum temperature value in all historical temperature data and the first temperature data falling within the sampling interval can also be used as the vertical coordinate of the point corresponding to the sampling interval, which is not limited here). Finally, each sampling interval corresponds to a point, and corresponding data fitting (such as fourth-order polynomial fitting) is performed on all the obtained points to obtain the corresponding target curve, wherein the horizontal axis of the target curve is current and the vertical axis is temperature.

[0039] S130 . Determine a target current value corresponding to a preset temperature threshold according to the target curve, and perform an abnormality detection on the first current data according to the target current value.

[0040] In this embodiment, the preset temperature threshold can be understood as a pre-set temperature threshold used to characterize the temperature safety of the switch cabinet contacts. The specific value of the preset temperature threshold is not limited here and can be flexibly set according to actual needs, such as 85 degrees Celsius (℃) or 90℃, etc.

[0041] Determining the target current value corresponding to the preset temperature threshold based on the target curve can be understood as substituting the preset temperature threshold into the curve formula corresponding to the target curve to obtain a corresponding current value. This obtained current value is the target current value. In other words, the target current value can be understood as the current value corresponding to the temperature value corresponding to the preset temperature threshold in the target curve.

[0042] Based on the obtained target current value, the first current data acquired within the first set time can be detected for abnormal data (i.e., abnormality detection). It is understandable that the target current value corresponding to the preset temperature threshold used to characterize the temperature safety of the switchgear contact can also be used to characterize the safety of the switchgear contact. Therefore, based on the target current value, it can be determined whether there is current data in the first current data that affects the safety of the switchgear contact, and such data can be considered abnormal data.

[0043] Here, there is no specific limitation on how to perform abnormality detection on the first current data based on the target current value. For example, current data in the first current data that is greater than or equal to the target current value can be regarded as abnormal data; or, on the basis of treating current data in the first current data that is greater than or equal to the target current value as abnormal data, current data in the first current data that is less than the target current value and differs from the target current value by a set value can also be regarded as abnormal data (it is understood that even if the current value is less than the target current value, it may affect the safety of the switch cabinet contacts due to being close to the target current value. Therefore, in order to further ensure the safety of the switch cabinet contacts, the current data less than the target current value can also be determined as abnormal data based on the set value). Here, there is no specific limitation on the set value.

[0044] This embodiment provides a detection method, which first obtains first temperature data and first current data of a switch cabinet contact within a first set time; then, based on historical data, the first temperature data, and the first current data, performs data fitting to obtain a target curve, where the target curve is a temperature-current relationship curve, and the historical data is the historical temperature data and historical current data of the switch cabinet contact obtained and stored before the first set time; finally, determines a target current value corresponding to a preset temperature threshold based on the target curve, and performs abnormality detection on the first current data based on the target current value. This method can obtain a relationship curve between temperature and current associated with the switch cabinet contact by performing data fitting on the obtained historical data, the first temperature data, and the first current data of the switch cabinet contact. Based on this relationship curve, a target current value corresponding to the preset temperature threshold can be obtained, so that the obtained first current data of the switch cabinet contact can be detected based on the target current value to determine whether there is an abnormality. This avoids the problems of long time consumption, data lag, and personnel insecurity caused by manual detection, thereby improving the safety and reliability of switch cabinet detection.

[0045] Example 2

[0046] Figure 2 A flow chart of a detection method provided for the second embodiment of the present application is shown in FIG. 2. The second embodiment is based on the first embodiment and is further refined. In the second embodiment, the process of obtaining the first temperature data and the first current data of the switch cabinet contacts within the first set time, fitting the target curve according to the historical data, the first temperature data and the first current data, and detecting the abnormality of the first current data according to the target current value are described in detail. As shown in FIG. 2, the method comprises the following steps. Figure 2

[0047] S210, for each switch cabinet contact, obtaining the second temperature data and the second current data of the switch cabinet contact every second set time within the first set time.

[0048] In the second embodiment, the number of switch cabinet contacts can be at least one. The second set time can refer to the time set in advance for obtaining the temperature value and the current value of the switch cabinet contacts at intervals within the first set time. It can be understood that the second set time is less than the first set time. The specific value of the second set time is not limited here, for example, if the first set time is 1 day, the second set time can be 15 minutes, 1 hour or 2 hours, etc. The second temperature data can refer to the temperature value of the switch cabinet contact obtained every second set time. Correspondingly, the second current data can refer to the current value of the switch cabinet contact obtained every second set time.

[0049] For each switch cabinet contact, the second temperature data and the second current data of the switch cabinet contact can be obtained every second set time within the first set time. Each switch cabinet contact corresponds to one second temperature data and one second current data.

[0050] S220, in each obtaining process, selecting the second temperature data with the largest temperature value from the second temperature data as the first temperature data, and selecting the second current data corresponding to the second temperature data with the largest temperature value as the first current data.

[0051] ​In this embodiment, in each acquisition process (i.e., the process of acquiring the second temperature data and second current data of the switch cabinet contact once every second set time), for all the second temperature data acquired (i.e., the second temperature data corresponding to all the switch cabinet contacts in each acquisition process; if there are 3 switch cabinet contacts, 3 second temperature data can be acquired in each acquisition process), the second temperature data with the largest temperature value is selected from each second temperature data as the first temperature data (e.g., the one with the largest temperature value is selected from the above 3 second temperature data as the first temperature data in this acquisition process), and the second current data corresponding to the second temperature data with the largest temperature value is used as the first current data (e.g., the second current data corresponding to the second temperature data with the largest temperature value selected above is used as the first current data in this acquisition process).

[0052] A first temperature data and a first current data can be determined in each acquisition process. On this basis, the first temperature data and the first current data determined in all acquisition processes can be considered as the first temperature data and the first current data acquired within the first set time.

[0053] S230 : Determine a current range according to the first current data and historical current data.

[0054] In this embodiment, the current interval can be understood as a fixed range determined based on the first current data and the historical current data. Specifically, the maximum current value and the minimum current value in the first current data and the historical current data are determined, and the range between the maximum current value and the minimum current value is used as the current interval.

[0055] Optionally, the current interval is determined based on the first current data and the historical current data, including: taking the current data with the smallest current value in the first current data and the historical current data as the first boundary point; taking the current data with the largest current value in the first current data and the historical current data as the second boundary point; and determining the interval between the first boundary point and the second boundary point as the current interval.

[0056] The first boundary point can be understood as the left boundary point of the current interval, and the second boundary point can be understood as the right boundary point of the current interval. Specifically, the current data with the smallest current value between the first current data and the historical current data can be used as the first boundary point, and the current data with the largest current value between the first current data and the historical current data can be used as the second boundary point. On this basis, the interval between the first boundary point and the second boundary point can be determined as the current interval.

[0057] S240 , sampling is performed according to the set current value within the current interval to obtain at least one sampling interval.

[0058] In this embodiment, the set current value may refer to a pre-set current value for sampling, and the specific numerical value of the set current value is not limited herein. It is understood that the set current value is less than the absolute value of the current difference between the first boundary point and the second boundary point. The sampling interval may be understood as a subinterval obtained by sampling the current interval; it is understood that there is at least one sampling interval, and the sampling interval is smaller than the current interval.

[0059] Specifically, sampling may be performed according to a set current value within the current interval to obtain at least one sampling interval.

[0060] S250 . For each sampling interval, determine the abscissa of a target point corresponding to the sampling interval according to the left boundary point and the right boundary point of the sampling interval, and determine the ordinate of the target point corresponding to the sampling interval according to the first current data and the historical current data falling within the sampling interval.

[0061] In this embodiment, if the sampling interval is [A, B], A can be considered the left boundary point, and B can be considered the right boundary point. It is understood that the left and right boundary points are current values. The target point can refer to a point used to fit the target curve, determined based on the left and right boundary points of the sampling interval. One target point can be determined for each sampling interval.

[0062] For each sampling interval, the horizontal coordinate of the target point corresponding to the sampling interval can be determined according to the left boundary point and the right boundary point of the sampling interval (for example, the average of the left boundary point and the right boundary point can be used as the horizontal coordinate of the target point, or the left boundary point or the right boundary point can be used as the horizontal coordinate of the target point, or the average of all the first current data and the historical current data falling within the sampling interval can be used as the horizontal coordinate of the target point, etc.), and the vertical coordinate of the target point corresponding to the sampling interval can be determined according to the first current data and the historical current data falling within the sampling interval (for example, the average of the temperature data corresponding to the left boundary point and the temperature data corresponding to the right boundary point can be used as the horizontal coordinate of the target point, or the temperature data corresponding to the left boundary point or the right boundary point can be used as the vertical coordinate of the target point, or the average of the first temperature data corresponding to all the first current data falling within the sampling interval and the historical temperature data corresponding to all the historical current data can be used as the vertical coordinate of the target point, etc.).

[0063] Optionally, determining the horizontal coordinate of the target point corresponding to the sampling interval according to the left boundary point and the right boundary point of the sampling interval includes: taking the average of the left boundary point and the right boundary point of the sampling interval as the horizontal coordinate of the target point corresponding to the sampling interval.

[0064] For each sampling interval, the mean value between the left boundary point and the right boundary point of the sampling interval may be used as the abscissa of the target point corresponding to the sampling interval.

[0065] Optionally, the vertical coordinate of the target point corresponding to the sampling interval is determined based on the first current data and the historical current data falling within the sampling interval, including: determining the first temperature data corresponding to the first current data falling within the sampling interval, and the historical temperature data corresponding to the historical current data falling within the sampling interval; and using the average of the determined first temperature data and the historical temperature data as the vertical coordinate of the target point corresponding to the sampling interval.

[0066] For each sampling interval, the first temperature data corresponding to all first current data falling within the sampling interval is determined, as is the historical temperature data corresponding to all historical current data falling within the sampling interval. Based on this, the average of all determined first temperature data and all historical temperature data is used as the vertical coordinate of the target point corresponding to the sampling interval. It is understood that the number of first current data falling within each sampling interval can be the same or different; similarly, the number of historical current data falling within each sampling interval can be the same or different; this determination is based on the actual first current data and historical current data.

[0067] S260 , performing data fitting based on the target points corresponding to each sampling interval to obtain a target curve.

[0068] In this embodiment, a target point may be determined corresponding to each sampling interval, and a target curve may be obtained by performing data fitting based on the target points corresponding to each sampling interval. For example, the data fitting method may be a quartic polynomial fitting.

[0069] S270 , determining a target current value corresponding to a preset temperature threshold according to a target curve.

[0070] In this embodiment, a target current value corresponding to a preset temperature threshold may be determined according to the determined target curve.

[0071] S280 , treating the current data in the first current data that is greater than or equal to the target current value as abnormal data.

[0072] In this embodiment, current data greater than or equal to the target current value in the first current data may be regarded as abnormal data.

[0073] The embodiment two provides a detection method, which specifically realizes the process of obtaining first temperature data and first current data of the switch cabinet contact in a first set time, performing data fitting to obtain a target curve according to historical data, the first temperature data and the first current data, and performing abnormal detection on the first current data according to a target current value. The method can obtain the corresponding target point by processing the data in the historical data, the first temperature data and the first current data, and the target curve of the temperature and the current can be obtained by performing data fitting according to the target point. The target current value corresponding to the preset temperature threshold can be obtained based on the target curve, and the abnormal data in the first current data can be detected through the target current value, so as to avoid the low efficiency of manual detection and improve the safety and efficiency of the switch cabinet detection.

[0074] The application is exemplarily described below.

[0075] The application provides a detection method, which aims to obtain the online temperature measurement data (i.e. the first temperature data) of the high-current switch cabinet and the real-time running current (i.e. the first current data), and realize intelligent prediction of the switch cabinet temperature load curve (the relationship curve of the temperature and the current, i.e. the target curve) by using the polynomial data fitting method, so as to give an early warning, inform the equipment operation and maintenance personnel, intervene early, and improve the power supply reliability.

[0076] Firstly, the online temperature measurement real-time temperature data (i.e. the second temperature data) of the switch cabinet and the real-time running current load data (i.e. the second current data) are obtained every 15 minutes (i.e. the second set time), wherein the temperature of six contacts (e.g. three static contacts and three moving contacts) of a switch cabinet is collected, and the one with the largest temperature value (the largest temperature and the corresponding current load, i.e. the second temperature data with the largest temperature value and the corresponding second current data) is selected and saved. In this way, 96 points of data can be obtained in one day (i.e. the first set time). For example, the data collected at a certain time in one day are as follows: the temperature value and the current value of the upper contact of A are 1 and 10 respectively, the temperature value and the current value of the lower contact of A are 1 and 10 respectively, the temperature value and the current value of the upper contact of B are 2 and 20 respectively, the temperature value and the current value of the lower contact of B are 3 and 30 respectively, the temperature value and the current value of the upper contact of C are 2 and 15 respectively, and the temperature value and the current value of the lower contact of C are 1 and 10 respectively. As can be seen, the temperature value corresponding to the lower contact of B is the largest, so the temperature value and the current value corresponding to the lower contact of B are selected as the final collected data (i.e. the first temperature data and the first current data determined in this process).

[0077] From all the saved historical data (temperature, current, i.e., including historical temperature data and historical current data), as well as the first temperature data and first current data determined on the current day, the minimum and maximum load currents are used as the minimum and maximum interval ranges of the load current statistics (i.e., the current interval), and every 10A (i.e., the set current value) is used as a sampling point to obtain at least one sampling interval.

[0078] The minimum and maximum intervals of the load current are used as the starting and end points of the horizontal axis, the vertical axis is the temperature (in °C), and the horizontal axis is the load current of the switch cabinet (in A). The data of the sampling point (i.e., the target point) is fitted with a fourth-order polynomial to obtain a fitting curve of temperature and load current.

[0079] For example, assuming that among all historical data, first temperature data, and first current data of a switch cabinet, the minimum load current is 500A and the maximum is 1500A, 10A is used as a minimum statistical unit (i.e., sampling is performed at a sampling interval of 10A):

[0080] The sampling interval is 500 <x<510时,对落入该采样区间范围内所有的温度值(即包括历史温度数据和第一温度数据)进行平均值计算得到T1,对采样区间的左边界点(即500)和右边界点(即510)进行平均值计算得到505,在此基础上,最终得到一个点坐标(x,y)为(505,T1),即该采样区间对应的目标点为(505,T1);

[0081] The sampling interval is 510 <x<520时,对落入该采样区间范围内所有的温度值进行平均值计算得到T2,对该采样区间的左边界点(即510)和右边界点(即520)进行平均值计算得到515,最终得到一个点坐标(x,y)为(515,T2),即该采样区间对应的目标点为(515,T2);

[0082] Similarly, by calculating the target points corresponding to all sampling intervals, we can get the target points.

[0083] Figure 3 This is a schematic diagram of a target curve implementation provided by the second embodiment of the present invention. Figure 3 As shown, in actual application, the above method is used to calculate multiple target points based on the acquired data. On this basis, a corresponding target curve can be obtained by fitting the data of a fourth-order polynomial to all target points.

[0084] Based on the target curve fitted using a quartic polynomial, the load current value (i.e., the target current value) corresponding to a temperature of 90°C (i.e., the preset temperature threshold) can be inverted. This target current value is used as the predicted red line value (the red line value can be understood as a benchmark value for judging the safety of the current value) and compared with the offline manually counted red and yellow line ledger, where the yellow line value is 0.85 times the red line value. The red and yellow line values ​​predicted based on real-time operating data are more consistent with the actual situation than the offline manually counted red and yellow line values, which helps to improve the ability of load redundancy control (that is, it can be understood that the predicted red line value obtained according to the method provided by this embodiment is more consistent with the real-time actual situation than the offline manually counted red line value, which can improve the efficiency, accuracy, and safety of switchgear current detection). It should be noted that the early warning rules for switchgear safety are formulated so that when the real-time collected temperature is greater than 80°C, an early warning signal can be generated, including the alarm time and alarm level (such as emergency, major, general), or when the relative temperature difference between the three phases A, B, C, and C is greater than 35%.

[0085] Example 3

[0086] Figure 4 This is a schematic diagram of the structure of a detection device provided in Example 3 of the present invention. Figure 4 As shown, the device includes:

[0087] An acquisition module 310 is configured to acquire first temperature data and first current data of a switch cabinet contact within a first set time;

[0088] a fitting module 320 for performing data fitting based on the historical data, the first temperature data, and the first current data to obtain a target curve, wherein the target curve is a temperature-current relationship curve, and the historical data is the historical temperature data and the historical current data of the switch cabinet contact acquired and stored before a first set time;

[0089] The determination module 330 is configured to determine a target current value corresponding to a preset temperature threshold according to the target curve, and perform anomaly detection on the first current data according to the target current value.

[0090] This third embodiment provides a detection device. First, an acquisition module 310 acquires first temperature data and first current data of a switch cabinet contact within a first set time. Then, a fitting module 320 performs data fitting based on historical data, the first temperature data, and the first current data to obtain a target curve. The target curve is a temperature-current relationship curve. The historical data is the historical temperature data and historical current data of the switch cabinet contact acquired and stored before the first set time. Finally, a determination module 330 determines a target current value corresponding to a preset temperature threshold based on the target curve, and performs abnormality detection on the first current data based on the target current value. The device can obtain a temperature-current relationship curve associated with the switch cabinet contact by performing data fitting on the acquired historical data, the first temperature data, and the first current data of the switch cabinet contact. Based on this relationship curve, a target current value corresponding to the preset temperature threshold can be obtained. The target current value can then be used to detect whether the acquired first current data of the switch cabinet contact is abnormal based on the target current value. This avoids the problems of time-consuming manual detection, data lag, and personnel insecurity, thereby improving the safety and reliability of switch cabinet detection.

[0091] Optionally, the number of the switch cabinet contact is at least one;

[0092] The acquisition module 310 includes:

[0093] An acquiring unit, configured to acquire, for each switch cabinet contact, second temperature data and second current data of the switch cabinet contact once every second set time within a first set time;

[0094] a data determining unit, configured to select, during each acquisition process, second temperature data having the largest temperature value from among the second temperature data as first temperature data, and use second current data corresponding to the second temperature data having the largest temperature value as first current data;

[0095] The second set time is smaller than the first set time.

[0096] Optionally, the fitting module 320 includes:

[0097] a current interval determining unit, configured to determine a current interval based on the first current data and historical current data in the historical data;

[0098] a sampling interval determining unit, configured to perform sampling according to a set current value within the current interval to obtain at least one sampling interval;

[0099] a target point determination unit, configured to determine, for each sampling interval, the abscissa of the target point corresponding to the sampling interval based on the left boundary point and the right boundary point of the sampling interval, and to determine the ordinate of the target point corresponding to the sampling interval based on the first current data and the historical current data falling within the sampling interval;

[0100] The fitting unit is used to perform data fitting based on the target points corresponding to each sampling interval to obtain a target curve.

[0101] Optionally, the current interval determining unit includes:

[0102] a first boundary point determining subunit, configured to use the current data with the smallest current value between the first current data and the historical current data as a first boundary point;

[0103] a second boundary point determining subunit, configured to use the current data with the largest current value between the first current data and the historical current data as a second boundary point;

[0104] The current interval determining subunit is configured to determine an interval between the first boundary point and the second boundary point as a current interval.

[0105] Optionally, the target point determination unit includes:

[0106] The horizontal coordinate determining subunit is configured to use the average of the left boundary point and the right boundary point of the sampling interval as the horizontal coordinate of the target point corresponding to the sampling interval.

[0107] Optionally, the target point determination unit further includes:

[0108] a data determination subunit, configured to determine first temperature data corresponding to first current data falling within the sampling interval, and historical temperature data corresponding to historical current data falling within the sampling interval;

[0109] The ordinate determination subunit is configured to use the average of the determined first temperature data and the historical temperature data as the ordinate of the target point corresponding to the sampling interval.

[0110] Optionally, the determination module 330 includes:

[0111] The abnormal data determining unit is configured to take the current data in the first current data that is greater than or equal to the target current value as abnormal data.

[0112] The detection device provided in the embodiment of the present invention can execute the detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0113] Example 4

[0114] Figure 5 A schematic diagram of the structure of an electronic device provided for embodiment four of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0115] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0116] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0117] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors for running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the detection method.

[0118] In some embodiments, the detection method may be implemented as a computer program that is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method XXX described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the detection method in any other appropriate manner (e.g., by means of firmware).

[0119] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0120] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0121] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0122] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0123] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0124] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0125] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0126] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A detection method, characterized in that: The method comprises: Acquire first temperature data and first current data of the switch cabinet contact within a first set time; Performing data fitting based on the historical data, the first temperature data, and the first current data to obtain a target curve, wherein the target curve is a temperature-current relationship curve, and the historical data is the historical temperature data and the historical current data of the switch cabinet contact acquired and stored before a first set time; The performing data fitting to obtain a target curve based on the historical data, the first temperature data, and the first current data includes: determining a current interval according to the first current data and historical current data in the historical data; Sampling according to a set current value within the current interval to obtain at least one sampling interval; For each sampling interval, determining the abscissa of a target point corresponding to the sampling interval according to the left boundary point and the right boundary point of the sampling interval, and determining the ordinate of the target point corresponding to the sampling interval according to the first current data and the historical current data falling within the sampling interval; Performing data fitting based on the target points corresponding to each sampling interval to obtain a target curve; Determine a target current value corresponding to a preset temperature threshold according to the target curve, and perform abnormality detection on the first current data according to the target current value, including: treating current data in the first current data that is less than the target current value and differs from the target current value by a set value as abnormal data.

2. The method according to claim 1, characterized in that The number of the switch cabinet contacts is at least one; The obtaining of first temperature data and first current data of the switch cabinet contact within a first set time includes: For each switch cabinet contact, obtaining second temperature data and second current data of the switch cabinet contact once every second set time within the first set time; In each acquisition process, the second temperature data with the largest temperature value is selected from each of the second temperature data as the first temperature data, and the second current data corresponding to the second temperature data with the largest temperature value is selected as the first current data; The second set time is smaller than the first set time.

3. The method according to claim 1, characterized in that The determining of the current interval according to the first current data and the historical current data includes: using the current data with the smallest current value between the first current data and the historical current data as a first boundary point; using the current data with the largest current value between the first current data and the historical current data as a second boundary point; An interval between the first boundary point and the second boundary point is determined as a current interval.

4. The method according to claim 1, wherein The determining the horizontal coordinate of the target point corresponding to the sampling interval according to the left boundary point and the right boundary point of the sampling interval includes: The average of the left boundary point and the right boundary point of the sampling interval is used as the horizontal coordinate of the target point corresponding to the sampling interval.

5. The method according to claim 1, wherein The determining the vertical coordinate of the target point corresponding to the sampling interval according to the first current data and the historical current data falling within the sampling interval includes: Determining first temperature data corresponding to first current data falling within the sampling interval, and historical temperature data corresponding to historical current data falling within the sampling interval; The average of the determined first temperature data and the historical temperature data is used as the vertical coordinate of the target point corresponding to the sampling interval.

6. The method according to claim 1, characterized in that The performing abnormality detection on the first current data according to the target current value further includes: Current data greater than or equal to the target current value among the first current data is regarded as abnormal data.

7. A detection device, characterized in that: include: An acquisition module, configured to acquire first temperature data and first current data of a switch cabinet contact within a first set time; a fitting module, configured to perform data fitting based on historical data, the first temperature data, and the first current data to obtain a target curve, wherein the target curve is a temperature-current relationship curve, and the historical data is historical temperature data and historical current data of the switch cabinet contact acquired and stored before a first set time; The fitting module includes: a current interval determining unit, configured to determine a current interval based on the first current data and historical current data in the historical data; a sampling interval determining unit, configured to perform sampling according to a set current value within the current interval to obtain at least one sampling interval; a target point determination unit, configured to determine, for each sampling interval, the abscissa of the target point corresponding to the sampling interval based on the left boundary point and the right boundary point of the sampling interval, and to determine the ordinate of the target point corresponding to the sampling interval based on the first current data and the historical current data falling within the sampling interval; A fitting unit, configured to perform data fitting based on target points corresponding to each sampling interval to obtain a target curve; a determination module, configured to determine a target current value corresponding to a preset temperature threshold according to the target curve, and perform anomaly detection on the first current data according to the target current value; The determining module includes: The abnormal data determining unit is configured to determine, as abnormal data, current data in the first current data that is smaller than the target current value and differs from the target current value by a set value.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor so as to enable the at least one processor to perform the detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the detection method according to any one of claims 1 to 6 when executed.

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