Electrical cabinet temperature monitoring and alarm method, device, equipment and storage medium

Abstract

The present application discloses a method, device, equipment and storage medium for monitoring and alarming the temperature of an electrical cabinet, which relates to the technical field of electrical equipment, including: collecting temperature images of the equipment inside the electrical cabinet by an infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image; extracting the highest temperatures in multiple preset areas on the infrared temperature image to obtain the highest temperatures in multiple areas; judging whether the highest temperature in each area exceeds the preset fixed alarm threshold of the corresponding preset area, and if so, generating an alarm for exceeding the fixed temperature; calculating the highest temperature of the area using a trend alarm algorithm to obtain a trend quantification value, and judging whether it exceeds the preset trend alarm threshold of the corresponding preset area, and if so, generating an alarm for exceeding the trend temperature. The present application installs an infrared image acquisition device in the electrical cabinet, which can automatically collect the temperature of the equipment in the electrical cabinet, detect temperature exceeding the threshold anomalies and temperature trend anomalies, thereby avoiding major safety accidents.

Description

Technical Field

[0001] The present application relates to the technical field of electrical equipment, and in particular to a method, device, equipment and storage medium for monitoring and alarming the temperature of an electrical cabinet. Background Art

[0002] At present, the temperature monitoring of electrical cabinets mainly relies on manual inspections. First, the temperature is collected manually on site. Then, the collected temperature data is manually analyzed through algorithms to determine whether an alarm is needed. However, due to the high cost of manual input and the long time interval between two inspections, abnormal temperature of the electrical cabinet cannot be discovered in time, which may lead to major safety accidents. In addition, when it is manually determined that an alarm is needed, the equipment in the electrical cabinet has already generated a high temperature. The subsequent cooling measures for the electrical cabinet are carried out under the premise that the equipment in the electrical cabinet has been damaged. In summary, how to effectively monitor the temperature of the electrical cabinet and prevent the electrical cabinet from overheating is a problem that technicians in this field currently need to solve. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide an electrical cabinet temperature monitoring and alarm method, device, equipment, and storage medium that can automatically collect temperature data from equipment within the electrical cabinet, detect temperature threshold anomalies and temperature trend anomalies, thereby avoiding major safety accidents and reducing the workload of manual data analysis and the cost of manual temperature data collection. The specific solution is as follows:

[0004] In a first aspect, the present application discloses a method for monitoring and alarming the temperature of an electrical cabinet, comprising:

[0005] The infrared image acquisition device installed inside the electrical cabinet collects temperature images of various devices inside the electrical cabinet to obtain an infrared temperature image;

[0006] Extracting the highest temperatures in a plurality of preset areas on the infrared temperature image respectively to obtain the maximum temperatures in a plurality of areas;

[0007] Determining whether the maximum temperature of each of the areas exceeds a preset fixed alarm threshold of the corresponding area, and generating an alarm for exceeding the fixed temperature if the threshold is exceeded;

[0008] The maximum temperature of the area is calculated using a preset trend alarm algorithm to obtain a trend quantification value, and it is determined whether the trend quantification value exceeds the preset trend alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the trend temperature is generated.

[0009] Optionally, after extracting the maximum temperatures in multiple preset areas on the infrared temperature image and obtaining the maximum temperatures in multiple areas, the method further includes:

[0010] The maximum temperature is stored in the target database.

[0011] Optionally, the calculating of the maximum temperature of the region by using a preset trend alarm algorithm to obtain a trend quantification value includes:

[0012] Extracting the regional maximum temperature corresponding to the preset area from the target database according to the preset trend alarm time range respectively to obtain historical regional temperature data;

[0013] The historical regional temperature data is calculated using a preset trend alarm algorithm to obtain a trend quantification value.

[0014] Optionally, the calculating of the historical regional temperature data using a preset trend alarm algorithm to obtain a trend quantification value includes:

[0015] Downsampling the temperature data of the historical area according to a preset trend alarm time scale to obtain downsampled temperature data;

[0016] The downsampled temperature data is calculated using a preset trend quantization algorithm to obtain a trend quantization value.

[0017] Optionally, the calculating the downsampled temperature data using a preset trend quantization algorithm to obtain a trend quantization value includes:

[0018] Taking the downsampled temperature data of the time series as input, and performing empirical mode decomposition on the time series to obtain a plurality of intrinsic mode functions;

[0019] Calculating the mean values ​​of a plurality of the intrinsic mode functions to obtain a target sequence of a preset length, and determining an inflection point from the target sequence;

[0020] Adding the intrinsic mode functions greater than the inflection point, and using the result of the addition as a trend term;

[0021] An average slope and a least squares straight line fitting slope of the trend item are calculated, and a trend quantification value for determining whether a trend temperature anomaly exists in the electrical cabinet is calculated using the average slope and the least squares straight line fitting slope.

[0022] Optionally, the intrinsic mode function satisfies a preset condition, wherein the preset condition is that the number of extreme points and the number of zero-crossing points in the time series differ by at most 1, and at any time point, the mean of the upper envelope defined by the local maximum and the lower envelope defined by the local minimum is zero.

[0023] Optionally, the collecting of temperature images of various devices inside the electrical cabinet by an infrared image collection device installed inside the electrical cabinet to obtain an infrared temperature image includes:

[0024] The infrared image acquisition device installed inside the electrical cabinet acquires temperature images of various devices inside the electrical cabinet at preset sampling intervals to obtain an infrared temperature image.

[0025] In a second aspect, the present application discloses an electrical cabinet temperature monitoring and alarm device, comprising:

[0026] A temperature image acquisition module is used to acquire temperature images of various devices inside the electrical cabinet through an infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image;

[0027] A maximum temperature extraction module is used to extract the maximum temperatures in multiple preset areas on the infrared temperature image respectively to obtain the maximum temperatures of multiple areas;

[0028] A fixed alarm threshold judgment module is used to judge whether the maximum temperature of each area exceeds the preset fixed alarm threshold of the corresponding area;

[0029] a fixed temperature anomaly alarm module, configured to generate an alarm indicating that the fixed temperature has exceeded the preset fixed alarm threshold if the maximum temperature of the area exceeds the preset fixed alarm threshold corresponding to the preset area;

[0030] A trend quantification value calculation module, configured to calculate the maximum temperature of the region using a preset trend alarm algorithm to obtain a trend quantification value;

[0031] The trend temperature anomaly alarm module is used to determine whether the trend quantization value exceeds the preset trend alarm threshold of the corresponding area, and if so, generate an alarm for exceeding the trend temperature.

[0032] In a third aspect, the present application discloses an electronic device comprising a processor and a memory; wherein, when the processor executes a computer program stored in the memory, the aforementioned electrical cabinet temperature monitoring and alarm method is implemented.

[0033] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the aforementioned electrical cabinet temperature monitoring and alarm method is implemented.

[0034] It can be seen that the present application first collects the temperature images of each device inside the electrical cabinet through the infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image, and then extracts the highest temperatures in multiple preset areas on the infrared temperature image to obtain the highest temperatures in multiple areas. Then, it is judged whether the highest temperature of each area exceeds the preset fixed alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the fixed temperature is generated. Then, the preset trend alarm algorithm is used to calculate the highest temperature of the area to obtain a trend quantization value, and it is judged whether the trend quantization value exceeds the preset trend alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the trend temperature is generated. The present application installs an infrared image acquisition device in the electrical cabinet, which can automatically collect the temperature of the equipment in the electrical cabinet, detect temperature exceeding the threshold anomalies and temperature trend anomalies, thereby discovering the temperature rising trend earlier, performing manual intervention in advance, avoiding the development of serious safety accidents, and reducing the workload of manual data analysis and the cost of manual temperature data collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0036] Figure 1 This is a flow chart of a temperature monitoring and alarm method for an electrical cabinet disclosed in this application;

[0037] Figure 2 This is a flow chart of a specific electrical cabinet temperature monitoring and alarm method disclosed in this application;

[0038] Figure 3 A specific trend quantification algorithm flow chart disclosed in this application;

[0039] Figure 4 This is a structural diagram of a temperature monitoring and alarm device for an electrical cabinet disclosed in this application;

[0040] Figure 5 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0042] The present application discloses a method for monitoring and alarming the temperature of an electrical cabinet. Figure 1 As shown, the method includes:

[0043] Step S11: collecting temperature images of various devices inside the electrical cabinet by using an infrared image collection device installed inside the electrical cabinet to obtain an infrared temperature image.

[0044] It should be noted that in this embodiment, an infrared image acquisition device, such as an infrared camera, is pre-installed inside the electrical cabinet to capture temperature images of various devices within the cabinet. When the cabinet temperature monitoring alarm is required, the infrared image acquisition device first captures temperature images of various devices within the cabinet to obtain corresponding infrared temperature images. The various devices within the cabinet include, but are not limited to, transformers, circuit breakers, contactors, and current transformers.

[0045] Step S12: extracting the maximum temperatures in a plurality of preset areas on the infrared temperature image respectively to obtain the maximum temperatures in a plurality of areas.

[0046] In this embodiment, after obtaining an infrared temperature image by capturing temperature images of various devices within the electrical cabinet using an infrared image acquisition device installed within the electrical cabinet, the maximum temperature within multiple pre-set regions of the infrared temperature image is further acquired to obtain the corresponding maximum temperatures in multiple regions. The shapes of the pre-set regions include, but are not limited to, rectangles, circles, and other shapes. It should be noted that several regions are pre-set within the infrared image based on the desired range of interest.

[0047] In this embodiment, after extracting the maximum temperatures for the plurality of preset areas on the infrared temperature image and obtaining the maximum temperatures for the plurality of areas, the method may further include storing the maximum temperatures in a target database. Specifically, after obtaining the maximum temperatures for each preset area, the maximum temperatures may be further stored in the database so that temperature data can be directly retrieved from the database during subsequent electrical cabinet temperature monitoring and alarming.

[0048] Step S13: determining whether the maximum temperature of each area exceeds a preset fixed alarm threshold of the corresponding area, and generating an alarm for exceeding the fixed temperature if the maximum temperature exceeds the preset fixed alarm threshold of the corresponding area.

[0049] In this embodiment, after extracting the highest temperatures in multiple preset areas on the infrared temperature image to obtain the highest temperatures in multiple areas, all the preset areas are traversed to determine whether the highest temperature of each of the above areas exceeds the preset fixed alarm threshold of the corresponding area. If the highest temperature of each area exceeds the preset fixed alarm threshold of the corresponding area, a corresponding alarm of exceeding the fixed temperature is generated. It should be pointed out that the monitoring and alarm process is performed separately for each preset area, and each preset area has a separate temperature monitoring parameter. Therefore, when performing temperature monitoring and alarm, the highest temperature in each preset area should be compared with the preset fixed alarm threshold of the corresponding area. If it exceeds the preset fixed alarm threshold of the area, a corresponding alarm message is generated. Among them, the preset fixed alarm threshold refers to a temperature value that exceeds the normal operating temperature of the equipment inside the electrical cabinet.

[0050] Step S14: Calculate the maximum temperature of the area using a preset trend alarm algorithm to obtain a trend quantification value, and determine whether the trend quantification value exceeds the preset trend alarm threshold of the corresponding area. If so, generate an alarm indicating that the trend temperature exceeds the threshold.

[0051] In this embodiment, in addition to determining whether the maximum temperature of each of the areas exceeds the preset fixed alarm threshold of the corresponding area, the preset trend alarm algorithm can also be used to calculate the maximum temperature of the above-mentioned area to obtain a trend quantification value, and then determine whether the above-mentioned trend quantification value exceeds the preset trend alarm threshold of the corresponding area. If the above-mentioned trend quantification value exceeds the preset trend alarm threshold of the corresponding area, an alarm information of exceeding the trend temperature is generated.

[0052] In this embodiment, the use of a preset trend alarm algorithm to calculate the maximum temperature of the area to obtain a trend quantification value may specifically include: extracting the maximum temperature of the area corresponding to the preset area from the target database according to the preset trend alarm time range to obtain historical area temperature data; and calculating the historical area temperature data using the preset trend alarm algorithm to obtain a trend quantification value. Specifically, for any preset rectangular box, the maximum temperature of the area corresponding to the preset area is extracted from the target database according to the preset trend alarm time range to obtain historical area temperature data, and the total number of historical temperature data is recorded as N. For example, if the preset trend alarm time range is 10 days and the preset temperature collection time interval is 10 minutes, a total of 1440 historical area temperature data points can be obtained, that is, N=1440, and the extracted historical area temperature data can be recorded as y i , i=0,1,...,1439. Then, the preset trend alarm algorithm is used to analyze the above historical regional temperature data y i Calculate and obtain the trend quantitative value.

[0053] It can be seen that the embodiment of the present application first collects the temperature images of each device inside the electrical cabinet through the infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image, and then extracts the highest temperatures in multiple preset areas on the infrared temperature image to obtain the highest temperatures of multiple areas. Then, it is judged whether the highest temperature of each area exceeds the preset fixed alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the fixed temperature is generated. Then, the preset trend alarm algorithm is used to calculate the highest temperature of the area to obtain a trend quantization value, and it is judged whether the trend quantization value exceeds the preset trend alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the trend temperature is generated. The embodiment of the present application installs an infrared image acquisition device in the electrical cabinet, which can automatically collect the temperature of the equipment in the electrical cabinet, detect temperature exceeding the threshold anomalies and temperature trend anomalies, thereby discovering the temperature rising trend earlier, performing manual intervention in advance, avoiding the development of serious safety accidents, and reducing the workload of manual data analysis and the cost of manual temperature data collection.

[0054] The present application discloses a specific electrical cabinet temperature monitoring and alarm method, see Figure 2 As shown, the method includes:

[0055] Step S21: The infrared image acquisition device installed inside the electrical cabinet acquires temperature images of various devices inside the electrical cabinet at preset sampling intervals to obtain an infrared temperature image.

[0056] In this embodiment, the infrared image acquisition device installed inside the electrical cabinet can collect temperature images of each device inside according to a preset sampling interval, for example, collecting the temperature image of the device once every minute or once every hour, and then obtain the collected infrared temperature image.

[0057] Step S22: extracting the highest temperatures in multiple preset areas on the infrared temperature image respectively to obtain the highest temperatures in multiple areas.

[0058] In this embodiment, after obtaining an infrared temperature image by collecting temperature images of each device inside the electrical cabinet at a preset sampling interval through an infrared image acquisition device installed inside the electrical cabinet, multiple preset areas on all the infrared temperature images are traversed, and the highest temperatures within the preset areas are extracted one by one to obtain the corresponding maximum temperatures of multiple areas.

[0059] Step S23: storing the maximum temperature in the target database.

[0060] Step S24: determining whether the maximum temperature of each area exceeds a preset fixed alarm threshold of the corresponding area, and generating an alarm for exceeding the fixed temperature if the maximum temperature exceeds the preset fixed alarm threshold of the corresponding area.

[0061] Step S25: extracting the regional maximum temperature corresponding to the preset area from the target database according to the preset trend alarm time range, obtaining historical regional temperature data, and downsampling the historical regional temperature data according to the preset trend alarm time scale to obtain downsampled temperature data.

[0062] In this embodiment, after the maximum temperature is stored in the target database, the regional maximum temperature corresponding to the preset area is extracted from the above target database according to the preset trend alarm time range, that is, all the preset areas are traversed to obtain the corresponding historical regional temperature data, and then the above historical regional temperature data is downsampled according to the preset trend alarm time scale to obtain the downsampled temperature data. For example, if the preset trend alarm time range is 10 days and the preset temperature collection time interval is 10 minutes, a total of 1440 historical regional temperature data points can be obtained, that is, the total number of temperature data points N = 1440, and the extracted historical regional temperature data can be recorded as y i , i=0,1,...,1439. Then, the above historical regional temperature data is downsampled according to the preset trend alarm time scale, such as the preset temperature collection interval is t, the preset time scale is t scale , and t scale Greater than or equal to t, the calculation formula for the downsampling interval is:

[0063]

[0064] It should be pointed out that at this time t scale The units of and t need to be converted to seconds. The number of points retained after downsampling is Where floor means rounding down. The temperature data sequence x after downsampling i It can be obtained by the following formula:

[0065] x i =y [c*j] , j = 0, 1, ..., M-1;

[0066] Where [c*j] means rounding after multiplication.

[0067] Step S26: Calculate the downsampled temperature data using a preset trend quantization algorithm to obtain a trend quantization value, and determine whether the trend quantization value exceeds a preset trend alarm threshold of the corresponding area. If so, generate an alarm indicating that the trend temperature exceeds the threshold.

[0068] In this embodiment, after downsampling the historical regional temperature data according to the preset trend alarm time scale to obtain downsampled temperature data, the downsampled temperature data x of the time series is converted into the downsampled temperature data. iAs the input of the preset trend quantification algorithm, a trend quantification value is then output. When the trend quantification value is greater than the preset trend alarm threshold, an alarm of exceeding the trend temperature is generated.

[0069] For details, see Figure 3 As shown, the calculation of the downsampled temperature data using a preset trend quantization algorithm to obtain a trend quantization value may include:

[0070] Step S31: taking the downsampled temperature data of the time series as input, and performing empirical mode decomposition on the time series to obtain a plurality of intrinsic mode functions;

[0071] Step S32: calculating the mean values ​​of a plurality of the intrinsic mode functions to obtain a target sequence of a preset length, and determining an inflection point from the target sequence;

[0072] Step S33: adding the intrinsic mode functions greater than the inflection point, and taking the result of the addition as a trend term;

[0073] Step S34: calculating the average slope and the least squares straight line fitting slope of the trend item, and using the average slope and the least squares straight line fitting slope to calculate a trend quantization value for determining whether there is a trend temperature anomaly in the electrical cabinet.

[0074] For example, execute step S31: convert the downsampled temperature data x of the time series into i As the input of the preset trend quantification algorithm, where i = 0, 1, ..., M-1, and it is recorded as vector X, then the time series x is transformed into i Decomposed into the sum of n intrinsic mode functions (IMF, Intrinsic Mode Functions), the calculation formula of vector X is:

[0075]

[0076] Among them, vector X n The nth intrinsic mode function is represented by the vector R, and the decomposition residual is represented by the vector R. Specifically, the process of the empirical mode decomposition may include: ① initializing n=1, R0=X; ② extracting the nth intrinsic mode function by the following steps: a. Let H=R n-1 , k = 1; b. Extract H k-1 The local maximum and local minimum of H; c. Use the cubic spline curve to calculate the local maximum and local minimum of H k-1 Interpolate the local maximum value of the upper envelope U k-1 , interpolate the local minimum to get the lower envelope L k-1; d. Calculate the mean M of the upper and lower envelopes k-1 =0.5*(U k-1 +L k-1 );e、remember H k =H k-1 -M k-1 If H k If the two conditions of the eigenmode function are met, then let X n =H k And R n =R n-1 -X n If H k If the eigenmode function condition is not met, set k = k + 1 and jump to step b. Further, if R n If n is a constant or monotonically increasing, the trend quantification algorithm is stopped; otherwise, n=n+1 is set and the process jumps to step ②.

[0077] Through the above steps, the original time series x i It is decomposed into several intrinsic mode functions, which include different components in the time series.

[0078] It should be noted that the intrinsic mode function satisfies a preset condition, wherein the preset condition is that the number of extreme points and the number of zero-crossing points in the time series differ by at most 1, and at any point in time, the mean of the upper envelope defined by the local maximum and the lower envelope defined by the local minimum are zero. In other words, the intrinsic mode function satisfies the following two conditions: the number of extreme points and the number of zero-crossing points in the sequence differ by at most 1; and at any point in time, the mean of the upper envelope defined by the local maximum and the lower envelope defined by the local minimum are zero.

[0079] Further, step S32 is executed: the original time series x i After decomposing into n intrinsic mode functions, calculate the mean of these n intrinsic mode functions and record the mean as IMF mean , among which, IMF mean Is a sequence of length n, and there is an inflection point, then retrieve IMF mean The inflection point subscript k in the , wherein the values ​​less than or equal to the subscript k and the values ​​greater than the subscript k have obvious differences, and then step S33 is executed: the intrinsic mode functions greater than the subscript k are added together as the extracted trend term. Specifically, the calculation process of the trend term includes: (1) initializing the subscript k and initializing the array D to be empty; (2) calculating the IMF mean The subsequences with subscripts less than k are fitted with the least squares straight line to obtain the fitted value, and the fitting error is recorded as E1. meanPerform least squares linear fitting on the subsequences with subscripts greater than or equal to k to obtain the fitted values. The fitting error is recorded as E2, and the total fitting error is E=E1+E2. E is stored in array D. (3) If k=n-2, jump to (4), otherwise jump to (2). (4) The subscript of the minimum value retrieved in array D is marked as j, and the sum of the n intrinsic mode functions with sequence numbers greater than j+2 is used as the extracted trend term, recorded as X trend .

[0080] Finally, step S34 is executed: calculate the above X trend The average slope S1 and the least squares straight line fitting slope S2 are calculated, where S2 refers to the slope of the line fitted by the least squares straight line. The calculation formula for the average slope S1 is:

[0081]

[0082] The final output trend quantization value is: 0.5*(S1+S2).

[0083] For more specific processing procedures of the above steps S22 and S23, reference may be made to the corresponding contents disclosed in the above embodiments, which will not be repeated here.

[0084] It can be seen that the embodiment of the present application installs an infrared image acquisition device in the electrical cabinet, which can perform high-frequency temperature acquisition on the equipment in the electrical cabinet, and can automatically detect temperature exceeding the threshold value and temperature trend abnormalities, thereby avoiding major safety accidents; and since there is no need for manual on-site temperature acquisition, the cost of manual temperature data acquisition can be reduced; furthermore, since data can be automatically collected and analyzed, and an algorithm is used to determine whether an alarm is needed, there is no need to manually pull historical data for manual analysis, so the present application reduces the workload of manual data analysis; at the same time, the embodiment of the present application improves the reliability of the temperature monitoring alarm of the electrical cabinet, and can perform higher-frequency temperature acquisition, timely detect temperature mutations and issue alarms, avoiding sudden accidents that may be caused by a long interval between two acquisitions during manual inspections; in addition, in addition to the threshold alarm, the embodiment of the present application also realizes automatic trend alarm. When the threshold alarm is not triggered, long-term trend alarm judgment can be performed, and the temperature rising trend can be discovered earlier, and manual intervention can be performed in advance to avoid the development of serious accidents.

[0085] Correspondingly, the embodiment of the present application also discloses an electrical cabinet temperature monitoring and alarm device, see Figure 4 As shown, the device includes:

[0086] The temperature image acquisition module 11 is used to acquire temperature images of various devices inside the electrical cabinet through an infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image;

[0087] A maximum temperature extraction module 12 is used to extract the maximum temperatures in multiple preset areas on the infrared temperature image to obtain the maximum temperatures of multiple areas;

[0088] A fixed alarm threshold determination module 13 is used to determine whether the maximum temperature of each area exceeds a preset fixed alarm threshold of the corresponding area;

[0089] A fixed temperature abnormality alarm module 14 is configured to generate an alarm indicating that the fixed temperature has exceeded the preset fixed alarm threshold if the maximum temperature of the area exceeds the preset fixed alarm threshold corresponding to the preset area;

[0090] a trend quantification value calculation module 15, configured to calculate the maximum temperature of the region using a preset trend alarm algorithm to obtain a trend quantification value;

[0091] The trend temperature abnormality alarm module 16 is used to determine whether the trend quantization value exceeds a preset trend alarm threshold of the corresponding area, and if so, generate an alarm indicating that the trend temperature exceeds the preset trend alarm threshold.

[0092] Among them, the specific work processes of the above modules can refer to the corresponding contents disclosed in the aforementioned embodiments, which will not be repeated here.

[0093] It can be seen that in the embodiment of the present application, the temperature images of each device inside the electrical cabinet are first collected by the infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image, and then the highest temperatures in multiple preset areas on the infrared temperature image are extracted respectively to obtain the highest temperatures of multiple areas. Then, it is judged whether the highest temperature of each area exceeds the preset fixed alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the fixed temperature is generated. Then, the preset trend alarm algorithm is used to calculate the highest temperature of the area to obtain a trend quantization value, and it is judged whether the trend quantization value exceeds the preset trend alarm threshold of the corresponding area. If it exceeds, an alarm of exceeding the trend temperature is generated. The embodiment of the present application installs an infrared image acquisition device in the electrical cabinet, which can automatically collect the temperature of the equipment in the electrical cabinet, detect temperature exceeding the threshold anomalies and temperature trend anomalies, thereby discovering the temperature rising trend earlier, performing manual intervention in advance, avoiding the development of serious safety accidents, and reducing the workload of manual data analysis and the cost of manual temperature data collection.

[0094] In some specific embodiments, after the maximum temperature extraction module 12, the following steps may also be included:

[0095] The maximum temperature storage unit is used to store the maximum temperature in the target database.

[0096] In some specific embodiments, the trend quantification value calculation module 15 may specifically include:

[0097] a maximum temperature extraction unit, configured to obtain historical regional temperature data from the regional maximum temperature corresponding to the preset region in the target database according to a preset trend alarm time range;

[0098] The first trend quantization value calculation unit is used to calculate the historical regional temperature data using a preset trend alarm algorithm to obtain a trend quantization value.

[0099] In some specific embodiments, the first trend quantification value calculation unit may specifically include:

[0100] A downsampling unit, configured to downsample the temperature data of the historical area according to a preset trend alarm time scale to obtain downsampled temperature data;

[0101] The second trend quantization value calculation unit is used to calculate the downsampled temperature data using a preset trend quantization algorithm to obtain a trend quantization value.

[0102] In some specific embodiments, the second trend quantification value calculation unit may specifically include:

[0103] an empirical mode decomposition unit, configured to take the downsampled temperature data of the time series as input and perform empirical mode decomposition on the time series to obtain a plurality of intrinsic mode functions;

[0104] a mean value calculation unit, configured to calculate the mean values ​​of a plurality of the intrinsic mode functions to obtain a target sequence of a preset length;

[0105] an inflection point determination unit, configured to determine an inflection point from the target sequence;

[0106] an addition calculation unit, configured to add the intrinsic mode functions greater than the inflection point, and use the addition result as a trend term;

[0107] a slope calculation unit, configured to calculate an average slope and a least squares straight line fitting slope of the trend item;

[0108] The third trend quantization value calculation unit is used to calculate a trend quantization value for determining whether there is a trend temperature anomaly in the electrical cabinet by using the average slope and the least squares straight line fitting slope.

[0109] In some specific embodiments, the intrinsic mode function satisfies a preset condition, wherein the preset condition is that the number of extreme points and the number of zero-crossing points in the time series differ by at most 1, and at any time point, the mean of the upper envelope defined by the local maximum and the lower envelope defined by the local minimum is zero.

[0110] In some specific embodiments, the temperature image acquisition module 11 may specifically include:

[0111] The temperature image acquisition unit is used to acquire the temperature image of each device inside the electrical cabinet through the infrared image acquisition device installed inside the electrical cabinet and according to the preset sampling interval to obtain an infrared temperature image.

[0112] Furthermore, the embodiment of the present application also discloses an electronic device, Figure 5 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram should not be considered as any limitation to the scope of application of the present application.

[0113] Figure 5 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps of the electrical cabinet temperature monitoring and alarm method disclosed in any of the aforementioned embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0114] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and the external device. The communication protocol it follows is any communication protocol that can be applied to the technical solution of this application and is not specifically limited here; the input and output interface 25 is used to obtain external input data or output data to the outside world. Its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0115] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or CD, etc. The resources stored thereon can include an operating system 221, a computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0116] The operating system 221 is used to manage and control the hardware devices on the electronic device 20 and the computer program 222. The operating system 221 can be Windows Server, NetWare, Unix, Linux, etc. In addition to including a computer program capable of implementing the electrical cabinet temperature monitoring and alarm method executed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 222 can further include a computer program capable of implementing other specific tasks.

[0117] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when executed by a processor, the computer program implements the aforementioned electrical cabinet temperature monitoring and alarm method. The specific steps of this method can be referred to the corresponding contents disclosed in the aforementioned embodiments and will not be repeated here.

[0118] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and the relevant parts can be referred to the descriptions of the methods.

[0119] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0121] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0122] The above is a detailed introduction to the electrical cabinet temperature monitoring and alarm method, device, equipment and storage medium provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for monitoring and alarming the temperature of an electrical cabinet, characterized in that: include: The infrared image acquisition device installed inside the electrical cabinet collects temperature images of various devices inside the electrical cabinet to obtain an infrared temperature image; Extracting the highest temperatures in a plurality of preset areas on the infrared temperature image respectively to obtain the highest temperatures in a plurality of areas, and storing the highest temperatures in a target database; Determining whether the maximum temperature of each of the areas exceeds a preset fixed alarm threshold of the corresponding area, and generating an alarm for exceeding the fixed temperature if the threshold is exceeded; Extracting the regional maximum temperature corresponding to the preset area from the target database according to the preset trend alarm time range respectively to obtain historical regional temperature data; Downsampling the temperature data of the historical area according to a preset trend alarm time scale to obtain downsampled temperature data; Calculating the downsampled temperature data using a preset trend quantification algorithm to obtain a trend quantification value; It is determined whether the trend quantization value exceeds a preset trend alarm threshold of the corresponding area, and if so, an alarm of exceeding the trend temperature is generated.

2. The electrical cabinet temperature monitoring and alarm method according to claim 1, characterized in that: The method of calculating the downsampled temperature data using a preset trend quantization algorithm to obtain a trend quantization value includes: Taking the downsampled temperature data of the time series as input, and performing empirical mode decomposition on the time series to obtain a plurality of intrinsic mode functions; Calculating the mean values ​​of a plurality of the intrinsic mode functions to obtain a target sequence of a preset length, and determining an inflection point from the target sequence; Adding the intrinsic mode functions greater than the inflection point, and using the result of the addition as a trend term; An average slope and a least squares straight line fitting slope of the trend item are calculated, and a trend quantification value for determining whether a trend temperature anomaly exists in the electrical cabinet is calculated using the average slope and the least squares straight line fitting slope.

3. The electrical cabinet temperature monitoring and alarm method according to claim 2, characterized in that: The intrinsic mode function satisfies a preset condition, wherein the preset condition is that the number of extreme points and the number of zero-crossing points in the time series differ by at most 1, and at any time point, the mean of the upper envelope defined by the local maximum and the lower envelope defined by the local minimum is zero.

4. The electrical cabinet temperature monitoring and alarm method according to any one of claims 1 to 3, characterized in that: The infrared image acquisition device installed inside the electrical cabinet acquires temperature images of various devices inside the electrical cabinet to obtain infrared temperature images, including: The infrared image acquisition device installed inside the electrical cabinet acquires temperature images of various devices inside the electrical cabinet at preset sampling intervals to obtain an infrared temperature image.

5. An electrical cabinet temperature monitoring and alarm device, characterized in that: include: A temperature image acquisition module is used to acquire temperature images of various devices inside the electrical cabinet through an infrared image acquisition device installed inside the electrical cabinet to obtain an infrared temperature image; A maximum temperature extraction module is used to extract the maximum temperatures in multiple preset areas on the infrared temperature image, obtain the maximum temperatures of multiple areas, and store the maximum temperatures in a target database; A fixed alarm threshold judgment module is used to judge whether the maximum temperature of each area exceeds the preset fixed alarm threshold of the corresponding area; a fixed temperature anomaly alarm module, configured to generate an alarm indicating that the fixed temperature has exceeded the preset fixed alarm threshold if the maximum temperature of the area exceeds the preset fixed alarm threshold corresponding to the preset area; A trend quantification value calculation module is used to extract the regional maximum temperature corresponding to the preset area from the target database according to the preset trend alarm time range, and obtain historical regional temperature data; Downsampling the temperature data of the historical area according to a preset trend alarm time scale to obtain downsampled temperature data; Calculating the downsampled temperature data using a preset trend quantification algorithm to obtain a trend quantification value; The trend temperature anomaly alarm module is used to determine whether the trend quantization value exceeds the preset trend alarm threshold of the corresponding area, and if so, generate an alarm for exceeding the trend temperature.

6. An electronic device, characterized in that: It comprises a processor and a memory; wherein, when the processor executes the computer program stored in the memory, it implements the electrical cabinet temperature monitoring and alarm method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that Used to store computer programs; wherein, when the computer program is executed by a processor, the electrical cabinet temperature monitoring and alarm method according to any one of claims 1 to 4 is implemented.

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