A method and device for early warning detection of ambient temperature in a power distribution room

Abstract

The embodiment of the present invention provides a method and device for early warning detection of the ambient temperature of a distribution room, which obtains cabinet equipment characteristic parameters of multiple electrical equipment; obtains temperature warning information, circuit design warning, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment; pre-processes the multiple warning vectors to obtain screening warning vectors, and forms a screening warning vector set according to the screening warning vector group; constructs early warning memory matrix parameters with the screening warning vector set, calculates the first temperature residual vector of the early warning memory matrix parameters and the operation warning vector; generates a state prediction model according to the first temperature residual vector; inputs the specific cabinet equipment characteristic parameters into the state prediction model to obtain output temperature warning information; realizes the temperature prediction and early warning effect in the distribution room environment, reduces the risk of equipment operation, predicts the abnormal state of user equipment, and ensures the safety of electrical equipment.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method for early warning detection of ambient temperature in a power distribution room, a device for early warning detection of ambient temperature in a power distribution room, a computer device and a computer-readable storage medium. Background Art

[0002] As a key node connecting the power grid and the user side, the distribution room is an important part of the power grid operation and maintenance. The traditional distribution room operation and maintenance management model can no longer meet the needs of users and the lean management requirements of the power grid. Its shortcomings are prominently reflected in the working environment, operation and maintenance model, monitoring methods, etc. The working environment of the traditional distribution room is complex, and it is easy for environmental factors to cause abnormal equipment working conditions, which can easily cause equipment aging, excessive temperature, poor ventilation, poor line contact, equipment overload operation and other problems, posing a serious threat to the safe operation of equipment and personal safety. Summary of the invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a method for early warning detection of ambient temperature in a power distribution room, an apparatus for early warning detection of ambient temperature in a power distribution room, a computer device and a computer-readable storage medium that overcome the above problems or at least partially solve the above problems.

[0004] In order to solve the above problem, an embodiment of the present invention discloses a method for early warning detection of the ambient temperature of a power distribution room, wherein the power distribution room includes a plurality of electrical devices; the method includes:

[0005] Obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters;

[0006] Obtain temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment;

[0007] The cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors;

[0008] Preprocessing the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector groups;

[0009] The screening warning vector set is used to construct a warning memory matrix parameter, and a first temperature residual vector of the warning memory matrix parameter and the running warning vector is calculated;

[0010] generating a state prediction model according to the first temperature residual vector;

[0011] The characteristic parameters of the specific cabinet equipment are input into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information.

[0012] Preferably, the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors, including:

[0013] The high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters are associated with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors.

[0014] Preferably, the preprocessing of the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vectors, comprises:

[0015] Detect whether the multiple warning vectors are repeated or missing, perform elimination operations and merging operations on the multiple warning vectors, and select a screening warning vector;

[0016] Multiple screening warning vectors are grouped into a screening warning vector set.

[0017] Preferably, the step of constructing a warning memory matrix parameter by screening the warning vector set and calculating the first temperature residual vector between the warning memory matrix parameter and the running warning vector comprises:

[0018] Divide the screening warning vector set into multiple vector column parameters according to the year parameter;

[0019] By vertically arranging multiple vector column parameters, the warning memory matrix parameters are constructed and generated;

[0020] Performing weight calculation on the warning memory matrix parameters to obtain multiple warning weight vectors;

[0021] Get the operation warning vector;

[0022] A first temperature residual vector of the operation warning vector and the warning weight vector is calculated.

[0023] Preferably, generating a state prediction model according to the first temperature residual vector includes:

[0024] A specific basic model is obtained, and a function corresponding to the first temperature residual vector is set as an activation function of the specific basic model to obtain the state prediction model.

[0025] The embodiment of the present invention discloses a device for early warning detection of the ambient temperature of a power distribution room, wherein the power distribution room includes a plurality of electrical equipments; the device includes:

[0026] The first acquisition module is used to obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters;

[0027] A second acquisition module is used to acquire temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment;

[0028] A composition module, used to combine the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information into multiple warning vectors;

[0029] A preprocessing module, used for preprocessing the plurality of warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector groups;

[0030] A calculation module, used for constructing a warning memory matrix parameter from the screening warning vector set, and calculating a first temperature residual vector between the warning memory matrix parameter and the running warning vector;

[0031] A generating module, used for generating a state prediction model according to the first temperature residual vector;

[0032] The output module is used to input the characteristic parameters of the specific cabinet equipment into the state prediction model to obtain output temperature warning information, circuit design warning, and fault warning information.

[0033] Preferably, the component modules include:

[0034] A generation submodule is used to associate the high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors.

[0035] Preferably, the preprocessing module comprises:

[0036] A detection submodule, used to detect whether the multiple warning vectors are repeated or missing, and to select a screening warning vector by performing a removal operation and a merging operation on the multiple warning vectors;

[0037] The composition submodule is used to combine multiple screening warning vectors into a screening warning vector set.

[0038] An embodiment of the present invention discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned early warning detection method for the ambient temperature of a power distribution room when executing the computer program.

[0039] An embodiment of the present invention discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned early warning detection method for the ambient temperature of a power distribution room are implemented.

[0040] The embodiments of the present invention include the following advantages:

[0041] In an embodiment of the present invention, the early warning detection method for the ambient temperature of the power distribution room includes: obtaining cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters; obtaining temperature early warning information, circuit design early warning, and fault early warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment; and composing the cabinet equipment characteristic parameters and temperature early warning information, circuit design early warning, and fault early warning information into multiple early warning vectors; The multiple warning vectors are preprocessed to obtain screening warning vectors, and a screening warning vector set is formed according to the screening warning vector group; the warning memory matrix parameters are constructed from the screening warning vector set, and the first temperature residual vector of the warning memory matrix parameters and the operation warning vector is calculated; a state prediction model is generated according to the first temperature residual vector; the characteristic parameters of the specific cabinet equipment are input into the state prediction model to obtain output temperature warning information, circuit design warning, and fault warning information; the temperature prediction and detection effect of the distribution room is achieved, the risk of equipment operation is reduced, the abnormal state of user equipment is predicted, and the safety of electrical equipment is ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] 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.

[0043] Figure 1 It is a schematic diagram of an embodiment of a method for early warning detection of ambient temperature in a power distribution room according to an embodiment of the present invention;

[0044] Figure 2It is a structural block diagram of an embodiment of an early warning detection device for the ambient temperature of a power distribution room according to an embodiment of the present invention;

[0045] Figure 3 The diagram is a diagram of the internal structure of a computer device according to an embodiment. DETAILED DESCRIPTION

[0046] In order to make the technical problems, technical solutions and beneficial effects solved by the embodiments of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0047] In a core concept of an embodiment of the present invention, the electrical characteristics of each cabinet device are different. By associating the electrical characteristics of the cabinet device with the warning information, a prediction training model is obtained to improve the accuracy of the prediction. Specifically, the electrical parameters, age parameters, and fault occurrence parameters of various cabinet electrical equipment are associated with temperature warnings, circuit design warning information, and fault warning information to obtain a parameter vector set. By combining the equipment parameters with the warning information, the accuracy of the prediction simulation is improved. The parameter vector set is then converted into a warning memory matrix parameter, and the difference between the warning memory matrix parameter and the historical data vector is calculated, and the difference is confirmed as the first temperature residual vector; the state prediction model is generated by using the first temperature residual vector as the activation layer, and a strong nonlinear factor is introduced to limit the model output result within a preset range, thereby improving the stability of the state prediction model. By inputting new operating parameters, a variety of warning information such as predicted temperature warnings can be obtained; the temperature warning detection effect in the distribution room environment is achieved, and other types of warning information can also be generated to reduce the risk of equipment operation, predict the abnormal state of user equipment, and ensure the safety of electrical equipment.

[0048] Reference Figure 1 , shows a schematic diagram of an embodiment of a method for early warning detection of the ambient temperature of a power distribution room according to an embodiment of the present invention, wherein the power distribution room includes a plurality of electrical equipments; specifically, the method may include the following steps:

[0049] Step S101, obtaining cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming cabinet parameters, voltage transformer cabinet parameters, transformer outgoing cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters;

[0050] In the embodiment of the present invention, the method can be applied to various terminals such as personal computers, laptops, smart phones, smart terminals and portable wearable devices. The embodiment of the present invention does not limit the specific type of the terminal. The operating system of the terminal may include Android, Harmony OS, IOS, Windows Phone, Windows, etc., and the present invention does not impose too many restrictions on this.

[0051] It should be noted that the cabinet equipment characteristic parameters refer to the electrical characteristic parameters, service life parameters, and fault occurrence parameters of the electrical equipment; the electrical characteristic parameters may refer to parameters such as rated capacity, overcurrent protection, short circuit protection, and zero-sequence protection, and the embodiments of the present invention do not impose excessive restrictions on this; in addition, the service life parameters refer to parameters such as the remaining service life of the electrical equipment and the equipment weather resistance data; the fault occurrence parameters refer to parameters such as the fault occurrence rate.

[0052] Specifically applied to the embodiment of the present invention, the cabinet equipment may include a high-voltage metering cabinet, a high-voltage incoming line cabinet, a voltage transformer cabinet, a transformer outgoing line cabinet, a high-voltage busbar cabinet, a dry-type transformer, a capacitor compensation cabinet, a high-voltage isolation cabinet, and a low-voltage contact cabinet. The embodiment of the present invention does not impose too many restrictions on the types of cabinet equipment. The electrical characteristics of each cabinet equipment are different. In the embodiment of the present invention, the electrical characteristics of the cabinet equipment are associated with the early warning information to obtain a predicted training model to improve the accuracy of the prediction. That is, the characteristic parameters of the cabinet equipment may include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, low-voltage contact cabinet parameters, etc. The embodiment of the present invention does not impose too many restrictions on this;

[0053] It should be noted that the high-voltage metering cabinet parameters may refer to the electrical characteristic parameters, age parameters, fault occurrence parameters, etc. of the high-voltage metering cabinet. The embodiment of the present invention does not impose too many restrictions on this. In addition, the high-voltage incoming line cabinet refers to electrical characteristic parameters, age parameters, fault occurrence parameters, etc. The other parameters in the cabinet equipment characteristic parameters may also include electrical characteristic parameters, age parameters, fault occurrence parameters, etc. The embodiment of the present invention will not go into details here.

[0054] Step S102, obtaining temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment;

[0055] Further applied to the embodiments of the present invention, corresponding temperature warning information, circuit design warning, and fault warning information can be obtained; specifically, temperature warning information refers to alarm information that the temperature of electrical equipment is too high, which is used to remind users that the temperature of the equipment is too high; and fault warning information refers to prompt information of fault types such as protection device failure, transformer failure, three-phase failure, circuit breaker failure, overload failure, and leakage failure of electrical equipment; and circuit design warning refers to alarm information of equipment circuit design defects found during the use of electrical equipment, such as the connection point between a certain device and a certain device is prone to short circuit; and the corresponding temperature warning information, circuit design warning, and fault warning information are then associated with the characteristic parameters of the cabinet equipment.

[0056] Step S103, combining the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information into a plurality of warning vectors;

[0057] Specifically applied to the embodiment of the present invention, the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into multiple warning vectors, including: the high-voltage metering cabinet parameters, high-voltage incoming cabinet parameters, voltage transformer cabinet parameters, transformer outgoing cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters are associated with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors;

[0058] For example, the warning vector =( , , , , , );in, Refers to the electrical characteristic parameters of a certain electrical equipment; Refers to the age parameter of a certain electrical equipment; It refers to the fault occurrence parameter of a certain electrical equipment; Refers to the temperature warning information of a certain electrical equipment; Refers to the circuit design warning information of a certain electrical equipment; Refers to the fault warning information of a certain electrical equipment.

[0059] Step S104, pre-processing the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector group;

[0060] After obtaining multiple warning vectors, pre-processing such as elimination or merging is performed on the warning vectors to obtain screening warning vectors, and the screening warning vectors are combined to form a screening warning vector set.

[0061] In actual application in an embodiment of the present invention, the multiple warning vectors are preprocessed to obtain screening warning vectors, and a screening warning vector set is formed according to the screening warning vector groups, including: detecting whether the multiple warning vectors are repeated or missing, performing elimination operations and merging operations on the multiple warning vectors, and selecting screening warning vectors; and forming multiple screening warning vector groups into a screening warning vector set.

[0062] The above-mentioned preprocessing operation is only an example of an embodiment of the present invention. The warning vector can also be pre-processed through other preprocessing operations, such as filling, replacing, data type conversion, data format conversion, data normalization, etc., to obtain a screening warning vector. The embodiment of the present invention does not impose too many restrictions on this, thereby improving the generalization ability and robustness of the model.

[0063] Step S105, constructing a warning memory matrix parameter by using the screening warning vector set, and calculating a first temperature residual vector between the warning memory matrix parameter and the running warning vector;

[0064] Specifically applied to the embodiment of the present invention, firstly, the warning memory matrix parameters are constructed according to the screening warning vector set; specifically, the screening warning vector set can be divided into multiple vector column parameters according to the age parameter; the multiple vector column parameters are arranged vertically to construct the warning memory matrix parameters;

[0065] In the embodiment of the present invention, the screening warning vector set is sorted from high to low according to the age parameter to obtain a plurality of sorted vector column parameters, and then the plurality of vector column parameters are arranged vertically to construct a warning memory matrix parameter;

[0066] For example, when the warning vector of a high-voltage meter cabinet =( , , , , , ), its age parameter is 5 years; the warning vector of a voltage transformer cabinet =( , , , , , ), its age parameter For 3 years; the warning vector of a capacitor compensation cabinet =( , , , , , ), its age parameter 7 years;

[0067] Then the early warning memory matrix parameter M can be composed as follows:

[0068] ;

[0069] In actual application to the embodiment of the present invention, the method of constructing a warning memory matrix parameter by using the screening warning vector set and calculating a first temperature residual vector between the warning memory matrix parameter and the operation warning vector includes: obtaining an operation warning vector; performing weight calculation on the warning memory matrix parameter to obtain multiple warning weight vectors; and calculating a first temperature residual vector between the operation warning vector and the warning weight vector.

[0070] In an embodiment of the present invention, the operation warning vector may refer to a vector parameter corresponding to a memory matrix parameter generated in a simulation. Specifically, the operation warning vector may be a simulation parameter generated by a conditional generative adversarial network model (CGAN). Specifically, the conditional generative adversarial network (CGAN) may be used to generate data that approximates real data. The conditional generative adversarial network may include a generator and a discriminator. The conditional generative adversarial network controls the generation of specific properties of the simulated memory matrix parameters by embedding conditional information into the networks of the generator and the discriminator, and converts discrete category label conditions into a continuous vector form. The function of the generator is to generate false data that is as close to the real data as possible. The function of the discriminator is to distinguish whether the input data is from a real data set or false data generated by the generator, thereby obtaining the simulated memory matrix parameters outputted in the end.

[0071] After obtaining the operation warning vector, weight calculation is performed on the operation warning vector and the warning memory matrix parameter to obtain multiple warning weight vectors;

[0072] Specifically, the calculation method of the warning weight vector U is as follows:

[0073] ;

[0074] in, Represents the warning memory matrix parameters; Represents the operation warning vector.

[0075] Furthermore, a first temperature residual vector of the operation warning vector and the warning weight vector may be calculated; that is, the difference between the operation warning vector and the warning weight vector is determined as the first temperature residual vector;

[0076] The first temperature residual vector .

[0077] Step S106, generating a state prediction model according to the first temperature residual vector;

[0078] In an embodiment of the present invention, the first temperature residual vector may be set as an activation function on a specific basic model to obtain a state prediction model;

[0079] It should be noted that the specific basic model may include a variety of supervised machine learning networks such as convolutional neural networks, or other multiple supervised machine learning networks, and the embodiments of the present invention do not impose too many restrictions on this.

[0080] Specifically, generating a state prediction model according to the first temperature residual vector includes:

[0081] A specific basic model is obtained, and the function corresponding to the first temperature residual vector is set as the activation function of the specific basic model as the activation layer of the model to obtain the state prediction model. The activation function of the embodiment of the present invention introduces a strong nonlinear factor, which limits the model output result within a preset range, thereby improving the stability of the state prediction model.

[0082] When the specific basic model is a convolutional neural network or other supervised machine learning network, the multiple warning vectors composed of the above-mentioned cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information can also be divided into training sets and verification sets. The specific basic model is trained with the training set and the verification set to obtain the specific basic model after the iteration is completed. The specific basic model after the iteration is completed is confirmed as a state prediction model for outputting new temperature warning information, circuit design warning, and fault warning information.

[0083] Step S107: input the characteristic parameters of the specific cabinet equipment into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information.

[0084] In the embodiment of the present invention, after the state prediction model is obtained, the new specific cabinet equipment characteristic parameter is input into the state prediction model to obtain output temperature warning information, circuit design warning, and fault warning information, and the temperature warning information, circuit design warning, and fault warning information are transmitted to the display device to form alarm information. In the embodiment of the present invention, the temperature warning effect in the power distribution room environment and other types of prediction and warning information are achieved, thereby improving the operation safety of the equipment;

[0085] It should be noted that the state prediction model may include multiple structures such as an input layer, a convolutional layer, an activation layer, a pooling layer, a fully connected layer and an output layer. The embodiment of the present invention does not impose excessive restrictions on the structure of the state prediction model.

[0086] In an embodiment of the present invention, the early warning detection method for the ambient temperature of the power distribution room includes: obtaining cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters; obtaining temperature early warning information, circuit design early warning, and fault early warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment; and composing the cabinet equipment characteristic parameters and temperature early warning information, circuit design early warning, and fault early warning information into multiple early warning vectors; The multiple warning vectors are preprocessed to obtain screening warning vectors, and a screening warning vector set is formed according to the screening warning vector group; the warning memory matrix parameters are constructed from the screening warning vector set, and the first temperature residual vector of the warning memory matrix parameters and the operation warning vector is calculated; a state prediction model is generated according to the first temperature residual vector; the characteristic parameters of the specific cabinet equipment are input into the state prediction model to obtain output temperature warning information, circuit design warning, and fault warning information; the temperature prediction and detection effect of the distribution room is achieved, the risk of equipment operation is reduced, the abnormal state of user equipment is predicted, and the safety of electrical equipment is ensured.

[0087] It should be noted that, for the method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that this embodiment is not limited by the order of the actions described, because according to this embodiment, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by this embodiment.

[0088] Reference Figure 2 , shows a structural block diagram of an embodiment of a device for early warning detection of the ambient temperature of a power distribution room of this embodiment, wherein the power distribution room includes a plurality of electrical equipments; specifically, the following modules may be included:

[0089] The first acquisition module 301 is used to obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters;

[0090] The second acquisition module 302 is used to acquire temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment;

[0091] A composition module 303 is used to combine the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information into multiple warning vectors;

[0092] A preprocessing module 304 is used to preprocess the multiple warning vectors to obtain screening warning vectors, and form a screening warning vector set according to the screening warning vector groups;

[0093] A calculation module 305 is used to construct a warning memory matrix parameter by using the screening warning vector set, and calculate a first temperature residual vector between the warning memory matrix parameter and the running warning vector;

[0094] A generating module 306, configured to generate a state prediction model according to the first temperature residual vector;

[0095] The output module 307 is used to input the characteristic parameters of the specific cabinet equipment into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information.

[0096] Preferably, the component modules include:

[0097] A generation submodule is used to associate the high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors.

[0098] Preferably, the preprocessing module comprises:

[0099] A detection submodule, used to detect whether the multiple warning vectors are repeated or missing, and to select a screening warning vector by performing a removal operation and a merging operation on the multiple warning vectors;

[0100] The composition submodule is used to combine multiple screening warning vectors into a screening warning vector set.

[0101] Preferably, the calculation module includes:

[0102] A division submodule is used to divide the screening warning vector set into multiple vector column parameters according to the year parameter;

[0103] A generation submodule is constructed to arrange the parameters of the warning memory matrix vertically through multiple vector column parameters;

[0104] A weight calculation submodule, used for performing weight calculation on the warning memory matrix parameters to obtain a plurality of warning weight vectors;

[0105] The acquisition submodule is used to obtain the operation warning vector;

[0106] The residual vector submodule is used to calculate the first temperature residual vector of the operation warning vector and the warning weight vector.

[0107] Preferably, the generating module comprises:

[0108] The activation function submodule is used to obtain a specific basic model, set the function corresponding to the first temperature residual vector as the activation function of the specific basic model, and obtain the state prediction model.

[0109] Each module in the above-mentioned early warning detection system for the ambient temperature of the power distribution room can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0110] The above-mentioned early warning detection system for the ambient temperature of a power distribution room can be used to execute the early warning detection method for the ambient temperature of a power distribution room provided in any of the above-mentioned embodiments, and has corresponding functions and beneficial effects.

[0111] In one embodiment, a computer device is provided, whose internal structure diagram can be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for early warning detection device of the ambient temperature of the power distribution room is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0112] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0113] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps of the above embodiment are implemented:

[0114] Obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters;

[0115] Obtain temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment;

[0116] The cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors;

[0117] Preprocessing the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector groups;

[0118] The screening warning vector set is used to construct a warning memory matrix parameter, and a first temperature residual vector of the warning memory matrix parameter and the running warning vector is calculated;

[0119] generating a state prediction model according to the first temperature residual vector;

[0120] The characteristic parameters of the specific cabinet equipment are input into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information.

[0121] Preferably, the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors, including:

[0122] The high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters are associated with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors.

[0123] Preferably, the preprocessing of the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vectors, comprises:

[0124] Detect whether the multiple warning vectors are repeated or missing, perform elimination operations and merging operations on the multiple warning vectors, and select a screening warning vector;

[0125] Multiple screening warning vectors are grouped into a screening warning vector set.

[0126] Preferably, the step of constructing a warning memory matrix parameter by screening the warning vector set and calculating the first temperature residual vector between the warning memory matrix parameter and the running warning vector comprises:

[0127] Divide the screening warning vector set into multiple vector column parameters according to the year parameter;

[0128] By vertically arranging multiple vector column parameters, the warning memory matrix parameters are constructed and generated;

[0129] Performing weight calculation on the warning memory matrix parameters to obtain multiple warning weight vectors;

[0130] Get the operation warning vector;

[0131] A first temperature residual vector of the operation warning vector and the warning weight vector is calculated.

[0132] Preferably, generating a state prediction model according to the first temperature residual vector includes:

[0133] A specific basic model is obtained, and a function corresponding to the first temperature residual vector is set as an activation function of the specific basic model to obtain the state prediction model.

[0134] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above embodiment are implemented:

[0135] Obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters;

[0136] Obtain temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment;

[0137] The cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors;

[0138] Preprocessing the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector groups;

[0139] The screening warning vector set is used to construct a warning memory matrix parameter, and a first temperature residual vector of the warning memory matrix parameter and the running warning vector is calculated;

[0140] generating a state prediction model according to the first temperature residual vector;

[0141] The characteristic parameters of the specific cabinet equipment are input into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information.

[0142] Preferably, the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors, including:

[0143] The high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters are associated with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors.

[0144] Preferably, the preprocessing of the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vectors, comprises:

[0145] Detect whether the multiple warning vectors are repeated or missing, perform elimination operations and merging operations on the multiple warning vectors, and select a screening warning vector;

[0146] Multiple screening warning vectors are grouped into a screening warning vector set.

[0147] Preferably, the step of constructing a warning memory matrix parameter by screening the warning vector set and calculating the first temperature residual vector between the warning memory matrix parameter and the running warning vector comprises:

[0148] Divide the screening warning vector set into multiple vector column parameters according to the year parameter;

[0149] By vertically arranging multiple vector column parameters, the warning memory matrix parameters are constructed and generated;

[0150] Performing weight calculation on the warning memory matrix parameters to obtain multiple warning weight vectors;

[0151] Get the operation warning vector;

[0152] A first temperature residual vector of the operation warning vector and the warning weight vector is calculated.

[0153] Preferably, generating a state prediction model according to the first temperature residual vector includes:

[0154] A specific basic model is obtained, and a function corresponding to the first temperature residual vector is set as an activation function of the specific basic model to obtain the state prediction model.

[0155] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0156] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0157] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0158] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0159] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0160] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0161] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0162] The above is a detailed introduction to a method for early warning detection of the ambient temperature of a distribution room, an early warning detection device for the ambient temperature of a distribution room, a computer device and a computer-readable storage medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for early warning detection of ambient temperature in a power distribution room, characterized in that: The power distribution room includes a plurality of electrical equipment; the method includes: Obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters; Obtain temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment; The cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors; Preprocessing the multiple warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector groups; The screening warning vector set is used to construct a warning memory matrix parameter, and a first temperature residual vector of the warning memory matrix parameter and the running warning vector is calculated; generating a state prediction model according to the first temperature residual vector; Inputting characteristic parameters of specific cabinet equipment into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information; The step of constructing a warning memory matrix parameter by screening the warning vector set and calculating a first temperature residual vector between the warning memory matrix parameter and the running warning vector comprises: Divide the screening warning vector set into multiple vector column parameters according to the year parameter; By vertically arranging multiple vector column parameters, the warning memory matrix parameters are constructed and generated; Performing weight calculation on the warning memory matrix parameters to obtain multiple warning weight vectors; Get the operation warning vector; Calculating a difference between the operation warning vector and the warning weight vector to determine it as a first temperature residual vector; The step of generating a state prediction model according to the first temperature residual vector comprises: A specific basic model is obtained, and a function corresponding to the first temperature residual vector is set as an activation function of the specific basic model to obtain the state prediction model.

2. The early warning detection method for the ambient temperature of the power distribution room according to claim 1 is characterized in that: The cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information are combined into a plurality of warning vectors, including: The high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage connection cabinet parameters are associated with temperature warning information, circuit design warning, and fault warning information to generate multiple warning vectors.

3. The early warning detection method for the ambient temperature of a power distribution room according to claim 1 is characterized in that: The preprocessing of the plurality of warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vectors, comprises: Detect whether the multiple warning vectors are repeated or missing, perform elimination operations and merging operations on the multiple warning vectors, and select a screening warning vector; Multiple screening warning vectors are grouped into a screening warning vector set.

4. A warning detection device for the ambient temperature of a power distribution room, characterized in that: The power distribution room includes a plurality of electrical equipment; the device includes: The first acquisition module is used to obtain cabinet equipment characteristic parameters of multiple electrical equipment; wherein the cabinet equipment characteristic parameters include high-voltage metering cabinet parameters, high-voltage incoming line cabinet parameters, voltage transformer cabinet parameters, transformer outgoing line cabinet parameters, high-voltage busbar cabinet parameters, dry-type transformer parameters, capacitor compensation cabinet parameters, high-voltage isolation cabinet parameters, and low-voltage contact cabinet parameters; A second acquisition module is used to acquire temperature warning information, circuit design warning information, and fault warning information corresponding to the cabinet equipment characteristic parameters of the electrical equipment; A composition module, used to combine the cabinet equipment characteristic parameters and temperature warning information, circuit design warning, and fault warning information into multiple warning vectors; A preprocessing module, used for preprocessing the plurality of warning vectors to obtain screening warning vectors, and forming a screening warning vector set according to the screening warning vector groups; A calculation module, used for constructing a warning memory matrix parameter from the screening warning vector set, and calculating a first temperature residual vector between the warning memory matrix parameter and the running warning vector; A generating module, used for generating a state prediction model according to the first temperature residual vector; An output module is used to input characteristic parameters of specific cabinet equipment into the state prediction model to obtain output temperature warning information, circuit design warning information, and fault warning information; The calculation module comprises: A division submodule is used to divide the screening warning vector set into multiple vector column parameters according to the year parameter; A generation submodule is constructed to arrange the parameters of the warning memory matrix vertically through multiple vector column parameters; A weight calculation submodule, used for performing weight calculation on the warning memory matrix parameters to obtain a plurality of warning weight vectors; The acquisition submodule is used to obtain the operation warning vector; A residual vector submodule, used for calculating the difference between the operation warning vector and the warning weight vector to determine it as a first temperature residual vector; The generation module comprises: The activation function submodule is used to obtain a specific basic model, set the function corresponding to the first temperature residual vector as the activation function of the specific basic model, and obtain the state prediction model.

5. The early warning detection device for the ambient temperature of the power distribution room according to claim 4 is characterized in that: The preprocessing module comprises: A detection submodule, used to detect whether the multiple warning vectors are repeated or missing, and to select a screening warning vector by performing a removal operation and a merging operation on the multiple warning vectors; The composition submodule is used to combine multiple screening warning vectors into a screening warning vector set.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the early warning detection method for the ambient temperature of a power distribution room according to any one of claims 1 to 3 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the early warning detection method for the ambient temperature of a power distribution room according to any one of claims 1 to 3 are implemented.

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