Abnormal identification method and system for power distribution IoT intelligent gateway based on IoT platform

Abstract

The present invention relates to the technical field of distribution gateway data exchange network, and discloses a distribution Internet of Things intelligent gateway abnormality identification method and system based on an Internet of Things platform, wherein the system comprises an intelligent distribution gateway internal fault analysis module, an intelligent distribution gateway external fault analysis module, and an intelligent distribution gateway fault priority analysis feedback module; gateway fault type feedback priority analysis is performed by combining standard preset priorities of different gateway fault types with intelligent search algorithms and gateway hardware and software environment fault identification result parameters, and gateway fault feedback priority analysis result parameters are generated, so as to realize feedback priority analysis of different hardware, software and environment fault identification results of the intelligent distribution gateway and orderly execute fault feedback operations, realize evaluation of the danger and urgency of fault types of the intelligent distribution gateway, and improve the safety and reliability of abnormal identification of the intelligent distribution gateway.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution gateway data exchange networks, and specifically to a power distribution IoT intelligent gateway anomaly identification method and system based on an IoT platform. Background Art

[0002] The smart power distribution gateway is a device based on the Internet of Things technology, which is used to monitor and control the power equipment in the distribution room in real time. It can collect data such as current, voltage, power, etc. through sensors, monitor the power equipment in the distribution room in real time, and transmit the data to the cloud for analysis and processing to achieve remote monitoring and intelligent control. The smart gateway of the smart distribution room can also analyze the data through intelligent algorithms, provide predictive maintenance and fault diagnosis services, and help enterprises improve the reliability and operation efficiency of power equipment. The smart gateway of the smart distribution room can also be linked with other smart devices, such as smart meters and smart lighting, to achieve intelligent management of the entire building. However, the existing smart distribution gateway cannot classify and identify its own operating faults, nor can it perform fault problem feedback priority analysis on the fault type of the smart distribution gateway, which reduces the reliability of the smart distribution gateway.

[0003] The Chinese invention patent application with publication number CN114389913A discloses a gateway controller exception handling method, a gateway controller and a car. The state information of the switching chip is determined by collecting; whether the state of the switching chip is abnormal is judged, and when the state of the switching chip is abnormal, the exception handling is performed. However, the above technical solution can only perform fault analysis on the chip hardware of the gateway controller, and cannot analyze the software and external interference factors of the gateway controller, which reduces the scope of application of the gateway controller abnormal fault handling. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In order to solve the problem that the above-mentioned existing intelligent distribution gateway cannot classify and identify its own operating faults, nor can it perform fault problem feedback priority analysis on the fault types of the intelligent distribution gateway, thereby reducing the operating efficiency and reliability of the intelligent distribution gateway, the above purpose is to accurately identify the hardware, software, and environmental interference fault problems of the intelligent distribution gateway, scientifically evaluate the fault problem feedback priority of the intelligent distribution gateway, intelligently feedback fault problems of different priorities, and improve the safety and reliability of the intelligent distribution gateway.

[0006] (II) Technical solution

[0007] The present invention is implemented by the following technical scheme: a method for identifying abnormalities of a power distribution IoT intelligent gateway, the method comprising the following steps:

[0008] S1, collect gateway hardware operation feature image data;

[0009] S2, performing gateway hardware fault type identification processing according to the gateway hardware operation characteristic image data and the gateway hardware fault operation characteristic image data, and generating gateway hardware fault type identification result data;

[0010] S3, inputting the original data of the gateway communication failure experiment at the gateway receiving end, and collecting the translation data of the gateway communication failure experiment at the gateway output end;

[0011] S4, performing gateway software fault identification processing according to the gateway communication fault experiment translation data and the gateway communication fault experiment standard translation data, and generating gateway software fault identification result data;

[0012] S5, collecting gateway environment feature image data and performing gateway operating environment fault type identification processing on the gateway environment fault feature image data, and generating gateway operating environment fault type identification result data;

[0013] S6. Collect and construct gateway hardware and software environment fault identification result data and different gateway fault type priority data to perform gateway fault type feedback priority analysis, and generate gateway fault feedback priority analysis result data;

[0014] S7. Execute the intelligent power distribution gateway fault feedback operation in order on the gateway hardware and software environment fault identification result data according to the gateway fault feedback priority analysis result data.

[0015] Preferably, the operation steps of collecting gateway hardware running characteristic image data are as follows:

[0016] S11. Collect online through the cloud lens the characteristic image of the hardware operation status of the intelligent power distribution gateway during the power monitoring operation and generate gateway hardware operation characteristic image data p. The gateway hardware operation characteristic image includes the data interface operation characteristic image, the indicator light operation characteristic image, the cooling fan operation characteristic image and the gateway heat dissipation port operation characteristic image.

[0017] Preferably, the operation steps of performing gateway hardware fault type identification processing according to the gateway hardware operation characteristic image data and the gateway hardware fault operation characteristic image data to generate gateway hardware fault type identification result data are as follows:

[0018] S21. Establishing gateway hardware fault operation feature image data set A = (a1, ..., a u ,…,a α ), u=1,2,3,…,α; where a urepresents the gateway hardware fault operation feature image data corresponding to the u-th gateway hardware fault type, and α represents the maximum number of gateway hardware fault types; gateway hardware fault types include data interface not installed properly, indicator light abnormality, cooling fan not rotating, and smoke appearing at the gateway cooling port;

[0019] S22: compare the gateway hardware operation feature image data p with the gateway hardware fault operation feature image data a in the gateway hardware fault operation feature image data set A. u Perform operation feature image matching of the gateway hardware, and generate gateway hardware fault type identification result data A based on the operation feature image matching results of the gateway hardware yingjian ; Execute and generate gateway hardware fault type identification result data A yingjian The specific steps are as follows:

[0020] S221, initialization, update the number of pigeon population N and the maximum number of iterations T;

[0021] S222, exploration phase, the number of iterations in the range of [0, t1] is the exploration phase, where t1 = 0.95xT. In the exploration phase, it is necessary to calculate the speed of the hardware fault identification pigeon based on the position and target of the hardware fault identification pigeon, and the current position plus the speed is the new position, that is, search for the gateway hardware fault operation feature image data a that matches the gateway hardware operation feature image data p in the search space of the gateway hardware fault operation feature image data set A. u The calculation formula for hardware fault identification pigeon speed is: in represents the new speed of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, represents the new speed of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase; represents the original speed of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, the original speed of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase; is a constant with a value of 0.2, t represents the current iteration number of the algorithm, represents an exponential function with base e, rand is a uniform random number in the interval [0,1], It represents the best position of the hardware fault identification pigeon in the exploration phase in the j-dimensional space, that is, in the exploration phase, the hardware fault identification pigeon searches for the gateway hardware fault operation feature image data a that best matches the gateway hardware operation feature image data p in the gateway hardware fault operation feature image data set A search space with dimension α. u Position; M i jIt represents the original position of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, the original position of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase; the calculation formula for the new position of the hardware fault identification pigeon is in It represents the new position of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, the new position of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase;

[0022] S223, development phase, the number of iterations within the range of [t1, T] is the development phase, first sort the hardware fault identification pigeon population, divide the hardware fault identification pigeon population into two groups, excellent and ordinary, the excellent group hardware fault identification pigeon population keeps its position unchanged, and provides its position and fitness value as parameters for the ordinary group hardware fault identification pigeon population to determine their new position, the ordinary hardware fault identification pigeon population new position calculation formula is

[0023] in It represents the new position of the hardware fault identification pigeon i in the j-dimensional space during the development stage, that is, the new position of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the development stage; It represents the best position of the excellent group of hardware fault identification pigeons in the j-dimensional space during the development stage, that is, the excellent group of hardware fault identification pigeons searches for the gateway hardware fault operation feature image data a that best matches the gateway hardware operation feature image data p in the gateway hardware fault operation feature image data set A search space with dimension α during the development stage. u location;

[0024] S224: When the algorithm meets the maximum number of iterations, output the gateway hardware operation feature image data p and the gateway hardware fault operation feature image data a. u The matching results;

[0025] S225, when the gateway hardware failure operation characteristic image data a output in step S224 u If it exists, the gateway hardware failure operation feature image data a u The corresponding gateway hardware fault type identifier generates gateway hardware fault type identification result data A yingjian ;

[0026] When the gateway hardware failure operation characteristic image data a output in step S224 u If it does not exist, it means that the intelligent power distribution gateway hardware has not identified a fault, and the gateway hardware fault type identification result data A is generated.yingjian For no fault.

[0027] Preferably, the operation steps of inputting the original data of the gateway communication failure experiment at the gateway receiving end and collecting the translation data of the gateway communication failure experiment at the gateway output end are as follows:

[0028] S31, when the gateway hardware fault type identification result data A yingjian When the generation is completed, the gateway communication failure experiment original data b is inputted at the receiving end of the intelligent power distribution gateway through the data transmission device, and the gateway communication failure experiment original data b represents the experimental transmission data used to check the intelligent power distribution gateway software configuration failure that has not been translated by the intelligent power distribution gateway in combination with the communication protocol;

[0029] S32. When the input of the original data b of the gateway communication fault experiment is completed, the original data b of the gateway communication fault experiment translated by the smart distribution network is collected at the output end of the smart distribution gateway by a data collector and gateway communication fault experiment translated data b' is generated.

[0030] Preferably, the operation steps of performing gateway software fault identification processing based on the gateway communication fault experiment translation data and the gateway communication fault experiment standard translation data to generate gateway software fault identification result data are as follows:

[0031] S41. Establishing gateway communication failure experiment standard translation data b biaozhun , the gateway communication failure experiment standard translation data b biaozhun It represents the standard experimental transmission data of the gateway communication failure experiment original data b translated by the intelligent power distribution gateway in combination with the standard communication protocol;

[0032] S42, using the KD tree nearest neighbor search algorithm to compare the gateway communication failure experiment translation data b' with the gateway communication failure experiment standard translation data b biaozhun Perform character matching on the intelligent power distribution gateway communication fault experimental data, and generate gateway software fault identification result data B according to the character matching result on the intelligent power distribution gateway communication fault experimental data;

[0033] When b' and b biaozhun The character matching of the intelligent power distribution gateway communication fault experiment data is successful, indicating that there is no software configuration fault in the intelligent power distribution gateway, and the output gateway software fault identification result data B is no fault;

[0034] When b' and b biaozhun If the character matching of the intelligent power distribution gateway communication fault experiment data fails, it means that there is a software configuration fault in the intelligent power distribution gateway, and the output gateway software fault identification result data B is faulty.

[0035] Preferably, the steps of collecting the gateway environment characteristic image data and performing gateway operating environment fault type identification processing with the gateway environment fault characteristic image data to generate the gateway operating environment fault type identification result data are as follows:

[0036] S51, collecting feature images of the surrounding environment of the smart power distribution gateway during the power monitoring operation online through the cloud lens and generating gateway environment feature image data R;

[0037] S52, establish a gateway environment fault feature image data set C = (c1, ..., c v ,…,c β ), v = 1, 2, 3, ..., β; where c v represents the gateway environment fault feature image data corresponding to the vth gateway environment fault type, β represents the maximum number of gateway environment fault types; gateway environment fault types include the presence of electromagnetic interference equipment, the presence of radio wave interference equipment, the presence of thunderstorm lightning weather and electromagnetic shielding space structure;

[0038] S53, using a bidirectional search algorithm to compare the gateway environment feature image data R with the gateway environment fault feature image data c in the gateway environment fault feature image data set C. v Perform feature image matching of the gateway environment, and generate gateway operating environment fault type identification result data C based on the feature image matching results of the gateway environment huanjing ;

[0039] When R and c v If the characteristic image matching of the gateway environment is successful, it means that there are environmental interference factors in the surrounding environment of the intelligent power distribution gateway, and the gateway environment fault characteristic image data c is output. v The corresponding gateway environment fault type identifier generates the gateway operation environment fault type identification result data C huanjing ;

[0040] When R and c v If the characteristic image of the gateway environment is not matched successfully, it means that there is no environmental interference factor in the surrounding environment of the intelligent power distribution gateway, and the gateway operating environment fault type identification result data C is output. huanjing For no fault.

[0041] Preferably, the operation steps of collecting and constructing the gateway hardware and software environment fault identification result data and different gateway fault type priority data to perform gateway fault type feedback priority analysis and generate gateway fault feedback priority analysis result data are as follows:

[0042] S61, the gateway hardware fault type identification result data A yingjian, Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing Collect and combine data to construct gateway hardware and software environment fault identification result data D = (A yingjian ,B,C huanjing );

[0043] S62. Establishing priority data sets for different gateway fault types in Indicates that when the gateway hardware fault type identification result data A yingjian When a fault occurs, the intelligent power distribution gateway sends the gateway hardware fault type identification result data A yingjian According to the first priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem are provided;

[0044] Or when the gateway hardware fault type identification result data A yingjian There is no fault, and when the gateway software fault identification result data B has a fault, the intelligent power distribution gateway will use the gateway software fault identification result data B according to the first priority to feedback the fault problem of the intelligent power distribution gateway corresponding to the different gateway fault type priority data;

[0045] Or when the gateway hardware fault type identification result data A yingjian and the gateway software fault identification result data B do not have any faults at the same time, and the gateway operating environment fault type identification result data C huanjing When a fault occurs, the intelligent power distribution gateway sends the gateway operating environment fault type identification result data C huanjing According to the first priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem are provided;

[0046] Indicates that when the gateway hardware fault type identification result data A yingjian When there is a fault at the same time as the gateway software fault identification result data B, the intelligent power distribution gateway will feedback the gateway software fault identification result data B according to the second priority level to the different gateway fault type priority data corresponding to the intelligent power distribution gateway fault problem;

[0047] Or when the gateway hardware fault type identification result data A yingjian and the gateway operating environment fault type identification result data C huanjing When there is a fault at the same time, the gateway software fault identification result data B does not have a fault, and the intelligent power distribution gateway sends the gateway operating environment fault type identification result data C huanjing According to the second priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem;

[0048] Indicates that when the gateway hardware fault type identification result data A yingjian , the gateway software fault identification result data B and the gateway operating environment fault type identification result data C huanjing When there are faults at the same time, the intelligent power distribution gateway will identify the fault type of the gateway operating environment. huanjing According to the third priority, the priority data of different gateway fault types corresponding to the feedback of intelligent power distribution gateway fault problems;

[0049] S63, using a unified cost search algorithm to search the gateway hardware fault type identification result data A in the gateway hardware and software environment fault identification result data D. yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The gateway fault type feedback priority analysis is performed on the different gateway fault type priority data in the different gateway fault type priority data set E according to the fault existence keywords, and the gateway hardware fault type identification result data A is searched out. yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The corresponding priority data of different gateway fault types are used to generate gateway fault feedback priority analysis result data E'.

[0050] Preferably, the operation steps of sequentially executing the intelligent power distribution gateway fault feedback operation on the gateway hardware and software environment fault identification result data according to the gateway fault feedback priority analysis result data are as follows:

[0051] S71, analyzing the gateway hardware fault type identification result data A in the gateway fault feedback priority analysis result data E' yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The corresponding different gateway fault type priority data will be the gateway hardware fault type identification result data A in the gateway hardware and software environment fault identification result data D yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing Execute the intelligent distribution gateway fault feedback work in order according to the gateway fault type feedback priority.

[0052] A power distribution IoT intelligent gateway abnormality identification system based on the IoT platform is used to implement the power distribution IoT intelligent gateway abnormality identification method. The system includes an intelligent distribution gateway internal fault analysis module, an intelligent distribution gateway external fault analysis module, and an intelligent distribution gateway fault priority analysis feedback module; the intelligent distribution gateway internal fault analysis module, the intelligent distribution gateway external fault analysis module and the intelligent distribution gateway fault priority analysis feedback module are connected through IoT communication.

[0053] The internal fault analysis module of the intelligent power distribution gateway includes a gateway hardware operation characteristic image acquisition unit, a gateway hardware fault operation characteristic image storage unit, a gateway hardware operation fault identification unit, a gateway communication fault experiment original parameter input unit, a gateway communication fault experiment translation parameter receiving unit, a gateway communication fault experiment standard translation parameter storage unit, and a gateway software operation fault identification unit;

[0054] The gateway hardware operation characteristic image acquisition unit acquires gateway hardware operation characteristic image data through a cloud lens; the gateway hardware fault operation characteristic image storage unit is used to store gateway hardware fault operation characteristic image data; the gateway hardware operation fault identification unit performs gateway hardware fault type identification processing according to the gateway hardware operation characteristic image data and the gateway hardware fault operation characteristic image data, and generates gateway hardware fault type identification result data; the gateway communication fault experiment original parameter input unit inputs the gateway communication fault experiment original data at the gateway receiving end; the gateway communication fault experiment translation parameter receiving unit is used to acquire gateway communication fault experiment translation data at the gateway output end; the gateway communication fault experiment standard translation parameter storage unit is used to store gateway communication fault experiment standard translation data; the gateway software operation fault identification unit performs gateway software fault identification processing according to the gateway communication fault experiment translation data and the gateway communication fault experiment standard translation data, and generates gateway software fault identification result data;

[0055] The external fault analysis module of the intelligent power distribution gateway includes a gateway environment feature image acquisition unit, a gateway environment fault feature image storage unit, and a gateway operating environment fault identification unit;

[0056] The gateway environment characteristic image acquisition unit is used to collect gateway environment characteristic image data through a cloud lens; the gateway environment fault characteristic image storage unit is used to store gateway environment fault characteristic image data; the gateway operation environment fault identification unit is used to perform gateway operation environment fault type identification processing on the gateway environment characteristic image data and the gateway environment fault characteristic image data to generate gateway operation environment fault type identification result data;

[0057] The intelligent power distribution gateway fault priority analysis feedback module includes a gateway fault identification result collection unit, a different gateway fault type priority storage unit, a gateway fault identification result priority analysis unit, and a gateway fault priority analysis result feedback unit;

[0058] The gateway fault identification result collection unit is used to collect and construct gateway hardware and software environment fault identification result data; the different gateway fault type priority storage unit is used to store different gateway fault type priority data; the gateway fault identification result priority analysis unit performs gateway fault type feedback priority analysis on the gateway hardware and software environment fault identification result data and different gateway fault type priority data to generate gateway fault feedback priority analysis result data; the gateway fault priority analysis result feedback unit performs intelligent distribution gateway fault feedback operations on the gateway hardware and software environment fault identification result data in an orderly manner according to the gateway fault feedback priority analysis result data.

[0059] (III) Beneficial effects

[0060] The present invention provides a method and system for identifying abnormalities of a power distribution IoT intelligent gateway based on an IoT platform. It has the following beneficial effects:

[0061] 1. Through the gateway hardware operation feature image acquisition unit, the cloud lens is used to collect the gateway hardware operation feature image parameters in real time to provide data support for accurately identifying the hardware faults of the intelligent distribution gateway; the gateway hardware fault operation feature image storage unit and the gateway hardware operation fault identification unit cooperate with each other, scientifically preset and store the gateway hardware fault operation feature image parameters, and combine the intelligent identification algorithm with the gateway hardware operation feature image parameters for image matching, so as to accurately analyze whether the intelligent distribution gateway has a hardware fault; the gateway communication fault experiment original parameter input unit and the gateway communication fault experiment translation parameter receiving unit cooperate with each other to collect the communication fault experiment original parameters and communication fault experiment translation parameters at the input and output ends of the intelligent distribution gateway, so as to provide data support for the subsequent verification of the software faults of the intelligent distribution gateway; the gateway communication fault experiment standard translation parameter storage unit and the gateway software operation fault identification unit cooperate with each other to accurately store the gateway communication fault experiment standard translation parameters and combine the intelligent search algorithm with the gateway communication fault experiment translation data to perform communication data character analysis, scientifically identify whether the intelligent distribution gateway has a software fault, and realize the dynamic and sensitive detection of the intelligent distribution gateway's own hardware faults and software faults.

[0062] 2. Through the gateway environment characteristic image acquisition unit, the cloud lens is used to dynamically obtain the gateway environment characteristic image parameters to provide data support for the intelligent identification of interference factors in the surrounding environment of the intelligent distribution gateway; the gateway environment fault characteristic image storage unit and the gateway operation environment fault identification unit cooperate with each other, pre-store the gateway environment fault characteristic image parameters and combine the intelligent search algorithm with the gateway environment characteristic image parameters for image analysis, so as to intelligently analyze whether there are interference factors in the operating environment of the intelligent distribution gateway, and realize the dynamic and sensitive detection of interference factors in the operating environment of the intelligent distribution gateway.

[0063] 3. Through the gateway fault identification result collection unit, data processing of the hardware, software and environmental fault identification results of the intelligent distribution gateway is realized, and gateway hardware and software environment fault identification result parameters are constructed; different gateway fault type priority storage units, gateway fault identification result priority analysis units and gateway fault priority analysis result feedback units cooperate with each other, and the standard preset priorities of different gateway fault types are combined with the intelligent search algorithm and the gateway hardware and software environment fault identification result parameters to perform gateway fault type feedback priority analysis, generate gateway fault feedback priority analysis result parameters, realize feedback priority analysis of different hardware, software and environmental fault identification results of the intelligent distribution gateway and execute fault feedback operations in an orderly manner, realize the evaluation of the danger and urgency of the fault types of the intelligent distribution gateway, and improve the safety and reliability of abnormal identification of the intelligent distribution gateway. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of a module of an abnormality identification system for a power distribution IoT intelligent gateway based on an IoT platform provided by the present invention;

[0065] Figure 2 This is a flow chart of the abnormality identification method of the power distribution Internet of Things intelligent gateway provided by the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] The embodiments of the power distribution IoT intelligent gateway abnormality identification method and system based on the IoT platform are as follows:

[0068] Embodiment 1:

[0069] See also Figure 1 - Figure 2, a method for identifying abnormalities of a power distribution IoT intelligent gateway, the method comprising the following steps:

[0070] S1, collect gateway hardware operation feature image data;

[0071] S2. Perform gateway hardware fault type identification processing according to the gateway hardware operation feature image data and the gateway hardware fault operation feature image data to generate gateway hardware fault type identification result data;

[0072] S3, inputting the original data of the gateway communication failure experiment at the gateway receiving end, and collecting the translation data of the gateway communication failure experiment at the gateway output end;

[0073] S4, performing gateway software fault identification processing according to the gateway communication fault experiment translation data and the gateway communication fault experiment standard translation data, and generating gateway software fault identification result data;

[0074] S5, collecting gateway environment feature image data and performing gateway operating environment fault type identification processing on the gateway environment fault feature image data, and generating gateway operating environment fault type identification result data;

[0075] S6. Collect and construct gateway hardware and software environment fault identification result data and different gateway fault type priority data to perform gateway fault type feedback priority analysis, and generate gateway fault feedback priority analysis result data;

[0076] S7. Execute the intelligent power distribution gateway fault feedback operation in order based on the gateway fault feedback priority analysis result data and the gateway hardware and software environment fault identification result data.

[0077] For further information, see Figure 1 - Figure 2 ,The steps to collect the characteristic image data of the gateway hardware operation are as follows:

[0078] S11. Collect online through the cloud lens the characteristic image of the hardware operation status of the intelligent power distribution gateway during the power monitoring operation and generate gateway hardware operation characteristic image data p. The gateway hardware operation characteristic image includes the data interface operation characteristic image, the indicator light operation characteristic image, the cooling fan operation characteristic image and the gateway heat dissipation port operation characteristic image.

[0079] The operation steps for performing gateway hardware fault type identification processing based on the gateway hardware operation feature image data and the gateway hardware fault operation feature image data and generating gateway hardware fault type identification result data are as follows:

[0080] S21. Establishing gateway hardware fault operation feature image data set A = (a1, ..., a u ,…,a α), u=1,2,3,…,α; where a u represents the gateway hardware fault operation feature image data corresponding to the u-th gateway hardware fault type, and α represents the maximum number of gateway hardware fault types; gateway hardware fault types include data interface not installed properly, indicator light abnormality, cooling fan not rotating, and smoke appearing at the gateway cooling port;

[0081] S22: compare the gateway hardware operation feature image data p with the gateway hardware fault operation feature image data a in the gateway hardware fault operation feature image data set A. u Perform operation feature image matching of the gateway hardware, and generate gateway hardware fault type identification result data A based on the operation feature image matching results of the gateway hardware yingjian ; Execute and generate gateway hardware fault type identification result data A yingjian The specific steps are as follows:

[0082] S221, initialization, update the number of pigeon population N and the maximum number of iterations T;

[0083] S222, exploration phase, the number of iterations in the range of [0, t1] is the exploration phase, where t1 = 0.95xT. In the exploration phase, it is necessary to calculate the speed of the hardware fault identification pigeon based on the position and target of the hardware fault identification pigeon, and the current position plus the speed is the new position, that is, search for the gateway hardware fault operation feature image data a that matches the gateway hardware operation feature image data p in the search space of the gateway hardware fault operation feature image data set A. u The calculation formula for hardware fault identification pigeon speed is: in represents the new speed of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, represents the new speed of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase; represents the original speed of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, the original speed of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase; is a constant with a value of 0.2, t represents the current iteration number of the algorithm, represents an exponential function with base e, rand is a uniform random number in the interval [0,1], It represents the best position of the hardware fault identification pigeon in the exploration phase in the j-dimensional space, that is, in the exploration phase, the hardware fault identification pigeon searches for the gateway hardware fault operation feature image data a that best matches the gateway hardware operation feature image data p in the gateway hardware fault operation feature image data set A search space with dimension α. u location; It represents the original position of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, the original position of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase; the calculation formula for the new position of the hardware fault identification pigeon is in It represents the new position of the hardware fault identification pigeon i in the j-dimensional space during the exploration phase, that is, the new position of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the exploration phase;

[0084] S223, development phase, the number of iterations within the range of [t1, T] is the development phase, first sort the hardware fault identification pigeon population, divide the hardware fault identification pigeon population into two groups, excellent and ordinary, the excellent group hardware fault identification pigeon population keeps its position unchanged, and provides its position and fitness value as parameters for the ordinary group hardware fault identification pigeon population to determine their new position, the ordinary hardware fault identification pigeon population new position calculation formula is

[0085] in It represents the new position of the hardware fault identification pigeon i in the j-dimensional space during the development stage, that is, the new position of the hardware fault identification pigeon i in the search space of the gateway hardware fault operation feature image data set A with dimension α during the development stage; It represents the best position of the excellent group of hardware fault identification pigeons in the j-dimensional space during the development stage, that is, the excellent group of hardware fault identification pigeons searches for the gateway hardware fault operation feature image data a that best matches the gateway hardware operation feature image data p in the gateway hardware fault operation feature image data set A search space with dimension α during the development stage. u location;

[0086] S224, when the algorithm meets the maximum number of iterations, output the gateway hardware operation feature image data p and the gateway hardware failure operation feature image data a u The matching results;

[0087] S225, when the gateway hardware failure operation characteristic image data a output in step S224 u If it exists, the gateway hardware failure operation feature image data a u The corresponding gateway hardware fault type identifier generates gateway hardware fault type identification result data A yingjian ;

[0088] When the gateway hardware failure operation characteristic image data a output in step S224 uIf it does not exist, it means that the intelligent power distribution gateway hardware has not identified a fault, and the gateway hardware fault type identification result data A is generated. yingjian For no fault.

[0089] The steps for inputting the original data of the gateway communication failure experiment at the gateway receiving end and collecting the translated data of the gateway communication failure experiment at the gateway output end are as follows:

[0090] S31, when the gateway hardware fault type identification result data A yingjian When the generation is completed, the gateway communication fault experiment original data b is inputted at the receiving end of the intelligent power distribution gateway through the data transmission device. The gateway communication fault experiment original data b represents the experimental transmission data used to check the intelligent power distribution gateway software configuration fault that has not been translated by the intelligent power distribution gateway in combination with the communication protocol;

[0091] S32. When the input of the original data b of the gateway communication fault experiment is completed, the original data b of the gateway communication fault experiment translated by the smart distribution network is collected at the output end of the smart distribution gateway by the data collector and the gateway communication fault experiment translated data b' is generated.

[0092] The operation steps for performing gateway software fault identification processing based on the gateway communication fault experiment translation data and the gateway communication fault experiment standard translation data and generating gateway software fault identification result data are as follows:

[0093] S41. Establishing gateway communication failure experiment standard translation data b biaozhun , Gateway communication failure experiment standard translation data b biaozhun It represents the original data b of the gateway communication failure experiment, which is the standard experimental transmission data translated by the intelligent power distribution gateway in combination with the standard communication protocol;

[0094] S42, using the KD tree nearest neighbor search algorithm to compare the gateway communication failure experiment translation data b' with the gateway communication failure experiment standard translation data b biaozhun Perform character matching on the intelligent power distribution gateway communication fault experimental data, and generate gateway software fault identification result data B according to the character matching result on the intelligent power distribution gateway communication fault experimental data;

[0095] When b' and b biaozhun The character matching of the intelligent power distribution gateway communication fault experiment data is successful, indicating that there is no software configuration fault in the intelligent power distribution gateway, and the output gateway software fault identification result data B is no fault;

[0096] When b' and b biaozhun If the character matching of the intelligent power distribution gateway communication fault experiment data fails, it means that there is a software configuration fault in the intelligent power distribution gateway, and the output gateway software fault identification result data B is faulty.

[0097] Through the gateway hardware operation feature image acquisition unit, the cloud lens is used to collect the gateway hardware operation feature image parameters in real time, providing data support for accurately identifying the hardware faults of the intelligent distribution gateway; the gateway hardware fault operation feature image storage unit and the gateway hardware operation fault identification unit cooperate with each other, scientifically preset and store the gateway hardware fault operation feature image parameters, and combine the intelligent identification algorithm with the gateway hardware operation feature image parameters for image matching, so as to accurately analyze whether the intelligent distribution gateway has a hardware fault; the gateway communication fault experiment original parameter input unit and the gateway communication fault experiment translation parameter receiving unit cooperate with each other, collect the communication fault experiment original parameters and communication fault experiment translation parameters at the input and output ends of the intelligent distribution gateway, and provide data support for the subsequent verification of the software faults of the intelligent distribution gateway; the gateway communication fault experiment standard translation parameter storage unit and the gateway software operation fault identification unit cooperate with each other, accurately store the gateway communication fault experiment standard translation parameters, combine the intelligent search algorithm with the gateway communication fault experiment translation data to perform communication data character analysis, and scientifically identify whether the intelligent distribution gateway has a software fault, so as to realize the dynamic and sensitive detection of the intelligent distribution gateway's own hardware faults and software faults.

[0098] For further information, see Figure 1 - Figure 2 , collect gateway environment feature image data and perform gateway operating environment fault type identification processing with gateway environment fault feature image data, and generate gateway operating environment fault type identification result data in the following steps:

[0099] S51, collecting feature images of the surrounding environment of the smart power distribution gateway during the power monitoring operation online through the cloud lens and generating gateway environment feature image data R;

[0100] S52, establish a gateway environment fault feature image data set C = (c1, ..., c v ,…,c β ), v = 1, 2, 3, ..., β; where c v represents the gateway environment fault feature image data corresponding to the vth gateway environment fault type, β represents the maximum number of gateway environment fault types; gateway environment fault types include the presence of electromagnetic interference equipment, the presence of radio wave interference equipment, the presence of thunderstorm lightning weather and electromagnetic shielding space structure;

[0101] S53, using a bidirectional search algorithm to compare the gateway environment feature image data R with the gateway environment fault feature image data c in the gateway environment fault feature image data set C. v Perform feature image matching of the gateway environment, and generate gateway operating environment fault type identification result data C based on the feature image matching results of the gateway environment huanjing ;

[0102] When R and c v If the characteristic image matching of the gateway environment is successful, it means that there are environmental interference factors in the surrounding environment of the intelligent power distribution gateway, and the gateway environment fault characteristic image data c is output. v The corresponding gateway environment fault type identifier generates the gateway operation environment fault type identification result data C huanjing ;

[0103] When R and c v If the characteristic image of the gateway environment is not matched successfully, it means that there is no environmental interference factor in the surrounding environment of the intelligent power distribution gateway, and the gateway operating environment fault type identification result data C is output. huanjing For no fault.

[0104] Through the gateway environment characteristic image acquisition unit, the cloud lens is used to dynamically obtain the gateway environment characteristic image parameters to provide data support for the intelligent identification of interference factors in the surrounding environment of the intelligent distribution gateway; the gateway environment fault characteristic image storage unit and the gateway operation environment fault identification unit cooperate with each other, pre-store the gateway environment fault characteristic image parameters and combine the intelligent search algorithm with the gateway environment characteristic image parameters for image analysis, so as to intelligently analyze whether there are interference factors in the operating environment of the intelligent distribution gateway, and realize the dynamic and sensitive detection of interference factors in the operating environment of the intelligent distribution gateway.

[0105] For further information, see Figure 1 - Figure 2 , collect and construct the gateway hardware and software environment fault identification result data and different gateway fault type priority data to conduct gateway fault type feedback priority analysis. The operation steps for generating gateway fault feedback priority analysis result data are as follows:

[0106] S61, gateway hardware fault type identification result data A yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing Collect and combine data to construct gateway hardware and software environment fault identification result data D = (A yingjian ,B,C huanjing );

[0107] S62. Establishing priority data sets for different gateway fault types in Indicates when the gateway hardware fault type identification result data A yingjian When a fault occurs, the intelligent power distribution gateway will send the gateway hardware fault type identification result data A yingjian According to the first priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem are provided;

[0108] Or when the gateway hardware fault type identification result data A yingjian When there is no fault and the gateway software fault identification result data B has a fault, the intelligent power distribution gateway will use the gateway software fault identification result data B as the first priority to feedback the fault problem of the intelligent power distribution gateway and the corresponding priority data of different gateway fault types;

[0109] Or when the gateway hardware fault type identification result data A yingjian There is no fault at the same time as the gateway software fault identification result data B, and the gateway operating environment fault type identification result data C huanjing When a fault occurs, the intelligent power distribution gateway will send the gateway operating environment fault type identification result data C huanjing According to the first priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem are provided;

[0110] Indicates when the gateway hardware fault type identification result data A yingjian When there is a fault at the same time as the gateway software fault identification result data B, the intelligent power distribution gateway will use the gateway software fault identification result data B according to the second priority to feedback the intelligent power distribution gateway fault problem and the corresponding gateway fault type priority data;

[0111] Or when the gateway hardware fault type identification result data A yingjian and gateway operating environment fault type identification result data C huanjing When there is a fault at the same time, the gateway software fault identification result data B is used. When there is no fault, the intelligent power distribution gateway will identify the gateway operating environment fault type result data C. huanjing According to the second priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem;

[0112] Indicates when the gateway hardware fault type identification result data A yingjian , gateway software fault identification result data B and gateway operating environment fault type identification result data C huanjing When there are faults at the same time, the intelligent power distribution gateway will identify the fault type of the gateway operating environment. huanjing According to the third priority, the priority data of different gateway fault types corresponding to the feedback of intelligent power distribution gateway fault problems;

[0113] S63, using a unified cost search algorithm to search the gateway hardware software environment fault identification result data D for the gateway hardware fault type identification result data A yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjingThe gateway fault type feedback priority analysis is performed based on the fault existence keywords of different gateway fault type priority data in different gateway fault type priority data set E, and the gateway hardware fault type identification result data A is searched out. yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The corresponding priority data of different gateway fault types are used to generate gateway fault feedback priority analysis result data E'.

[0114] The operation steps for sequentially executing the intelligent power distribution gateway fault feedback operation on the gateway hardware and software environment fault identification result data according to the gateway fault feedback priority analysis result data are as follows:

[0115] S71, analyzing the gateway hardware fault type identification result data A in the gateway fault feedback priority result data E'. yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The corresponding different gateway fault type priority data will be the gateway hardware software environment fault identification result data D in the gateway hardware fault type identification result data A yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing Execute the intelligent distribution gateway fault feedback work in order according to the gateway fault type feedback priority.

[0116] Through the gateway fault identification result collection unit, data processing of the hardware, software and environmental fault identification results of the intelligent distribution gateway is realized, and gateway hardware and software environment fault identification result parameters are constructed; different gateway fault type priority storage units, gateway fault identification result priority analysis units and gateway fault priority analysis result feedback units cooperate with each other, and standard preset priorities of different gateway fault types are combined with intelligent search algorithms and gateway hardware and software environment fault identification result parameters to perform gateway fault type feedback priority analysis, generate gateway fault feedback priority analysis result parameters, realize feedback priority analysis of different hardware, software and environmental fault identification results of the intelligent distribution gateway and execute fault feedback operations in an orderly manner, realize the evaluation of the danger and urgency of the fault types of the intelligent distribution gateway, and improve the safety and reliability of abnormal identification of the intelligent distribution gateway.

[0117] Embodiment 2:

[0118] See also Figure 1 - Figure 2The power distribution IoT intelligent gateway abnormality identification system based on the IoT platform is used to implement the power distribution IoT intelligent gateway abnormality identification method. The system includes an intelligent power distribution gateway internal fault analysis module, an intelligent power distribution gateway external fault analysis module, and an intelligent power distribution gateway fault priority analysis feedback module; the intelligent power distribution gateway internal fault analysis module, the intelligent power distribution gateway external fault analysis module and the intelligent power distribution gateway fault priority analysis feedback module are connected through IoT communication.

[0119] The internal fault analysis module of the intelligent power distribution gateway includes a gateway hardware operation characteristic image acquisition unit, a gateway hardware fault operation characteristic image storage unit, a gateway hardware operation fault identification unit, a gateway communication fault experiment original parameter input unit, a gateway communication fault experiment translation parameter receiving unit, a gateway communication fault experiment standard translation parameter storage unit, and a gateway software operation fault identification unit;

[0120] A gateway hardware operation characteristic image acquisition unit is used to acquire gateway hardware operation characteristic image data through a cloud lens; a gateway hardware fault operation characteristic image storage unit is used to store gateway hardware fault operation characteristic image data; a gateway hardware operation fault identification unit is used to perform gateway hardware fault type identification processing according to gateway hardware operation characteristic image data and gateway hardware fault operation characteristic image data, and generate gateway hardware fault type identification result data; a gateway communication fault experiment original parameter input unit is used to input gateway communication fault experiment original data at the gateway receiving end; a gateway communication fault experiment translation parameter receiving unit is used to acquire gateway communication fault experiment translation data at the gateway output end; a gateway communication fault experiment standard translation parameter storage unit is used to store gateway communication fault experiment standard translation data; a gateway software operation fault identification unit is used to perform gateway software fault identification processing according to gateway communication fault experiment translation data and gateway communication fault experiment standard translation data, and generate gateway software fault identification result data;

[0121] The external fault analysis module of the intelligent power distribution gateway includes a gateway environment feature image acquisition unit, a gateway environment fault feature image storage unit, and a gateway operating environment fault identification unit;

[0122] A gateway environment characteristic image acquisition unit is used to collect gateway environment characteristic image data through a cloud lens; a gateway environment fault characteristic image storage unit is used to store gateway environment fault characteristic image data; a gateway operation environment fault identification unit is used to identify the gateway operation environment fault type by using the gateway environment characteristic image data and the gateway environment fault characteristic image data to generate gateway operation environment fault type identification result data;

[0123] The intelligent power distribution gateway fault priority analysis feedback module includes a gateway fault identification result collection unit, a different gateway fault type priority storage unit, a gateway fault identification result priority analysis unit, and a gateway fault priority analysis result feedback unit;

[0124] A gateway fault identification result collection unit is used to collect and construct gateway hardware and software environment fault identification result data; a different gateway fault type priority storage unit is used to store different gateway fault type priority data; a gateway fault identification result priority analysis unit performs gateway fault type feedback priority analysis on the gateway hardware and software environment fault identification result data and different gateway fault type priority data to generate gateway fault feedback priority analysis result data; a gateway fault priority analysis result feedback unit performs intelligent distribution gateway fault feedback operations on the gateway hardware and software environment fault identification result data in an orderly manner according to the gateway fault feedback priority analysis result data.

[0125] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for identifying abnormalities in a power distribution IoT intelligent gateway, characterized in that: The method comprises the following steps: S1, collect gateway hardware operation feature image data; S2, performing gateway hardware fault type identification processing according to the gateway hardware operation characteristic image data and the gateway hardware fault operation characteristic image data, and generating gateway hardware fault type identification result data; S3, inputting the original data of the gateway communication failure experiment at the gateway receiving end, and collecting the translation data of the gateway communication failure experiment at the gateway output end; S4, performing gateway software fault identification processing according to the gateway communication fault experiment translation data and the gateway communication fault experiment standard translation data, and generating gateway software fault identification result data; S5, collecting gateway environment feature image data and performing gateway operating environment fault type identification processing on the gateway environment fault feature image data, and generating gateway operating environment fault type identification result data; S6. Collect and construct gateway hardware and software environment fault identification result data, perform gateway fault type feedback priority analysis on the gateway hardware and software environment fault identification result data and different gateway fault type priority data, and generate gateway fault feedback priority analysis result data; S7, according to the gateway fault feedback priority analysis result data, the gateway hardware and software environment fault identification result data is sequentially executed to perform the intelligent power distribution gateway fault feedback operation; The S1 comprises the following steps: S11, collecting feature images of the hardware operation status of the smart power distribution gateway during the power monitoring operation online through the cloud lens and generating gateway hardware operation feature image data p; The S2 comprises the following steps: S21. Establishing gateway hardware fault operation feature image data set A = (a1, ..., a u ,…,a α ), u=1,2,3,…,α; where a u represents the gateway hardware fault operation feature image data corresponding to the u-th gateway hardware fault type, and α represents the maximum number of gateway hardware fault types; S22: compare the gateway hardware operation feature image data p with the gateway hardware fault operation feature image data a in the gateway hardware fault operation feature image data set A. u Perform operation feature image matching of the gateway hardware, and generate gateway hardware fault type identification result data A based on the operation feature image matching results of the gateway hardware yingjian ; Execute and generate gateway hardware fault type identification result data A yingjian The specific steps are as follows: S221, initialization, update the number of pigeon population N and the maximum number of iterations T; S222, exploration phase, the number of iterations in the range of [0, t1] is the exploration phase, where t1 = 0.95xT. In the exploration phase, it is necessary to calculate the speed of the hardware fault identification pigeon based on the position and target of the hardware fault identification pigeon, and the current position plus the speed is the new position, that is, search for the gateway hardware fault operation feature image data a that matches the gateway hardware operation feature image data p in the search space of the gateway hardware fault operation feature image data set A. u location; S223, development phase, the number of iterations within the range of [t1, T] is the development phase, firstly, the hardware fault identification pigeon population is sorted, and the hardware fault identification pigeon population is divided into two groups, excellent and ordinary, the excellent group of hardware fault identification pigeon population keeps its position unchanged, and at the same time provides its position and fitness value as parameters for the ordinary group of hardware fault identification pigeon population to determine their new position; S224: When the algorithm meets the maximum number of iterations, output the gateway hardware operation feature image data p and the gateway hardware fault operation feature image data a. u The matching results; S225, when the gateway hardware failure operation characteristic image data a output in step S224 u If it exists, the gateway hardware failure operation feature image data a u The corresponding gateway hardware fault type identifier generates gateway hardware fault type identification result data A yingjian ; When the gateway hardware failure operation characteristic image data a output in step S224 u If it does not exist, it means that the intelligent power distribution gateway hardware has not identified a fault, and the gateway hardware fault type identification result data A is generated. yingjian For no fault; The S3 comprises the following steps: S31, when the gateway hardware fault type identification result data A yingjian When the generation is completed, the gateway communication failure experiment original data b is inputted at the receiving end of the intelligent power distribution gateway through the data transmission device, and the gateway communication failure experiment original data b represents the experimental transmission data used to check the intelligent power distribution gateway software configuration failure that has not been translated by the intelligent power distribution gateway in combination with the communication protocol; S32, when the input of the original data b of the gateway communication fault experiment is completed, the original data b of the gateway communication fault experiment translated by the smart distribution network is collected at the output end of the smart distribution gateway by a data collector and the gateway communication fault experiment translated data b' is generated; The S4 comprises the following steps: S41. Establishing gateway communication failure experiment standard translation data b biaozhun , the gateway communication failure experiment standard translation data b biaozhun It represents the standard experimental transmission data of the gateway communication failure experiment original data b translated by the intelligent power distribution gateway in combination with the standard communication protocol; S42, using the KD tree nearest neighbor search algorithm to compare the gateway communication failure experiment translation data b' with the gateway communication failure experiment standard translation data b biaozhun Perform character matching on the intelligent power distribution gateway communication fault experimental data, and generate gateway software fault identification result data B according to the character matching result on the intelligent power distribution gateway communication fault experimental data; When b' and b biaozhun The character matching of the intelligent power distribution gateway communication fault experiment data is successful, indicating that there is no software configuration fault in the intelligent power distribution gateway, and the output gateway software fault identification result data B is no fault; When b' and b biaozhun If the character matching of the intelligent power distribution gateway communication fault experiment data fails, it means that there is a software configuration fault in the intelligent power distribution gateway, and the output gateway software fault identification result data B is faulty; The S5 comprises the following steps: S51, collecting feature images of the surrounding environment of the smart power distribution gateway during the power monitoring operation online through the cloud lens and generating gateway environment feature image data R; S52, establish a gateway environment fault feature image data set C = (c1, ..., c v ,…,c β ), v = 1, 2, 3, ..., β; where c v represents the gateway environment fault feature image data corresponding to the vth gateway environment fault type, and β represents the maximum number of gateway environment fault types; S53, using a bidirectional search algorithm to compare the gateway environment feature image data R with the gateway environment fault feature image data c in the gateway environment fault feature image data set C. v Perform feature image matching of the gateway environment, and generate gateway operating environment fault type identification result data C based on the feature image matching results of the gateway environment huanjing ; When R and c v If the characteristic image matching of the gateway environment is successful, it means that there are environmental interference factors in the surrounding environment of the intelligent power distribution gateway, and the gateway environment fault characteristic image data c is output. v The corresponding gateway environment fault type identifier generates the gateway operation environment fault type identification result data C huanjing ; When R and c v If the characteristic image of the gateway environment is not matched successfully, it means that there is no environmental interference factor in the surrounding environment of the intelligent power distribution gateway, and the gateway operating environment fault type identification result data C is output. huanjing For no fault; The S6 comprises the following steps: S61, the gateway hardware fault type identification result data A yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing Collect and combine data to construct gateway hardware and software environment fault identification result data D = (A yingjian ,B,C huanjing ); S62. Establishing priority data sets for different gateway fault types in Indicates that when the gateway hardware fault type identification result data A yingjian When a fault occurs, the intelligent power distribution gateway sends the gateway hardware fault type identification result data A yingjian According to the first priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem are provided; Or when the gateway hardware fault type identification result data A yingjian There is no fault, and when the gateway software fault identification result data B has a fault, the intelligent power distribution gateway will use the gateway software fault identification result data B according to the first priority to feedback the intelligent power distribution gateway fault problem corresponding to different gateway fault type priority data; Or when the gateway hardware fault type identification result data A yingjian and the gateway software fault identification result data B do not have any faults at the same time, and the gateway operating environment fault type identification result data C huanjing When a fault occurs, the intelligent power distribution gateway sends the gateway operating environment fault type identification result data C huanjing According to the first priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem are provided; Indicates that when the gateway hardware fault type identification result data A yingjian When there is a fault at the same time as the gateway software fault identification result data B, the intelligent power distribution gateway will feedback the gateway software fault identification result data B according to the second priority level to the different gateway fault type priority data corresponding to the intelligent power distribution gateway fault problem; Or when the gateway hardware fault type identification result data A yingjian and the gateway operating environment fault type identification result data C huanjing When there is a fault at the same time, the gateway software fault identification result data B does not have a fault, and the intelligent power distribution gateway sends the gateway operating environment fault type identification result data C huanjing According to the second priority, the priority data of different gateway fault types corresponding to the feedback of the intelligent power distribution gateway fault problem; Indicates that when the gateway hardware fault type identification result data A yingjian , the gateway software fault identification result data B and the gateway operating environment fault type identification result data C huanjing When there are faults at the same time, the intelligent power distribution gateway will identify the fault type of the gateway operating environment. huanjing According to the third priority, the priority data of different gateway fault types corresponding to the feedback of intelligent power distribution gateway fault problems; S63, using a unified cost search algorithm to search the gateway hardware software environment fault identification result data D for the gateway hardware fault type identification result data A yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The gateway fault type feedback priority analysis is performed on the different gateway fault type priority data in the different gateway fault type priority data set E according to the fault existence keywords, and the gateway hardware fault type identification result data A is searched out. yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The corresponding priority data of different gateway fault types and generating gateway fault feedback priority analysis result data 'E; The S7 comprises the following steps: S71, analyzing the gateway hardware fault type identification result data A in the gateway fault feedback priority analysis result data E′ yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing The corresponding different gateway fault type priority data will be the gateway hardware fault type identification result data A in the gateway hardware and software environment fault identification result data D yingjian , Gateway software fault identification result data B, Gateway operating environment fault type identification result data C huanjing Execute the intelligent distribution gateway fault feedback work in order according to the gateway fault type feedback priority.

2. A power distribution IoT intelligent gateway abnormality identification system based on the IoT platform, used to implement the power distribution IoT intelligent gateway abnormality identification method according to claim 1, characterized in that: The system includes an intelligent power distribution gateway internal fault analysis module, an intelligent power distribution gateway external fault analysis module, and an intelligent power distribution gateway fault priority analysis feedback module.

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