Power distribution Internet of Things health state assessment method

Abstract

The invention relates to the technical field of power distribution Internet of Things, and discloses a power distribution Internet of Things health state assessment method, which comprises the following steps: S1, data acquisition and classification; s2, calculating a health index; s3, calculating a fault index; s4, calculating a state index; and S5, comprehensively evaluating the health state. According to the invention, the problems of low accuracy and the like in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution Internet of Things, and in particular to a health status assessment method for power distribution Internet of Things. Background Art

[0002] The power distribution IoT is a network system that enables the identification, perception, interconnection, and control of power grid infrastructure, personnel, and the environment. Based on advanced sensors, controls, and software applications, it leverages new ICT technologies such as big data, cloud computing, IoT, mobile internet, and artificial intelligence to connect billions of devices, machines, and systems across energy production, transmission, and consumption, forming the "Internet of Things foundation" for a new power system. In smart grids, the power distribution IoT plays a crucial supporting role and is crucial for accelerating the digital transformation of the power industry.

[0003] The power distribution IoT connects all aspects of the power system, creating a smart service system that enables the interconnection of all things and human-machine interaction. It can visualize energy and information flows with photovoltaic power generation, energy storage, ground-source heat pumps, and various home appliances. Through a smart energy control system, it can sense and optimize various energy states, enabling unified management of all business data for power companies, and promoting the digitalization, informatization, and intelligent development of my country's leading power distribution IoT.

[0004] Evaluating the health status of power distribution IoT terminal devices is of great significance in ensuring the normal operation of equipment, improving the efficiency and safety of energy systems, and reducing operation and maintenance costs.

[0005] Traditional methods for evaluating the health of power distribution IoT terminal devices suffer from inaccuracy. Current health assessment methods often rely on historical data and empirical inferences, making it difficult to accurately predict the actual health of the device. Furthermore, due to the complexity and variability of the device's operating environment, assessment results often contain certain errors. Summary of the Invention

[0006] In order to overcome the shortcomings of the existing technology, the present invention provides a health status assessment method for the power distribution Internet of Things to solve the problems of low accuracy in the existing technology.

[0007] The technical solution adopted by the present invention to solve the above problems is:

[0008] A method for evaluating the health status of a power distribution Internet of Things comprises the following steps:

[0009] S1, data collection and classification: collects the operating data of each terminal device in the power distribution Internet of Things, and classifies the data into a health data set for evaluating the health index of the terminal device, a fault data set for evaluating the failure rate of the terminal device, and a status data set for evaluating the status of the terminal device;

[0010] S2, health index calculation: use the health data in the health data set to calculate the health index f1 of the terminal device during operation;

[0011] S3, Fault Index Calculation: Calculate the fault rate of the terminal device during operation using the fault data in the fault data set, classify the fault type according to the change in the fault rate, and calculate the fault index f2 of the terminal device during operation;

[0012] S4, state index calculation: using the state data of each component in the state data set, evaluate the state of the terminal device during operation and calculate the state index f3 of the terminal device during operation;

[0013] S5, comprehensive health status assessment: Calculate the health status assessment index of the distribution Internet of Things based on the health index, fault index and status index, and refer to the health status assessment index threshold to conduct a comprehensive assessment of the health status of the distribution Internet of Things.

[0014] As a preferred technical solution, step S2 includes the following steps:

[0015] S21: Split the data in the health data set into a safety data subset, a reliability data subset, an economic data subset, and an environmental protection data subset;

[0016] S22, the security data subset includes the network stability coefficient k1, the anti-interference coefficient k2, and the failure rate k3 caused by network attacks;

[0017] S23, calculating the safety factor K1 of the terminal device during operation;

[0018] S24, calculating the reliability coefficient K2 of each terminal device in the power distribution Internet of Things based on the availability coefficient e1, stability coefficient e2, and durability coefficient e3;

[0019] S25, let the environmental protection data subset B = (b1, b2, ..., bn); where b1, b2, ..., bn n are the 1st, 2nd, ..., nth environmental protection data respectively, and n is the amount of data in the environmental protection data subset;

[0020] S26, establish the environmental data matrix B = [b1, b2, ..., b n ], construct the threshold data matrix B′=[b1′,b2′,…,b n ′], make the difference BB′ between matrix B and matrix B′, and calculate the pollution coefficient Get the pollution coefficient matrix X=[x1,x2,…,x n ]; where b1′, b2′, …, b n′ are the thresholds of the 1st, 2nd, ..., nth environmental protection data, x1, x2, ..., x n are the pollution coefficients of the 1st, 2nd,…,nth environmental data respectively;

[0021] S27, using the pollution coefficient matrix X to sum up to obtain the environmental protection coefficient K3: Where i is the number of the pollution coefficient;

[0022] S28, calculating the health index f1 using the safety factor K1, the reliability factor K2 and the environmental protection factor K3.

[0023] As a preferred technical solution, in step S22, the expressions of the network stability coefficient k1, the anti-interference coefficient k2, and the failure rate k3 generated by the network attack are respectively:

[0024]

[0025]

[0026]

[0027] Among them, f max is the peak value of network fluctuation, f min is the valley value of network fluctuation, u1 is the number of times the network virus fails to attack the terminal device, u2 is the number of times the network virus successfully attacks the terminal device, and u max is the number of network viruses found to be threatening terminal devices, v1 is the number of times the terminal device malfunctions when attacked by the network, and v2 is the total number of times the terminal device is attacked by the network.

[0028] As a preferred technical solution, in step S23, the safety factor K1 of the terminal device during operation is expressed as:

[0029]

[0030] Among them, g1 is the influence coefficient of network stability, g2 is the influence coefficient of anti-interference, and g3 is the influence coefficient of the failure rate caused by network attack on security.

[0031] As a preferred technical solution, in step S24, the reliability coefficient K2 of the terminal device is expressed as:

[0032]

[0033] Among them, E1 is the influence coefficient of availability on the reliability of the terminal device, E2 is the influence coefficient of stability on the reliability of the terminal device, E3 is the influence coefficient of durability on the reliability of the terminal device, A1 is the number of times the opening instruction is sent to the terminal device, a1 is the number of times the terminal device can be opened during use, a2 is the number of times the terminal device can be used stably during the process of opening and using, A2 is the rated usage time of the terminal device, and a3 is the actual usage time of the terminal device.

[0034] As a preferred technical solution, in step S28, the expression of the health index f1 is:

[0035] f1=w1K1+w2K2+w3K3+W;

[0036] Among them, w1 is the weight coefficient of safety, w2 is the weight coefficient of reliability, w3 is the weight coefficient of environmental protection, and W is the allowable fluctuation value.

[0037] As a preferred technical solution, step S3 includes the following steps:

[0038] S31: Calculate the failure rate G based on the number of failures reported per unit time and the number of uses of the terminal device during use;

[0039] S32: drawing a failure rate curve according to the failure rates in different time periods, and using the failure rate curve types of different terminal devices to classify the failure types of the terminal devices into a decreasing failure rate class, a constant failure rate class, and an increasing failure rate class;

[0040] S33: Establishing a calculation model for the fault index f2 according to the change rates of different fault types.

[0041] As a preferred technical solution, in step S33, the calculation model of the fault index f2 is expressed as follows:

[0042]

[0043] Wherein, h is the minimum failure rate of the terminal device, t is the usage time of the terminal device, t1 is the number of failures of the terminal device, t2 is the number of times the terminal device is used, t1<t2, and j is the parameter of the failure index calculation model of the failure rate decreasing class.

[0044] As a preferred technical solution, in step S4, the calculation formula of the state index f3 is:

[0045]

[0046] Among them, I is the number of status data, m is the number of status data, M I is the I-th state data, is the status data M I The threshold value, o I is the restriction weight of the state data, and λ is the coefficient of the restriction weight.

[0047] As a preferred technical solution, step S5 includes the following steps:

[0048] S51, using the health index, fault index and status index to calculate the health status assessment index F of the power distribution Internet of Things: F = f1 + f2 + f3;

[0049] S52, setting the health status assessment index threshold F 阈值 , when F>F 阈值 , then the health status of the power distribution Internet of Things is judged to be poor, when F≤F 阈值 , then the health status of the power distribution Internet of Things is judged to be excellent.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] (1) The present invention utilizes modern technologies such as big data and intelligence to comprehensively perceive, analyze, predict, and make decisions on the operating status of power distribution IoT device terminals. Based on big data security, the present invention improves the ability to discover, identify, understand, analyze, and process security threats from a global perspective, thereby enabling decisions and actions related to security.

[0052] (2) The present invention accurately evaluates the operating status of the device terminal, understands the status and changes of the device during operation, and promptly discovers and resolves potential faults or problems;

[0053] (3) The present invention utilizes panoramic situational awareness to achieve comprehensive awareness of equipment status and reduce information blind spots; panoramic situational awareness can provide real-time feedback based on actual operating conditions, optimize evaluation processes and methods, and thus improve the accuracy and efficiency of evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a schematic diagram of the steps of a method for evaluating the health status of a power distribution Internet of Things according to the present invention;

[0055] Figure 2 The failure rate curve is shown in Figure 2. DETAILED DESCRIPTION

[0056] The present invention will be further described in detail below with reference to the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0057] Example 1

[0058] like Figures 1 to 2As shown, in response to the shortcomings of the existing technology, the present invention provides a panoramic situational awareness and evaluation method for the terminal equipment status of the power distribution Internet of Things, which can fully and accurately display the operating status of all terminal devices in the power distribution Internet of Things and accurately evaluate the health status.

[0059] The present invention discloses a method for evaluating the health status of a power distribution Internet of Things, comprising the following steps: collecting data of each terminal device in the power distribution Internet of Things during operation; calculating the safety coefficient, reliability coefficient and environmental protection coefficient of the terminal device during operation, and calculating the health index of the terminal device during operation; calculating the fault index of the terminal device during operation; calculating the status index of the terminal device during operation; calculating the health status evaluation index of the power distribution Internet of Things based on the health index, fault index and status index, and performing a comprehensive evaluation of the health status of the power distribution Internet of Things with reference to a health status evaluation index threshold.

[0060] A method for evaluating the health status of a power distribution Internet of Things comprises the following steps:

[0061] S1: Collects data from the operation of each terminal device in the power distribution Internet of Things, and classifies the data into a health data set for evaluating the health index of the terminal device, a fault data set for evaluating the failure rate of the terminal device, and a status data set for evaluating the status of the terminal device;

[0062] S2: Split the data in the health data set into a safety data subset, a reliability data subset, and an environmental protection data subset; calculate the safety factor, reliability factor, and environmental protection factor of the terminal device during operation, and calculate the health index of the terminal device during operation;

[0063] S3: Using the fault data in the fault data set, calculate the failure rate of the terminal device during operation, classify the fault type according to the change in the failure rate, and calculate the failure index of the terminal device during operation;

[0064] S4: Using the status data of each component in the status data set, evaluate the status of the terminal device during operation, discover potential faults of each component, and calculate the status index of the terminal device during operation;

[0065] S5: Calculate the health status assessment index of the distribution Internet of Things based on the health index, fault index and status index, and make a comprehensive assessment of the health status of the distribution Internet of Things with reference to the health status assessment index threshold.

[0066] Furthermore, step S2 includes:

[0067] S21: Split the data in the health data set into a safety data subset, a reliability data subset, an economic data subset, and an environmental protection data subset;

[0068] S22: The security data subset includes the network stability coefficient k1, the anti-interference coefficient k2, and the failure rate k3 caused by network attacks;

[0069]

[0070] Among them, f max is the peak value of network fluctuation, f min is the valley value of network fluctuation, u1 is the number of times the network virus fails to attack the terminal device, u2 is the number of times the network virus successfully attacks the terminal device, and u max is the number of network viruses found to be threatening terminal devices, v1 is the number of times the terminal device malfunctions when attacked by the network, and v2 is the total number of times the terminal device is attacked by the network;

[0071] S23: Calculate the safety factor K1 of the terminal equipment during operation:

[0072]

[0073] Among them, g1, g2, and g3 are the influence coefficients of network stability, anti-interference, and failure rate caused by network attacks on security respectively;

[0074] S24: Calculate the reliability coefficient K2 of the terminal equipment based on the availability coefficient e1, stability coefficient e2, and durability coefficient e2 of each terminal equipment in the power distribution Internet of Things:

[0075]

[0076] Among them, E1, E2, and E3 are the influence coefficients of availability, stability, and durability on the reliability of the terminal device respectively; A1 is the number of times the opening command is sent to the terminal device, a1 is the number of times the terminal device can be opened during use, a2 is the number of times the terminal device can be used stably during the opening process, A2 is the rated usage time of the terminal device, and a3 is the actual usage time of the terminal device;

[0077] S25: The environmental data subset includes noise data, light pollution data, radiation pollution data, heat pollution data, and waste pollution data during the operation of the terminal equipment. The environmental data subset B = (b1, b2, ..., b n ), bn is the nth data, and n is the amount of data in the environmental protection data subset;

[0078] S26: Establish environmental data matrix B = [b1, b2, ..., b n ], construct the threshold data matrix B′=[b1′,b2′,…,b n ′],b n ′ is the nth data bn The threshold value is used to make a difference BB′ between matrix B and matrix B′, and the pollution coefficient is calculated. Get the pollution coefficient matrix X=[x1,x2,…,x n ];

[0079] S27: The pollution coefficient matrix X is summed to obtain the environmental protection coefficient K3: i is the number of the pollution coefficient;

[0080] S28: Calculate the health index f1 using the safety factor K1, reliability factor K2, and environmental factor K3:

[0081] f1=w1K1+w2K2+w3K3+W;

[0082] Among them, w1, w2, and w3 are the weight coefficients of safety, reliability, and environmental protection, respectively, and W is the allowable fluctuation value.

[0083] Furthermore, step S3 includes:

[0084] S31: Calculate the failure rate G based on the number of failures reported per unit time and the number of uses of the terminal device during use;

[0085] S32: drawing a failure rate curve according to the failure rates in different time periods, and using the failure rate curve types of different terminal devices to classify the failure types of the terminal devices into a decreasing failure rate class, a constant failure rate class, and an increasing failure rate class;

[0086] S33: Establish a calculation model for the fault index f2 based on the change rate of different fault types:

[0087]

[0088] Wherein, h is the minimum failure rate of the terminal device, t is the usage time of the terminal device, t1<t2, and j is the parameter of the failure index calculation model of the failure rate decreasing class.

[0089] Furthermore, the calculation method of the state index f3 is:

[0090]

[0091] Among them, M I is the I-th state data, I is the number of the state data, is the status data M I The threshold value, o I is the restriction weight of the state data, and λ is the coefficient of the restriction weight.

[0092] Furthermore, step S5 includes:

[0093] S51: Calculate the health status assessment index F of the power distribution Internet of Things using the health index, fault index, and status index: F = f1 + f2 + f3;

[0094] S52: Setting the health status assessment index threshold F 阈值 , when F>F 阈值 , then the health status of the power distribution Internet of Things is judged to be poor, when F≤F 阈值 , then the health status of the power distribution Internet of Things is judged to be excellent.

[0095] Example 2

[0096] like Figures 1 to 2 As shown, as a further optimization of Example 1, based on Example 1, this embodiment also includes the following technical features:

[0097] like Figure 1 As shown, a method for evaluating the health status of a power distribution Internet of Things includes the following steps:

[0098] S1: Collects data from the operation of each terminal device in the power distribution Internet of Things, and classifies the data into a health data set for evaluating the health index of the terminal device, a fault data set for evaluating the failure rate of the terminal device, and a status data set for evaluating the status of the terminal device;

[0099] S2: Split the data in the health data set into a safety data subset, a reliability data subset, an economic data subset, and an environmental protection data subset; calculate the safety factor, reliability factor, and environmental protection factor of the terminal device during operation, and calculate the health index of the terminal device during operation.

[0100] The health of the power distribution IoT can be evaluated from four perspectives: safety, reliability, economy, and greenness. The safety dimension primarily considers the stability, anti-interference capability, and failure rate of the device during operation; the reliability dimension primarily considers the availability, stability, and durability of the device; the economy dimension primarily considers the energy consumption, operating costs, and economic benefits of the device; and the greenness dimension primarily considers the environmental impact and environmental performance of the device during operation.

[0101] Step S2 includes:

[0102] S21: Split the data in the health data set into a safety data subset, a reliability data subset, an economic data subset, and an environmental protection data subset;

[0103] S22: The security data subset includes the network stability coefficient k1, the anti-interference coefficient k2, and the failure rate k3 caused by network attacks;

[0104]

[0105] Among them, fmax is the peak value of network fluctuation, f min is the valley value of network fluctuation, u1 is the number of times the network virus fails to attack the terminal device, u2 is the number of times the network virus successfully attacks the terminal device, and u max is the number of network viruses found to be threatening terminal devices, v1 is the number of times the terminal device malfunctions when attacked by the network, and v2 is the total number of times the terminal device is attacked by the network;

[0106] S23: Calculate the safety factor K1 of the terminal equipment during operation:

[0107]

[0108] Among them, g1, g2, and g3 are the influence coefficients of network stability, anti-interference, and failure rate caused by network attacks on security respectively;

[0109] S24: Calculate the reliability coefficient K2 of the terminal equipment based on the availability coefficient e1, stability coefficient e2, and durability coefficient e2 of each terminal equipment in the power distribution Internet of Things:

[0110]

[0111] Among them, E1, E2, and E3 are the influence coefficients of availability, stability, and durability on the reliability of the terminal device respectively; A1 is the number of times the opening command is sent to the terminal device, a1 is the number of times the terminal device can be opened during use, a2 is the number of times the terminal device can be used stably during the opening process, A2 is the rated usage time of the terminal device, and a3 is the actual usage time of the terminal device;

[0112] S25: The environmental data subset includes noise data, light pollution data, radiation pollution data, heat pollution data, and waste pollution data during the operation of the terminal equipment. The environmental data subset B = (b1, b2, ..., b n ), bn is the nth data, and n is the amount of data in the environmental protection data subset;

[0113] S26: Establish environmental data matrix B = [b1, b2, ..., b n ], construct the threshold data matrix B′=[b1′,b2′,…,b n ′],b n ′ is the nth data b n The threshold value is used to make a difference BB′ between matrix B and matrix B′, and the pollution coefficient is calculated. Get the pollution coefficient matrix X=[x1,x2,…,x n ];

[0114] S27: The pollution coefficient matrix X is summed to obtain the environmental protection coefficient K3: i is the number of the pollution coefficient;

[0115] S28: Calculate the health index f1 using the safety factor K1, reliability factor K2, and environmental factor K3:

[0116] f1=w1K1+w2K2+w3K3+W;

[0117] Among them, w1, w2, and w3 are the weight coefficients of safety, reliability, and environmental protection, respectively, and W is the allowable fluctuation value.

[0118] S3: Using the fault data in the fault data set, calculate the failure rate of the terminal device during operation, classify the fault type according to the change of the failure rate, and calculate the failure index of the terminal device during operation.

[0119] The failure rate of a power distribution IoT device terminal refers to the probability of a device failure during operation, typically measured as the number of failures per unit time. The failure rate of a power distribution IoT device is a key indicator of device health, reflecting its stability and reliability during operation. Failures in a power distribution IoT device can impact the stability and reliability of the power system and even cause inconvenience and losses to people's lives and production.

[0120] Step S3 includes:

[0121] S31: Calculate the failure rate G by dividing the number of failures per unit time by the number of uses of the terminal device during use;

[0122] S32: Draw a failure rate curve based on the failure rate in different time periods, such as Figure 2 As shown, using the failure rate curve types of different terminal devices, the failure types of terminal devices are classified into a failure rate decreasing class, a failure rate constant class, and a failure rate increasing class;

[0123] S33: Establish a calculation model for the fault index f2 based on the change rate of different fault types:

[0124]

[0125] Where h is the minimum failure rate of the terminal device, t is the usage time of the terminal device, t1 is the number of failures of the terminal device, t2 is the number of times the terminal device is used, t1 < t2, and j is the parameter of the failure index calculation model for the decreasing failure rate category. The corresponding failure index calculation model is derived based on the change in failure rate.

[0126] S4: Use the status data of each component in the status data set to evaluate the status of the terminal device during operation, discover potential faults of each component, and calculate the status index of the terminal device during operation.

[0127] Equipment condition evaluation assesses the current state of equipment to determine its health status or performance level. This involves collecting and analyzing the equipment's technical parameters, operating data, and test data. Its primary purpose is to understand the equipment's status and changes during operation, enabling timely identification and resolution of potential faults or issues to ensure normal operation.

[0128] The calculation method of the state index f3 is:

[0129]

[0130] Among them, M I is the I-th state data, I is the number of the state data, is the status data M I The threshold value, o I is the restriction weight of the state data, and λ is the coefficient of the restriction weight.

[0131] S5: Calculate the health status assessment index of the distribution Internet of Things based on the health index, fault index and status index, and make a comprehensive assessment of the health status of the distribution Internet of Things with reference to the health status assessment index threshold.

[0132] Step S5 includes:

[0133] S51: Calculate the health status assessment index F of the power distribution Internet of Things using the health index, fault index, and status index: F = f1 + f2 + f3;

[0134] S52: Setting the health status assessment index threshold F 阈值 , when F>F 阈值 , then the health status of the power distribution Internet of Things is judged to be poor, when F≤F 阈值 , then the health status of the power distribution Internet of Things is judged to be excellent.

[0135] As described above, the present invention can be preferably implemented.

[0136] All features disclosed in all embodiments in this specification, or steps in all methods or processes implicitly disclosed, except for mutually exclusive features and / or steps, can be combined and / or expanded or replaced in any manner.

[0137] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Based on the technical essence of the present invention and within the spirit and principles of the present invention, any simple modification, equivalent replacement and improvement of the above embodiment shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for evaluating the health status of a power distribution Internet of Things, characterized in that: The following steps are involved: S1, data collection and classification: collects the operating data of each terminal device in the power distribution Internet of Things, and classifies the data into a health data set for evaluating the health index of the terminal device, a fault data set for evaluating the failure rate of the terminal device, and a status data set for evaluating the status of the terminal device; S2, health index calculation: use the health data in the health data set to calculate the health index f1 of the terminal device during operation; S3, Fault Index Calculation: Calculate the fault rate of the terminal device during operation using the fault data in the fault data set, classify the fault type according to the change in the fault rate, and calculate the fault index f2 of the terminal device during operation; S4, state index calculation: using the state data of each component in the state data set, evaluate the state of the terminal device during operation and calculate the state index f3 of the terminal device during operation; S5, comprehensive health status assessment: Calculate the health status assessment index of the distribution Internet of Things based on the health index, fault index and status index, and refer to the health status assessment index threshold to conduct a comprehensive assessment of the health status of the distribution Internet of Things.

2. A method for evaluating the health status of a power distribution Internet of Things according to claim 1, characterized in that: Step S2 includes the following steps: S21: Split the data in the health data set into a safety data subset, a reliability data subset, an economic data subset, and an environmental protection data subset; S22, the security data subset includes the network stability coefficient k1, the anti-interference coefficient k2, and the failure rate k3 caused by network attacks; S23, calculating the safety factor K1 of the terminal device during operation; S24, calculating the reliability coefficient K2 of each terminal device in the power distribution Internet of Things based on the availability coefficient e1, stability coefficient e2, and durability coefficient e3; S25, let the environmental protection data subset B = (b1, b2, ..., bn); where b1, b2, ..., bn n are the 1st, 2nd, ..., nth environmental protection data respectively, and n is the amount of data in the environmental protection data subset; S26, establish the environmental data matrix B = [b1, b2, ..., b n ], construct the threshold data matrix B′=[b1′,b2′,…,b n ′], make the difference BB′ between matrix B and matrix B′, and calculate the pollution coefficient Get the pollution coefficient matrix X=[x1,x2,…,x n ]; where b1′, b2′, …, b n ′ are the thresholds of the 1st, 2nd, ..., nth environmental protection data, x1, x2, ..., x n are the pollution coefficients of the 1st, 2nd,…,nth environmental data respectively; S27, using the pollution coefficient matrix X to sum up to obtain the environmental protection coefficient K3: Where i is the number of the pollution coefficient; S28, calculating the health index f1 using the safety factor K1, the reliability factor K2 and the environmental protection factor K3.

3. A method for evaluating the health status of a power distribution Internet of Things according to claim 2, characterized in that: In step S22, the expressions of the network stability coefficient k1, the anti-interference coefficient k2, and the failure rate k3 generated by the network attack are respectively: Among them, f max is the peak value of network fluctuation, f min is the valley value of network fluctuation, u1 is the number of times the network virus fails to attack the terminal device, u2 is the number of times the network virus successfully attacks the terminal device, and u max is the number of network viruses found to be threatening terminal devices, v1 is the number of times the terminal device malfunctions when attacked by the network, and v2 is the total number of times the terminal device is attacked by the network.

4. A method for evaluating the health status of a power distribution Internet of Things according to claim 2, characterized in that: In step S23, the safety factor K1 of the terminal device during operation is expressed as: Among them, g1 is the influence coefficient of network stability, g2 is the influence coefficient of anti-interference, and g3 is the influence coefficient of the failure rate caused by network attack on security.

5. The method for evaluating the health status of a power distribution Internet of Things according to claim 2, wherein: In step S24, the reliability coefficient K2 of the terminal device is expressed as: Among them, E1 is the influence coefficient of availability on the reliability of the terminal device, E2 is the influence coefficient of stability on the reliability of the terminal device, E3 is the influence coefficient of durability on the reliability of the terminal device, A1 is the number of times the opening instruction is sent to the terminal device, a1 is the number of times the terminal device can be opened during use, a2 is the number of times the terminal device can be used stably during the process of opening and using, A2 is the rated usage time of the terminal device, and a3 is the actual usage time of the terminal device.

6. A method for evaluating the health status of a power distribution Internet of Things according to claim 2, characterized in that: In step S28, the expression of the health index f1 is: f1=w1K1+w2K2+w3K3+W; Among them, w1 is the weight coefficient of safety, w2 is the weight coefficient of reliability, w3 is the weight coefficient of environmental protection, and W is the allowable fluctuation value.

7. The method for evaluating the health status of a power distribution Internet of Things according to claim 1, characterized in that: Step S3 includes the following steps: S31: Calculate the failure rate G based on the number of failures reported per unit time and the number of uses of the terminal device during use; S32: drawing a failure rate curve according to the failure rates in different time periods, and using the failure rate curve types of different terminal devices to classify the failure types of the terminal devices into a decreasing failure rate class, a constant failure rate class, and an increasing failure rate class; S33: Establishing a calculation model for the fault index f2 according to the change rates of different fault types.

8. A method for evaluating the health status of a power distribution Internet of Things according to claim 7, characterized in that: In step S33, the calculation model of the fault index f2 is expressed as follows: Wherein, h is the minimum failure rate of the terminal device, t is the usage time of the terminal device, t1 is the number of failures of the terminal device, t2 is the number of times the terminal device is used, t1<t2, and j is the parameter of the failure index calculation model of the failure rate decreasing class.

9. The method for evaluating the health status of a power distribution Internet of Things according to claim 1, characterized in that: In step S4, the calculation formula of the state index f3 is: Among them, I is the number of status data, m is the number of status data, M I is the I-th state data, is the status data M I The threshold value, o I is the restriction weight of the state data, and λ is the coefficient of the restriction weight.

10. A method for evaluating the health status of a power distribution Internet of Things according to any one of claims 1 to 9, characterized in that: Step S5 includes the following steps: S51, using the health index, fault index and status index to calculate the health status assessment index F of the power distribution Internet of Things: F = f1 + f2 + f3; S52, setting the health status assessment index threshold F 阈值 , when F>F 阈值 , then the health status of the power distribution Internet of Things is judged to be poor, when F≤F 阈值 , then the health status of the power distribution Internet of Things is judged to be excellent.

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