Power equipment status assessment method and system

Abstract

The present invention discloses a method and system for evaluating the state of electric equipment. The method obtains the operating parameters of the electric equipment and the environmental parameters of the current environment as state influencing parameters, uses these state influencing parameters to analyze the use state of the electric equipment, obtains the state evaluation vector of the electric equipment, and then compares the state evaluation vector with each standard vector in a preset state sequence to select a target vector matching the state evaluation vector from the state sequence. Finally, the device state parameters corresponding to the target vector are used as the state evaluation result of the electric equipment. In the process of state evaluation of the electric equipment, there is no need to manually analyze the state of the electric equipment, which can improve the accuracy of state evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of power grids, and in particular to a method and system for evaluating the state of electric power equipment. Background Art

[0002] With the rapid development of power grid technology, the demand for electricity is increasing year by year, and the scale of power grids in power-intensive areas is also expanding. The increasing power load, the greatly increased number of power grid equipment, and the constantly adjusted and optimized industrial structure have put higher and higher requirements on the safe and reliable operation of urban distribution networks. Therefore, the stable operation and regular maintenance of distribution network equipment are particularly important and have become an important part of power work. Traditionally, the comprehensive management of distribution equipment is done by staff using their accumulated experience and combining the historical data recorded by the power company for manual analysis to obtain the status evaluation results of the equipment, thereby predicting the service life of the equipment, and making it easier for staff to take timely response measures. However, since manual analysis relies on the subjective factors of the staff, it will affect the accuracy of the equipment status evaluation and the reliability is not high. Summary of the invention

[0003] The purpose of the embodiments of the present invention is to provide a method and system for evaluating the state of electric equipment, which eliminates the need for manual analysis of the state of the electric equipment and improves the accuracy of the state evaluation.

[0004] To achieve the above object, an embodiment of the present invention provides a method for evaluating the state of an electric power device, comprising:

[0005] Acquire at least two state influencing parameters of the power equipment; wherein the state influencing parameters include at least one of an operating parameter of the power equipment and an environmental parameter of the current environment;

[0006] Calculate the weight of each state influencing parameter;

[0007] Calculate a parameter evaluation value of each state influencing parameter according to the weight and an average parameter value of the state influencing parameter;

[0008] Determining a state evaluation vector of the electric power equipment according to parameter evaluation values ​​of all state influencing parameters;

[0009] Comparing the state evaluation vector with each standard vector in a preset state sequence to select a target vector from the state sequence that matches the state evaluation vector;

[0010] The device state parameter corresponding to the target vector is used as the state evaluation result of the power device.

[0011] As an improvement of the above solution, the operating parameters include at least one of the equipment operating time, equipment current intensity and equipment voltage level; the environmental parameters include at least one of ambient temperature, ambient humidity and air quality.

[0012] As an improvement of the above solution, the device status parameter is the remaining usage time of the device.

[0013] As an improvement of the above solution, after obtaining at least two state influencing parameters of the power equipment, the method further includes:

[0014] All state influencing parameters collected in different detection cycles are normalized.

[0015] As an improvement of the above solution, the calculation of the weight of each state influencing parameter includes:

[0016] Calculate the ratio of each state influencing parameter to all state influencing parameters of the same type;

[0017] The weight of each state influencing parameter is calculated according to the ratio.

[0018] As an improvement of the above solution, the step of calculating the parameter evaluation value of each state influencing parameter according to the weight and the average parameter value of the state influencing parameter includes:

[0019] For each state influencing parameter, the average parameter value of the current state influencing parameter is calculated based on all state influencing parameters;

[0020] A parameter difference between the state influencing parameter and the average parameter value is calculated, and a parameter evaluation value corresponding to each state influencing parameter is obtained according to the parameter difference and a corresponding weight.

[0021] As an improvement of the above solution, determining the state evaluation vector of the power equipment according to the parameter evaluation values ​​of all state influencing parameters includes:

[0022] Constructing a parameter evaluation matrix according to the parameter evaluation values ​​of all state influencing parameters;

[0023] Calculate the covariance matrix of the power equipment according to the parameter evaluation matrix and the corresponding transposed matrix;

[0024] The state evaluation vector of the power device is calculated by using the covariance matrix, the real-time state vector of the power device, the best state vector and the worst state vector.

[0025] As an improvement of the above solution, comparing the state evaluation vector with each standard vector in a preset state sequence to select a target vector matching the state evaluation vector from the state sequence includes:

[0026] Calculate the difference between the state evaluation vector and k standard vectors in a preset state sequence; wherein the difference is an absolute value, k is an integer, and k≥2;

[0027] A minimum difference is selected from the k differences, and a standard vector corresponding to the minimum difference is used as the target vector.

[0028] As an improvement of the above solution, after the device state parameter corresponding to the target vector is used as the state evaluation result of the power device, the method further includes:

[0029] When the remaining usage time is greater than a first time threshold, marking the risk level of the current power equipment as the first level;

[0030] When the remaining usage time is greater than a second time threshold and less than or equal to the first time threshold, marking the risk level of the current power equipment as the second level;

[0031] When the remaining usage time is less than or equal to the second time threshold, the risk level of the current power equipment is marked as the third level, and a warning prompt message is issued.

[0032] To achieve the above purpose, an embodiment of the present invention further provides a power equipment status assessment system, comprising:

[0033] A state influencing parameter acquisition module, used to acquire at least two state influencing parameters of the power equipment; wherein the state influencing parameters include at least one of an operating parameter of the power equipment and an environmental parameter of the current environment;

[0034] Parameter weight calculation module, used to calculate the weight of each state influencing parameter;

[0035] A parameter evaluation value calculation module, for calculating the parameter evaluation value of each state influencing parameter according to the weight and the average parameter value of the state influencing parameter;

[0036] A state evaluation vector determination module, used to determine the state evaluation vector of the electric power equipment according to parameter evaluation values ​​of all state influencing parameters;

[0037] A state comparison module, used for comparing the state evaluation vector with each standard vector in a preset state sequence, so as to select a target vector matching the state evaluation vector from the state sequence;

[0038] The state assessment result generating module is used to take the device state parameter corresponding to the target vector as the state assessment result of the power equipment.

[0039] Compared with the prior art, the power equipment state assessment method and system disclosed in the present invention obtain the operating parameters of the power equipment and the environmental parameters of the current environment as state influencing parameters, use these state influencing parameters to analyze the usage status of the power equipment, and obtain the state assessment vector of the power equipment. Then, the state assessment vector is compared with each standard vector in a preset state sequence to select a target vector matching the state assessment vector from the state sequence. Finally, the equipment state parameters corresponding to the target vector are used as the state assessment result of the power equipment. In the state assessment process of the power equipment, there is no need to manually analyze the state of the power equipment, which can improve the accuracy of the state assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart of a method for evaluating the state of electric equipment in a system according to an embodiment of the present invention;

[0041] Figure 2 It is a structural block diagram of a power equipment status assessment system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] 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.

[0043] See also Figure 1 , Figure 1 1 is a flow chart of a method for evaluating the state of electric equipment according to an embodiment of the present invention, wherein the method for evaluating the state of electric equipment comprises:

[0044] S1. Obtain at least two state influencing parameters of the power equipment; wherein the state influencing parameters include at least one of an operating parameter of the power equipment and an environmental parameter of the current environment;

[0045] S2. Calculate the weight of each state influencing parameter;

[0046] S3, calculating a parameter evaluation value of each state influencing parameter according to the weight and the average parameter value of the state influencing parameter;

[0047] S4. Determine a state evaluation vector of the electric power equipment according to parameter evaluation values ​​of all state influencing parameters;

[0048] S5, comparing the state evaluation vector with each standard vector in a preset state sequence to select a target vector matching the state evaluation vector from the state sequence;

[0049] S6. Taking the device state parameter corresponding to the target vector as the state evaluation result of the power equipment.

[0050] Exemplarily, the device status parameter is the remaining usage time of the power equipment. In the embodiment of the present invention, the historical operating status information and environmental information of typical equipment in the distribution network are used as empirical sample data. For example, when the power equipment is just put into operation, its status data and current time are recorded regularly or at the user preset time. When the power equipment can no longer be put into use, the current time is recorded again. After calculating the time forward, the corresponding remaining usage time of different power equipment in different states is obtained. Assuming that the status data of the power equipment is collected 100 times from the first time it is put into use to the last time it is put into use, the state sequence of the power equipment is constructed as follows: , the corresponding remaining useful life sequence is ,in To ensure the best condition of the equipment, For The corresponding remaining usage time, The worst state of the device. For The corresponding remaining usage time.

[0051] It should be noted that each data in the state sequence is obtained after data processing of the state data (the data processing process of steps S1 to S4 above can be used), so as to facilitate comparison with the state evaluation vector obtained by subsequent real-time calculation. In addition, since different types of equipment have different service lives, a state sequence and a corresponding remaining service life sequence must be constructed for different types of equipment. After executing steps S1 to S4 to obtain the state evaluation vector, in step S5, the corresponding state sequence and remaining service life sequence are indexed according to the model of the power equipment, and the state evaluation vector is compared with the state sequence to obtain the target vector that best matches the state evaluation vector, and then this target vector is used in step S6 to obtain the corresponding remaining usage time from the remaining service life sequence.

[0052] In the embodiment of the present invention, since there is no need to manually analyze the state of the power equipment during the state evaluation process of the power equipment, the efficiency and accuracy of the state evaluation can be improved.

[0053] Specifically, in step S1, the operating parameters include the equipment operating time , Equipment current intensity and equipment voltage level At least one of; the environmental parameters include ambient temperature , Ambient humidity and air quality At least one of .

[0054] Exemplarily, the device operation time It is the cumulative power-on time of the power equipment recorded each time. The current intensity of the equipment is the real-time current of the power equipment, the voltage level of the equipment is the real-time voltage of the power equipment. Since the environment in which the power equipment is located changes over time, the ambient temperature can be the average temperature of the power equipment over a period of time (the period of time can be a time period within a detection cycle). Similarly, the ambient humidity and air quality It is also the average value of the power equipment over a period of time.

[0055] Furthermore, after obtaining the state influencing parameters, a state matrix of the power equipment can be constructed. Satisfies the following formula:

[0056] (1);

[0057] (2);

[0058] in, For the The first data of the power equipment collected during the detection cycle The item status affects the value of the parameter, , is the type of state-affecting parameter, ≥2, assuming that the above six state influencing parameters all exist, then The value of is 6; For the The state vector collected during the detection cycle is , is the number of detection cycles. For example, if n is 5, one detection cycle can be set every 24 hours, and data can be collected 5 times in total.

[0059] Specifically, after executing step S1, the method further includes: normalizing all state influencing parameters collected in different detection cycles.

[0060] For example, a set of data is collected in one detection cycle. The data collected during the detection cycle The data of each state are normalized to eliminate the dimension differences between different influencing factors and comprehensively consider the relative importance of influencing factors in terms of competition. The calculation formula of normalization is as follows:

[0061] (3);

[0062] in, For the Device corresponds to The item state affects the normalized value of the parameter. For the The maximum value among the item status influence parameters; For the The minimum value among the item status impact parameters.

[0063] Specifically, in step S2, the calculating the weight of each state influencing parameter includes: calculating the ratio of each state influencing parameter to all state influencing parameters of the same type; and calculating the weight of each state influencing parameter according to the ratio.

[0064] Exemplarily, the proportion and entropy value of each state influencing parameter are calculated based on the normalized data, and then the weight of each state influencing parameter is calculated. , the specific formula is:

[0065] (4);

[0066] (5);

[0067] (6);

[0068] in, For the The corresponding detection cycle The ratio of the item state influence parameter to all state influence parameters of the same type. Assuming that For the The device running time during each detection cycle The normalized value of the current device running time needs to be calculated. The running time of all devices in the detection cycle The proportion of No. The entropy value of the state influencing parameter under all state influencing parameters. In this example, the weights of the state influencing parameters of the current power equipment are shown in Table 1.

[0069] Table 1 Example of weights corresponding to state influence parameters

[0070]

[0071] Specifically, in step S3, the parameter evaluation value of each state influencing parameter is calculated based on the weight and the average parameter value of the state influencing parameter, including: for each state influencing parameter, calculating the average parameter value of the current state influencing parameter based on all state influencing parameters; calculating the parameter difference between the state influencing parameter and the average parameter value, and obtaining the parameter evaluation value corresponding to each state influencing parameter based on the parameter difference and the corresponding weight.

[0072] Exemplarily, the average parameter value of each state influencing parameter is calculated , the calculation formula is as follows:

[0073] (7).

[0074] In order to accurately calculate the distance between the device state vector and the optimal state, it is necessary to fully consider the correlation of various state influencing parameters, so it is necessary to use the covariance matrix to calculate the distance between the device state vector and the optimal state. At the same time, considering that the state of distribution network equipment is sensitive to the changes of various state influencing parameters, a small disturbance of the state influencing parameters will greatly affect the change of the device state, and the degree of influence of each state influencing parameter on the device state is different, so the weight of each state influencing parameter is introduced. , and the concavity of the equipment influencing parameters is increased by the square term. The specific formula is:

[0075] (8);

[0076] in, For the During the detection cycle, the device Parameter evaluation values ​​corresponding to item status impact parameters; For the The parameter difference between the item state affecting the parameter and the corresponding average parameter value.

[0077] Specifically, in step S4, the state evaluation vector of the power equipment is determined according to the parameter evaluation values ​​of all state influencing parameters, including: constructing a parameter evaluation matrix according to the parameter evaluation values ​​of all state influencing parameters; calculating the covariance matrix of the power equipment according to the parameter evaluation matrix and the corresponding transposed matrix; and calculating the state evaluation vector of the power equipment using the covariance matrix, the real-time state vector of the power equipment, the optimal state vector and the worst state vector.

[0078] Exemplarily, in this step, the state evaluation vector of the current power device is compared with the state evaluation vector of the same type of power device stored in advance. The state vector in is compared to obtain the best matching result. Before that, all state influencing parameters of the current power equipment need to be integrated. This process is achieved by constructing a covariance matrix. The calculation process of the covariance matrix satisfies the following formula:

[0079] (9);

[0080] (10);

[0081] in, For the Parameter evaluation matrix of the equipment during each detection cycle; is the covariance matrix of the power equipment.

[0082] Exemplarily, the real-time state vector is determined by the state influence parameter acquired in real time, and the best state vector and the worst state vector are determined by the historical state influence parameter. The Mahalanobis distance is calculated based on the improved covariance matrix, and the exponential term and distance parameter are introduced. Further determine the state evaluation vector For the sensitivity of changes in influencing factors, the specific formula is:

[0083] (11);

[0084] (12);

[0085] (13);

[0086] (14);

[0087] (15);

[0088] in, is the real-time state vector With the best state vector The Mahalanobis distance, is the real-time state vector and the worst state vector The Mahalanobis distance of is the difference between the real-time state vector of the device and the optimal state vector, is the difference between the real-time state vector of the device and the worst state vector, is a distance parameter, which can be taken as 1.7 in this example.

[0089] Specifically, in step S5, the state evaluation vector is compared with each standard vector in a preset state sequence to select a target vector matching the state evaluation vector from the state sequence, including: calculating the difference between the state evaluation vector and k standard vectors in the preset state sequence; wherein the difference is an absolute value, k is an integer, and k≥2; selecting the minimum difference from the k differences, and taking the standard vector corresponding to the minimum difference as the target vector.

[0090] For example, after obtaining a state evaluation vector After that, the corresponding state sequence is indexed according to the model of the power equipment. Since there are n detection cycles at this time, the state evaluation vector corresponding to the n detection cycles can be Sequence of states Each state vector in Compare and get n*k differences , The calculation formula is as follows:

[0091] (16).

[0092] Specifically, in step S6, after calculation of formula (16), for each detection cycle, the minimum difference is selected from the k differences to obtain n target vectors that best match the state evaluation vector. For example, if the target vector corresponding to one of the detection cycles is the state sequence In , then from the remaining useful life sequence The corresponding remaining usage time is obtained as Thus, n remaining usage times can be obtained, and the final remaining usage time of the power equipment can be obtained by taking the average of the n remaining usage times.

[0093] Furthermore, the embodiment of the present invention provides another method for calculating the remaining usage time. In step S5, after obtaining a state evaluation vector After that, continue to calculate the remaining state evaluation vectors in n cycles, and then calculate the average value to obtain the average state evaluation vector corresponding to the power equipment in n detection cycles According to the model of the power equipment, the corresponding state sequence is indexed and the average state evaluation vector is calculated. With state sequence Each state vector in The difference , The calculation formula is as follows:

[0094] (17).

[0095] Specifically, in step S6, after calculation according to formula (17), a target vector that best matches the average state evaluation vector is obtained, and then the corresponding remaining time is obtained as the final remaining usage time of the power equipment.

[0096] Specifically, after the above steps S1 to S6, the remaining usage time of the current power equipment can be obtained, which is convenient for the staff to give an early warning of the remaining usage time of the equipment. The first time threshold and the second time threshold are pre-divided, and the first time threshold is greater than the second time threshold. At this time, there are the following situations:

[0097] 1) When the remaining usage time is greater than the first time threshold, the risk level of the current power equipment is marked as the first level, which means that the power equipment can still be used for a long time and no warning is issued at this time;

[0098] 2) When the remaining usage time is greater than the second time threshold and less than or equal to the first time threshold, the risk level of the current power equipment is marked as the second level, which means that the power equipment can still be used for a long time, but the staff needs to pay attention to the subsequent use of the equipment;

[0099] 3) When the remaining usage time is less than or equal to the second time threshold, the risk level of the current power equipment is marked as the third level, and a warning prompt message is issued. The third level indicates that the life of this power equipment is short, and preparations for replacing the equipment need to be made at any time.

[0100] Compared with the prior art, the method for evaluating the state of electric equipment disclosed in the present invention obtains the operating parameters of the electric equipment and the environmental parameters of the current environment as state influencing parameters, uses these state influencing parameters to analyze the usage state of the electric equipment, and obtains the state evaluation vector of the electric equipment. The state evaluation vector is then compared with each standard vector in a preset state sequence to select a target vector matching the state evaluation vector from the state sequence. Finally, the device state parameters corresponding to the target vector are used as the state evaluation result of the electric equipment. In the process of state evaluation of the electric equipment, there is no need to manually analyze the state of the electric equipment, which can improve the accuracy of the state evaluation.

[0101] See also Figure 2 , Figure 2 1 is a structural block diagram of a power equipment status assessment system 100 provided in an embodiment of the present invention, wherein the power equipment status assessment system 100 comprises:

[0102] The state influencing parameter acquisition module 11 is used to acquire at least two state influencing parameters of the power equipment; wherein the state influencing parameters include at least one of the operating parameters of the power equipment and the environmental parameters of the current environment;

[0103] A parameter weight calculation module 12 is used to calculate the weight of each state influencing parameter;

[0104] Parameter evaluation value calculation module 13, for calculating the parameter evaluation value of each state influencing parameter according to the weight and the average parameter value of the state influencing parameter;

[0105] A state evaluation vector determination module 14, configured to determine a state evaluation vector of the power equipment according to parameter evaluation values ​​of all state influencing parameters;

[0106] A state comparison module 15, for comparing the state evaluation vector with each standard vector in a preset state sequence, so as to select a target vector matching the state evaluation vector from the state sequence;

[0107] The state assessment result generating module 16 is used to take the device state parameter corresponding to the target vector as the state assessment result of the power device.

[0108] Specifically, the device status parameter is the remaining use time of the device. The operating parameter includes at least one of the device operating time, device current intensity and device voltage level; the environmental parameter includes at least one of the ambient temperature, ambient humidity and air quality.

[0109] Specifically, the power equipment status assessment system 100 further includes:

[0110] The data processing module is used to normalize all state influencing parameters collected in different detection cycles.

[0111] Specifically, the parameter weight calculation module 12 is specifically used to: calculate the ratio of each state influencing parameter to all state influencing parameters of the same type; and calculate the weight of each state influencing parameter according to the ratio.

[0112] Specifically, the parameter evaluation value calculation module 13 is specifically used to: for each state influencing parameter, calculate the average parameter value of the current state influencing parameter based on all state influencing parameters; calculate the parameter difference between the state influencing parameter and the average parameter value, and calculate the parameter evaluation value corresponding to each state influencing parameter based on the parameter difference and the corresponding weight.

[0113] Specifically, the state evaluation vector determination module 14 is specifically used to: construct a parameter evaluation matrix based on parameter evaluation values ​​of all state influencing parameters; calculate the covariance matrix of the power equipment based on the parameter evaluation matrix and the corresponding transposed matrix; and calculate the state evaluation vector of the power equipment using the covariance matrix, the real-time state vector of the power equipment, the optimal state vector and the worst state vector.

[0114] Specifically, the state comparison module 15 is specifically used to: calculate the difference between the state evaluation vector and k standard vectors in a preset state sequence; wherein the difference is an absolute value, k is an integer, and k≥2; select the minimum difference from the k differences, and use the standard vector corresponding to the minimum difference as the target vector.

[0115] Specifically, the power equipment status assessment system 100 also includes an early warning module, which is used to: when the remaining usage time is greater than a first time threshold, mark the risk level of the current power equipment as the first level; when the remaining usage time is greater than a second time threshold, and is less than or equal to the first time threshold, mark the risk level of the current power equipment as the second level; when the remaining usage time is less than or equal to the second time threshold, mark the risk level of the current power equipment as the third level, and issue an early warning prompt message.

[0116] It is worth noting that the working process of each module in the power equipment status assessment system 100 described in the embodiment of the present invention can refer to the working process of the power equipment status assessment method described in the above embodiment, and will not be repeated here.

[0117] Compared with the prior art, the power equipment state assessment system 100 disclosed in the present invention obtains the operating parameters of the power equipment and the environmental parameters of the current environment as state influencing parameters, uses these state influencing parameters to analyze the usage status of the power equipment, and obtains the state assessment vector of the power equipment, and then compares the state assessment vector with each standard vector in a preset state sequence to select a target vector matching the state assessment vector from the state sequence, and finally uses the equipment state parameters corresponding to the target vector as the state assessment result of the power equipment. In the process of state assessment of the power equipment, there is no need to manually analyze the state of the power equipment, which can improve the accuracy of the state assessment.

[0118] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for evaluating the state of electric power equipment, characterized in that: include: Acquire at least two state influencing parameters of the power equipment; wherein the state influencing parameters include at least one of an operating parameter of the power equipment and an environmental parameter of the current environment; Calculate the weight of each state influencing parameter; Calculate a parameter evaluation value of each state influencing parameter according to the weight and an average parameter value of the state influencing parameter; Determining a state evaluation vector of the electric power equipment according to parameter evaluation values ​​of all state influencing parameters; Comparing the state evaluation vector with each standard vector in a preset state sequence to select a target vector from the state sequence that matches the state evaluation vector; Taking the device state parameter corresponding to the target vector as the state assessment result of the power device; The step of calculating the parameter evaluation value of each state influencing parameter according to the weight and the average parameter value of the state influencing parameter comprises: for each state influencing parameter, calculating the average parameter value of the current state influencing parameter according to all state influencing parameters; calculating the parameter difference between the state influencing parameter and the average parameter value, and obtaining the parameter evaluation value corresponding to each state influencing parameter according to the parameter difference and the corresponding weight; The method of determining the state evaluation vector of the electric power equipment according to the parameter evaluation values ​​of all state influencing parameters includes: constructing a parameter evaluation matrix according to the parameter evaluation values ​​of all state influencing parameters; calculating the covariance matrix of the electric power equipment according to the parameter evaluation matrix and the corresponding transposed matrix; and calculating the state evaluation vector of the electric power equipment using the covariance matrix, the real-time state vector of the electric power equipment, the optimal state vector and the worst state vector.

2. The method for evaluating the state of electric power equipment according to claim 1, characterized in that: The operating parameters include at least one of the equipment operating time, equipment current intensity and equipment voltage level; the environmental parameters include at least one of the ambient temperature, ambient humidity and air quality.

3. The method for evaluating the state of electric power equipment according to claim 1, characterized in that: The device status parameter is the remaining usage time of the device.

4. The method for evaluating the state of electric power equipment according to claim 1, characterized in that: After obtaining at least two state influencing parameters of the power equipment, the method further includes: All state influencing parameters collected in different detection cycles are normalized.

5. The method for evaluating the state of electric power equipment according to claim 1, characterized in that: The calculating the weight of each state influencing parameter includes: Calculate the ratio of each state influencing parameter to all state influencing parameters of the same type; The weight of each state influencing parameter is calculated according to the ratio.

6. The method for evaluating the state of electric power equipment according to claim 1, characterized in that: The step of comparing the state evaluation vector with each standard vector in a preset state sequence to select a target vector matching the state evaluation vector from the state sequence includes: Calculate the difference between the state evaluation vector and k standard vectors in a preset state sequence; wherein the difference is an absolute value, k is an integer, and k≥2; A minimum difference is selected from the k differences, and a standard vector corresponding to the minimum difference is used as the target vector.

7. The method for evaluating the state of electric power equipment according to claim 3, characterized in that: After the device state parameter corresponding to the target vector is used as the state evaluation result of the power device, the method further includes: When the remaining usage time is greater than a first time threshold, marking the risk level of the current power equipment as the first level; When the remaining usage time is greater than a second time threshold and less than or equal to the first time threshold, marking the risk level of the current power equipment as the second level; When the remaining usage time is less than or equal to the second time threshold, the risk level of the current power equipment is marked as the third level, and an early warning prompt message is issued.

8. A power equipment status assessment system, characterized in that: include: A state influencing parameter acquisition module, used to acquire at least two state influencing parameters of the power equipment; wherein the state influencing parameters include at least one of an operating parameter of the power equipment and an environmental parameter of the current environment; Parameter weight calculation module, used to calculate the weight of each state influencing parameter; A parameter evaluation value calculation module, used to calculate the parameter evaluation value of each state influencing parameter according to the weight and the average parameter value of the state influencing parameter; A state evaluation vector determination module, used to determine the state evaluation vector of the electric power equipment according to parameter evaluation values ​​of all state influencing parameters; a state comparison module, configured to compare the state evaluation vector with each standard vector in a preset state sequence, so as to select a target vector matching the state evaluation vector from the state sequence; A state assessment result generating module, used for taking the device state parameter corresponding to the target vector as the state assessment result of the power device; The parameter evaluation value calculation module is specifically used to: for each state influencing parameter, calculate the average parameter value of the current state influencing parameter according to all state influencing parameters; calculate the parameter difference between the state influencing parameter and the average parameter value, and calculate the parameter evaluation value corresponding to each state influencing parameter according to the parameter difference and the corresponding weight; The state evaluation vector determination module is specifically used to: construct a parameter evaluation matrix based on the parameter evaluation values ​​of all state influencing parameters; calculate the covariance matrix of the power equipment based on the parameter evaluation matrix and the corresponding transposed matrix; and calculate the state evaluation vector of the power equipment using the covariance matrix, the real-time state vector of the power equipment, the optimal state vector and the worst state vector.

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