Power transmission and transformation equipment health diagnosis method and system

Abstract

The invention discloses a power transmission and transformation equipment health diagnosis method and system, relates to the technical field of equipment diagnosis, and solves the technical problems that the equipment state cannot be monitored in real time and potential faults are difficult to find in time. By acquiring the sensor data corresponding to the abnormal monitoring signal and matching the sensor data with the historical data, the abnormal reason is accurately found out, the fault diagnosis efficiency is improved, after the abnormal reason is determined, the abnormal influence factor is further calculated, and the influence of the abnormality on multiple aspects of the equipment is considered, so that the assessment of the abnormal condition of the equipment is more comprehensive, and the assessment efficiency is improved. According to the method, the change trend of the equipment performance can be better predicted, the health degree of the equipment can be more accurately judged by calculating a performance evaluation index and comparing the performance evaluation index with a normal evaluation index in the self-adaptive diagnosis analysis unit, and more detailed and accurate equipment health condition information can be provided for operators through a refined diagnosis mode; and making of more reasonable maintenance plans and decisions is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment diagnosis, and in particular to a method and system for health diagnosis of power transmission and transformation equipment. Background Art

[0002] As the scale of power grid continues to expand, the number of power transmission and transformation equipment is large and widely distributed. Traditional manual inspections and simple monitoring methods are difficult to meet the real-time and accurate grasp of equipment status.

[0003] According to the publication number CN118709152A, a method, system and equipment for health diagnosis of power transmission and transformation equipment are disclosed. The method includes: obtaining state parameters of historical power transmission and transformation equipment, analyzing the state parameters of historical power transmission and transformation equipment to first determine the single-state quantity weight coefficient, and then using the single-state quantity weight coefficient to determine the single-state quantity coupling weight coefficient; using the single-state quantity coupling weight coefficient as the input of the health diagnosis model and the equipment fault type as the output, to construct an integrated health diagnosis model; training the integrated health diagnosis model to obtain a target integrated health diagnosis model; inputting the single-state quantity coupling weight coefficient of the current power transmission and transformation equipment into the target integrated health diagnosis model, and predicting and outputting the fault type of the current power transmission and transformation equipment.

[0004] The above patented comprehensive decision tree can handle irrelevant features and the high accuracy of artificial neural networks, thereby improving the overall accuracy of diagnosis. However, when using some existing diagnostic methods, since the power transmission and transformation equipment is in a high voltage and high current working environment for a long time, it is easy to be affected by various factors and cause failure or performance degradation. It is impossible to monitor the equipment status in real time and it is difficult to detect potential failures in time, which affects the subsequent use of the power transmission and transformation equipment. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for diagnosing the health of power transmission and transformation equipment, which solves the problem of being unable to monitor the equipment status in real time and difficulty in timely discovering potential faults.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for health diagnosis of power transmission and transformation equipment, the method specifically comprising the following steps: Step S1: acquiring sensor data of power transmission and transformation equipment, and cleaning the acquired sensor data to obtain pre-processed data; Step S2: Analyze the preprocessed data and extract corresponding data features, extract feature data of the power transmission and transformation equipment under normal operation according to historical data to obtain normal data, and compare the data features with the normal data to obtain a comparison result; Step S3: Analyze the abnormal monitoring signal obtained, determine the abnormal cause according to the abnormal sensor data, and calculate the abnormal impact factor based on the abnormal cause; Step S4: Calculate the performance evaluation index of the power transmission and transformation equipment, and calculate based on different sensor data conditions, and calculate the normal evaluation index of the power transmission and transformation equipment; Step S5, the obtained performance evaluation index is compared with the normal evaluation index to generate a judgment result, and a health diagnosis is performed on the power transmission and transformation equipment according to the judgment result to generate diagnostic information.

[0007] As a further solution of the present invention, the specific method of obtaining the comparison result in step S2 is: Acquire preprocessed data, and extract data features of the preprocessed data. Similarly, extract feature data of normal working conditions in historical data, and record them as normal data, and the normal data is an interval value. Compare the acquired data features with the normal data. If the data characteristics meet the normal data, it means that the working state of the power transmission and transformation equipment is normal, and a normal monitoring signal is generated. If the data characteristics do not meet the normal data, it means that the working state of the power transmission and transformation equipment is abnormal, and an abnormal monitoring signal is generated.

[0008] As a further solution of the present invention, the specific method of analyzing the abnormal monitoring signal in step S3 is: The sensor data corresponding to the abnormal monitoring signal is obtained and recorded as abnormal sensor data. Then the historical data is obtained, and the abnormal sensor data is matched with the historical data to determine the cause of the abnormality. At the same time, the influence of the determined abnormal cause on the power transmission and transformation equipment is analyzed, and different influencing factors are further calculated.

[0009] As a further solution of the present invention, the specific method of calculating the performance evaluation index of the power transmission and transformation equipment in step S4 is: Calculate the performance evaluation indexes of the power transmission and transformation equipment corresponding to the normal monitoring signals and the abnormal monitoring signals; The method for calculating the performance evaluation index of the power transmission and transformation equipment corresponding to the normal monitoring signal is as follows: the load loss, no-load loss and short-circuit impedance of the power transmission and transformation equipment are obtained as P0, Q0 and Z0 respectively, and the load loss, no-load loss and short-circuit impedance are standardized to obtain the load loss standardized value , no-load loss standardization value and short-circuit impedance normalized value ; Substitute the obtained parameters into the formula The performance evaluation index H of power transmission and transformation equipment is calculated, and , and They are the weight coefficients of load loss, no-load loss and short-circuit impedance respectively, and the specific values ​​are set by the operator.

[0010] As a further solution of the present invention, the method for calculating the power transmission and transformation equipment performance evaluation index corresponding to the abnormal monitoring signal in step S4 is: Obtain the abnormal impact factor corresponding to the abnormal monitoring signal, and calculate the performance evaluation index of the power transmission and transformation equipment corresponding to the abnormal monitoring signal in the same way as the calculation method for the normal monitoring signal; Similarly, the calculation method of normal monitoring signals and abnormal monitoring signals is used to calculate the normal evaluation index and record it in Hz.

[0011] As a further solution of the present invention, the specific method of generating the judgment result in step S5 is: The calculated performance evaluation index is compared with the normal evaluation index. If the performance evaluation index H is greater than or equal to the normal evaluation index Hz, a normal signal is generated. If the performance evaluation index H is less than the normal evaluation index Hz, a diagnostic analysis signal is generated. At the same time, the diagnostic analysis signal is analyzed to generate diagnostic information.

[0012] As a further solution of the present invention, the specific method of analyzing the diagnostic analysis signal to generate diagnostic information in step S5 is: Different health level intervals are generated based on the normal evaluation index Hz, and the performance evaluation index H is matched with the health level intervals to generate diagnostic information.

[0013] A health diagnosis system for power transmission and transformation equipment, comprising a data acquisition unit, a state analysis unit, an abnormality diagnosis unit, an adaptive diagnosis analysis unit and an information output unit; A data acquisition unit, which is used to clean the acquired sensor data to obtain pre-processed data, and transmit the pre-processed data to the state analysis unit; A state analysis unit, which is used to extract data features of preprocessed data, obtain normal data in combination with historical data, and compare the data features with the normal data to generate a normal monitoring signal and an abnormal monitoring signal, and then transmit the normal monitoring signal to the adaptive diagnosis analysis unit, and transmit the abnormal monitoring signal to the abnormal diagnosis unit; An abnormality diagnosis unit, which is used to analyze the acquired abnormal monitoring signal, determine the abnormal cause based on the abnormal sensor data corresponding to the abnormal monitoring signal, calculate the abnormality impact factor according to the abnormal cause, and then transmit the abnormality impact factor to the adaptive diagnosis analysis unit; An adaptive diagnosis and analysis unit, which is used to analyze the acquired normal monitoring signals, calculate the performance evaluation index of the power transmission and transformation equipment and compare it with the normal evaluation index, and calculate the performance evaluation index of the power transmission and transformation equipment with abnormal working conditions for the abnormal transmission influencing factors, and compare it with the normal evaluation index to generate a judgment result, and at the same time, perform health diagnosis on the power transmission and transformation equipment according to the judgment result to generate diagnostic information, and then transmit the diagnostic information to the information output unit; An information output unit is used to display the acquired diagnostic information to the corresponding operator.

[0014] Beneficial Effects The present invention provides a method and system for health diagnosis of power transmission and transformation equipment. Compared with the prior art, it has the following beneficial effects: In the abnormal diagnosis unit of the present invention, by acquiring sensor data corresponding to the abnormal monitoring signal and matching it with historical data, the cause of the abnormality is accurately found, thereby improving the efficiency of fault diagnosis. After determining the cause of the abnormality, the abnormal impact factor is further calculated, and the impact of the abnormality on the equipment in many aspects is taken into account, so that the evaluation of the abnormal situation of the equipment is more comprehensive and the changing trend of the equipment performance can be better predicted. In the adaptive diagnosis and analysis unit, by calculating the performance evaluation index and comparing it with the normal evaluation index, the health of the equipment can be more accurately judged. The refined diagnosis method can provide the operator with more detailed and accurate equipment health status information, which is helpful to formulate more reasonable maintenance plans and decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a step method diagram of the present invention; Figure 2 This is a block diagram of the system principle of the present invention. DETAILED DESCRIPTION

[0016] 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.

[0017] For example, see Figure 1 The present application provides a method for health diagnosis of power transmission and transformation equipment, which specifically includes the following steps: Step S1: acquiring sensor data of power transmission and transformation equipment, and cleaning the acquired sensor data to obtain pre-processed data.

[0018] The sensor data is obtained, and the sensor data here includes voltage data, current data, power data and temperature data, etc. The specific temperature data is obtained through the corresponding temperature sensor, and the voltage data, current data and power data are obtained through the corresponding voltmeter, ammeter and electric power meter. At the same time, the obtained sensor data is cleaned, and the cleaning process includes removing interference factors such as noise and outliers. For example, some erroneous data points may be generated due to sensor failure or electromagnetic interference, which need to be identified and processed by a data cleaning algorithm. The specific data cleaning belongs to the existing technology and will not be described in detail here. The preprocessed data is obtained after the data cleaning process.

[0019] Step S2: Analyze the preprocessed data and extract corresponding data features, extract feature data of the power transmission and transformation equipment under normal operation according to historical data to obtain normal data, and compare the data features with the normal data to obtain a comparison result.

[0020] Acquire preprocessed data, and extract data features of the preprocessed data. Here, data features are represented as data generated when the corresponding power transmission and transformation equipment is working. Similarly, extract data features of preprocessed data, extract feature data under normal working conditions in historical data, and record them as normal data. Normal data is an interval value. For example, for transformers, their oil temperature should be continuously monitored, because oil temperature is one of the important indicators reflecting the operating status of transformers. During normal operation, the oil temperature should be within a certain reasonable range. Therefore, this reasonable range is recorded as normal data. For example, for an oil-immersed transformer with a rated capacity of 50MVA, its oil temperature should generally be controlled between 50°C and 70°C during normal operation. Compare the acquired data features with the normal data. If the data feature satisfies the normal data, specifically indicating that the data feature is within the normal data range, for example, the oil temperature in the data feature is 55°C, and the oil temperature in the normal data is 50°C to 70°C, further indicating that the data feature is within the range, then it indicates that the working state of the power transmission and transformation equipment is normal, and a normal monitoring signal is generated; if the data feature does not satisfy the normal data, specifically indicating that the data feature is not within the normal data range, for example, the oil temperature in the data feature is 75°C, and the oil temperature in the normal data is 50°C to 70°C, further indicating that the data feature is not within the range, then it indicates that the working state of the power transmission and transformation equipment is abnormal, and an abnormal monitoring signal is generated.

[0021] Step S3: Analyze the obtained abnormal monitoring signal, determine the abnormal cause according to the abnormal sensor data, and calculate the abnormal impact factor based on the abnormal cause.

[0022] The sensor data corresponding to the abnormal monitoring signal is obtained and recorded as abnormal sensor data, and then the historical data is obtained, and the abnormal sensor data is matched with the historical data to determine the cause of the abnormality. The specific matching method here is to obtain the same data as the abnormal sensor data in the historical data, and determine the cause of the abnormality based on the same data obtained. The abnormal causes for the abnormal sensor data in the specific historical data are the same. At the same time, the influence of the determined abnormal cause on the power transmission and transformation equipment is analyzed, and different influencing factors are further calculated. Taking temperature as an example, when the temperature is determined to be the cause of the abnormality, the influence of the temperature abnormality on the load loss, no-load loss and short-circuit impedance of the power transmission and transformation equipment is analyzed, and according to the influence value To determine the corresponding influencing factors, suppose that after analysis and calculation, it is found that due to the increase in oil temperature to 85°C, the load loss of the transformer increased by 10% (assuming that the normal load loss is P0, and the load loss becomes 1.1P0 in an abnormal situation), the no-load loss increased by 5% (assuming that the normal no-load loss is Q0, and the no-load loss becomes 1.05Q0 in an abnormal situation), and the short-circuit impedance changed by 3% (assuming that the normal short-circuit impedance is Z0, and the short-circuit impedance becomes 1.03Z0 in an abnormal situation). The corresponding influencing factors are determined based on these influencing values. For example, the load loss influence factor can be set to 0.1 (indicating the proportional coefficient of the increase in load loss), the no-load loss influence factor to 0.05, and the short-circuit impedance influence factor to 0.03.

[0023] Step S4: Calculate the performance evaluation index of the power transmission and transformation equipment, and calculate based on different sensor data conditions, and calculate the normal evaluation index of the power transmission and transformation equipment at the same time.

[0024] The specific method for calculating the performance evaluation index of the power transmission and transformation equipment corresponding to the normal monitoring signal is as follows: The load loss, no-load loss and short-circuit impedance of the power transmission and transformation equipment are obtained, and the load loss is recorded as P0. The load loss can be measured by a short-circuit test. The winding on one side of the transformer is short-circuited, and the rated frequency voltage is applied to the winding on the other side to make the current in the winding reach the rated value. At this time, the input power is the load loss and is recorded as P0. At the same time, the load loss is standardized to obtain the load loss standardized value. According to the calculation formula Calculate the load loss normalized value ,and is the minimum value of load loss (the theoretical minimum value when the equipment is operating normally or the minimum value in historical data), is the maximum value of the load loss (usually a reasonable upper limit is determined according to the equipment specifications or experience), and the no-load loss is recorded as Q0. The no-load loss is measured by the no-load test. The secondary side of the transformer is open-circuited, and the rated voltage of the rated frequency is applied to the primary side. At this time, the input power is the no-load loss, and according to the formula The calculated no-load loss standardized value is recorded as ,and is the minimum no-load loss, is the maximum value of no-load loss, the short-circuit impedance is recorded as Z0, and the short-circuit impedance is calculated as follows: In the short-circuit test, the short-circuit voltage is assumed to be U k , rated voltage is U N , and the short-circuit impedance is calculated according to the formula , where I N is the rated current, and according to the formula The calculated short-circuit impedance standardized value is recorded as ,and is the minimum value of short-circuit impedance, is the maximum value of short-circuit impedance; Assume that for a certain type of transformer, the following parameters are determined through a large amount of historical data statistics and equipment performance analysis: Load loss range: =1000W, =5000W; No-load loss range: =500W, =2000W; Short circuit impedance range: =4Ω, =10Ω; The actual measurement value at a certain moment is =3000W, =1200W, =6Ω, and the load loss value, no-load loss value and short-circuit impedance are standardized to obtain =0.5, =0.467, =0.33.

[0025] Then substitute the obtained parameters into the formula The performance evaluation index H of power transmission and transformation equipment is calculated, and , and are the weight coefficients of load loss, no-load loss and short-circuit impedance respectively. The specific values ​​are set by the operator. Assuming that the weight coefficients are determined by the hierarchical analysis method, , and The specific values ​​are 0.4, 0.3 and 0.3 respectively. The performance evaluation index calculated by the above formula is 0.44.

[0026] The specific method for calculating the performance evaluation index of the power transmission and transformation equipment corresponding to the abnormal monitoring signal is as follows: The abnormal impact factor corresponding to the abnormal monitoring signal is obtained. Similarly, the above calculation method is used to calculate the performance evaluation index of the power transmission and transformation equipment corresponding to the abnormal monitoring signal. The specific calculation method is to substitute the calculated abnormal impact factor into the corresponding standardized value. For example, if the abnormal impact factor is the no-load loss impact factor, the product of the control loss impact factor and the no-load loss standardized value is calculated, and the abnormal impact factor is substituted into the formula in this way.

[0027] Similarly, the above calculation method is used to calculate the normal evaluation index Hz, and the specific value of the normal evaluation index is set by the operator.

[0028] Step S5, the obtained performance evaluation index is compared with the normal evaluation index to generate a judgment result, and a health diagnosis is performed on the power transmission and transformation equipment according to the judgment result to generate diagnostic information.

[0029] The calculated performance evaluation index is compared with the normal evaluation index. If the performance evaluation index H is greater than or equal to the normal evaluation index Hz, a normal signal is generated. If the performance evaluation index H is less than the normal evaluation index Hz, a diagnostic analysis signal is generated. Taking the above example as an example, if the performance evaluation index H is 0.44 and the normal evaluation index is 0.4, the performance evaluation index is greater than the normal evaluation index, and a warning analysis signal is generated. If the normal evaluation index is calculated to be 0.5, a diagnostic analysis signal is generated.

[0030] The generated diagnostic analysis signal is processed, different health level intervals are generated based on the normal evaluation index Hz, and the performance evaluation index H is matched with the health level interval, and diagnostic information is generated. The matching result is obtained here, and the specific matching result is the health status corresponding to the current power transmission and transformation equipment.

[0031] For example 2, please refer to Figure 2 The present application provides a health diagnosis system for power transmission and transformation equipment, including: a data acquisition unit, a state analysis unit, an abnormal diagnosis unit, an adaptive diagnosis analysis unit and an information output unit, and at the same time combines Figure 2 It can be known that the above functional units are electrically connected in a unidirectional manner.

[0032] The data acquisition unit is used to clean the acquired sensor data to obtain pre-processed data, and transmit the pre-processed data to the state analysis unit. The specific method of obtaining the pre-processed data here is the same as the processing process of step S1 in the first embodiment.

[0033] A state analysis unit is used to extract data features of preprocessed data, obtain normal data in combination with historical data, and compare the data features with the normal data to generate normal monitoring signals and abnormal monitoring signals. The normal monitoring signals are then transmitted to the adaptive diagnosis analysis unit, and the abnormal monitoring signals are transmitted to the abnormal diagnosis unit. The specific method of generating normal monitoring signals and abnormal monitoring signals here is similar to the processing process of step S2 in Example 1.

[0034] An abnormality diagnosis unit is used to analyze the acquired abnormal monitoring signal, and determine the cause of the abnormality based on the abnormal sensor data corresponding to the abnormal monitoring signal, and calculate the abnormality impact factor according to the abnormal cause. The specific method of calculating the abnormality impact factor here is the same as the processing process of step S4 in embodiment 1, and then the abnormality impact factor is transmitted to the adaptive diagnosis analysis unit.

[0035] An adaptive diagnostic analysis unit is used to analyze the acquired normal monitoring signals, and by comparing the performance evaluation index of the power transmission and transformation equipment with the normal evaluation index, calculate the performance evaluation index of the power transmission and transformation equipment with abnormal working conditions for the abnormal transmission influencing factors, and compare them with the normal evaluation index to generate a judgment result, and at the same time, perform health diagnosis on the power transmission and transformation equipment according to the judgment result to generate diagnostic information, and then transmit the diagnostic information to the information output unit, and the specific method of generating the diagnostic information here is the same as the processing method of steps S4 and S5 of embodiment 1.

[0036] An information output unit is used to display the acquired diagnostic information to the corresponding operator.

[0037] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0038] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for health diagnosis of power transmission and transformation equipment, characterized in that: The method specifically comprises the following steps: Step S1: acquiring sensor data of power transmission and transformation equipment, and cleaning the acquired sensor data to obtain pre-processed data; Step S2: Analyze the preprocessed data and extract corresponding data features, extract feature data of the power transmission and transformation equipment under normal operation according to historical data to obtain normal data, and compare the data features with the normal data to obtain a comparison result; Step S3: Analyze the abnormal monitoring signal obtained, determine the abnormal cause according to the abnormal sensor data, and calculate the abnormal impact factor based on the abnormal cause; Step S4: Calculate the performance evaluation index of the power transmission and transformation equipment, and calculate based on different sensor data conditions, and calculate the normal evaluation index of the power transmission and transformation equipment; Step S5, the obtained performance evaluation index is compared with the normal evaluation index to generate a judgment result, and a health diagnosis is performed on the power transmission and transformation equipment according to the judgment result to generate diagnostic information.

2. A method for health diagnosis of power transmission and transformation equipment according to claim 1, characterized in that: The specific method of obtaining the comparison result in step S2 is: Acquire preprocessed data, and extract data features of the preprocessed data. Similarly, extract feature data of normal working conditions in historical data, and record them as normal data, and the normal data is an interval value. Compare the acquired data features with the normal data. If the data characteristics meet the normal data, it means that the working state of the power transmission and transformation equipment is normal, and a normal monitoring signal is generated. If the data characteristics do not meet the normal data, it means that the working state of the power transmission and transformation equipment is abnormal, and an abnormal monitoring signal is generated.

3. A method for health diagnosis of power transmission and transformation equipment according to claim 1, characterized in that: The specific method of analyzing the abnormal monitoring signal in step S3 is: The sensor data corresponding to the abnormal monitoring signal is obtained and recorded as abnormal sensor data. Then the historical data is obtained, and the abnormal sensor data is matched with the historical data to determine the cause of the abnormality. At the same time, the influence of the determined abnormal cause on the power transmission and transformation equipment is analyzed, and different influencing factors are further calculated.

4. A method for health diagnosis of power transmission and transformation equipment according to claim 1, characterized in that: The specific method of calculating the performance evaluation index of the power transmission and transformation equipment in step S4 is: Calculate the performance evaluation indexes of the power transmission and transformation equipment corresponding to the normal monitoring signals and the abnormal monitoring signals; The method for calculating the performance evaluation index of the power transmission and transformation equipment corresponding to the normal monitoring signal is as follows: the load loss, no-load loss and short-circuit impedance of the power transmission and transformation equipment are obtained as P0, Q0 and Z0 respectively, and the load loss, no-load loss and short-circuit impedance are standardized to obtain the load loss standardized value , no-load loss standardization value and short-circuit impedance normalized value ; Substitute the obtained parameters into the formula The performance evaluation index H of power transmission and transformation equipment is calculated, and , and They are the weight coefficients of load loss, no-load loss and short-circuit impedance respectively, and the specific values ​​are set by the operator.

5. A method for health diagnosis of power transmission and transformation equipment according to claim 4, characterized in that: The method for calculating the power transmission and transformation equipment performance evaluation index corresponding to the abnormal monitoring signal in step S4 is: Obtain the abnormal impact factor corresponding to the abnormal monitoring signal, and calculate the performance evaluation index of the power transmission and transformation equipment corresponding to the abnormal monitoring signal in the same way as the calculation method for the normal monitoring signal; Similarly, the calculation method of normal monitoring signals and abnormal monitoring signals is used to calculate the normal evaluation index and record it in Hz.

6. A method for health diagnosis of power transmission and transformation equipment according to claim 1, characterized in that: The specific method of generating the judgment result in step S5 is: The calculated performance evaluation index is compared with the normal evaluation index. If the performance evaluation index H is greater than or equal to the normal evaluation index Hz, a normal signal is generated. If the performance evaluation index H is less than the normal evaluation index Hz, a diagnostic analysis signal is generated. At the same time, the diagnostic analysis signal is analyzed to generate diagnostic information.

7. A method for health diagnosis of power transmission and transformation equipment according to claim 6, characterized in that: The specific method of analyzing the diagnostic analysis signal to generate diagnostic information in step S5 is: Different health level intervals are generated based on the normal evaluation index Hz, and the performance evaluation index H is matched with the health level intervals to generate diagnostic information.

8. A power transmission and transformation equipment health diagnosis system, used to execute a power transmission and transformation equipment health diagnosis method according to any one of claims 1 to 7, characterized in that: It includes a data acquisition unit, a state analysis unit, an abnormality diagnosis unit, an adaptive diagnosis analysis unit and an information output unit; A data acquisition unit, which is used to clean the acquired sensor data to obtain pre-processed data, and transmit the pre-processed data to the state analysis unit; A state analysis unit, which is used to extract data features of preprocessed data, obtain normal data in combination with historical data, and compare the data features with the normal data to generate a normal monitoring signal and an abnormal monitoring signal, and then transmit the normal monitoring signal to the adaptive diagnosis analysis unit, and transmit the abnormal monitoring signal to the abnormal diagnosis unit; An abnormality diagnosis unit, which is used to analyze the acquired abnormal monitoring signal, determine the abnormal cause based on the abnormal sensor data corresponding to the abnormal monitoring signal, calculate the abnormality impact factor according to the abnormal cause, and then transmit the abnormality impact factor to the adaptive diagnosis analysis unit; An adaptive diagnosis and analysis unit, which is used to analyze the acquired normal monitoring signals, calculate the performance evaluation index of the power transmission and transformation equipment and compare it with the normal evaluation index, and calculate the performance evaluation index of the power transmission and transformation equipment with abnormal working conditions for the abnormal transmission influencing factors, and compare it with the normal evaluation index to generate a judgment result, and at the same time, perform health diagnosis on the power transmission and transformation equipment according to the judgment result to generate diagnostic information, and then transmit the diagnostic information to the information output unit; An information output unit is used to display the acquired diagnostic information to the corresponding operator.

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