The invention discloses a failure diagnosis method for a power transformer winding based on a GSMallat-NIN-CNN network. The failure diagnosis method includes: measuring a vibration condition of the transformer winding by using a multi-channel sensor to obtain multi-source vibration data of the transformer; converting the multi-source vibration data obtained through measurement into gray-scale images through GST gray-scale conversion; decomposing, by using a Mallat algorithm, each gray-scale image layer by layer into a high-frequency component sub-image and a low-frequency component sub-image, and fusing the sub-images; reconstructing fused gray-scale images, and coding vibration gray-scale images according to respective failure states of the transformer winding; establishing a failure diagnosis model for the transformer based on the GSMallat-NIN-CNN network; and randomly initializing network parameters to divide a training set and a test set, and training and tuning the network by using the training set; and testing the trained network by using the test set.

A transformer condition evaluation method combining a FAHP-DEMATEL method and a CRITIC method is provided and includes: selecting a plurality sets of condition quantities, building a hierarchical indicator system; calculating a degree of influencing and a degree of being influenced by using the DEMATEL method on a subjective level, calculating a weight of each of a plurality of indicators of an indicator layer through the FAHP-DEMATEL method, calculating the weights of the indicators of the indicator layer through the CRITIC method on an objective level; calculating an optimal weight according to the subjective weights of the indicators and the objective weights of the indicators; and calculating condition scores layer by layer, finally determining an actual health condition of each of a plurality of transformers by combining condition level classification rules. In the disclosure, the weights are calculated based on the subjective level and the objective level.

A transformer condition evaluation method combining a FAHP-DEMATEL method and a CRITIC method is provided and includes: selecting a plurality sets of condition quantities, building a hierarchical indicator system; calculating a degree of influencing and a degree of being influenced by using the DEMATEL method on a subjective level, calculating a weight of each of a plurality of indicators of an indicator layer through the FAHP-DEMATEL method, calculating the weights of the indicators of the indicator layer through the CRITIC method on an objective level; calculating an optimal weight according to the subjective weights of the indicators and the objective weights of the indicators; and calculating condition scores layer by layer, finally determining an actual health condition of each of a plurality of transformers by combining condition level classification rules. In the disclosure, the weights are calculated based on the subjective level and the objective level.

A monitoring system for sensing electrical parameters including current and voltage can comprise a current transformer and an antenna. The current transformer can be configured to sense current passing through a conductor. The antenna can be configured to sense electrical potential of the conductor by sensing an electric field generated by the conductor. The antenna can sense the electrical potential independent of whether current is present in the conductor. The monitoring system can further comprise a temperature sensor configured to sense a temperature of the conductor. A sensing module can include a housing supporting the current transformer, the antenna, and the temperature sensor for monitoring an electrical power circuit.

A monitoring system for sensing electrical parameters including current and voltage can comprise a current transformer and an antenna. The current transformer can be configured to sense current passing through a conductor. The antenna can be configured to sense electrical potential of the conductor by sensing an electric field generated by the conductor. The antenna can sense the electrical potential independent of whether current is present in the conductor. The monitoring system can further comprise a temperature sensor configured to sense a temperature of the conductor. A sensing module can include a housing supporting the current transformer, the antenna, and the temperature sensor for monitoring an electrical power circuit.

The present disclosure relates to a device for testing insulation properties of a transformer, comprising: a low-voltage winding part and a high-voltage winding part that are arranged concentrically with each other; an iron core for testing combined with the low-voltage winding part and the high-voltage winding part and adjustable in height according to the height of low-voltage winding part and the high-voltage winding part; a low-voltage terminal part connected to both ends of the winding of the low-voltage winding part; a high-voltage terminal part connected to both ends of the winding of the high-voltage winding part.

The present disclosure provides a system and a method for measuring hot-spot temperature of a transformer, wherein the measurement system comprises a processor, an oscilloscope and a plurality of ultrasonic sensors, wherein the ultrasonic sensors are oppositely arranged on an outer wall of a transformer oil tank and electrically connected with the oscilloscope, and the oscilloscope is electrically connected with the processor; the ultrasonic sensors receive signals transmitted by the oppositely arranged ultrasonic sensors and transmit them to the oscilloscope. The method, by applying an ultrasonic wave to measure the hot-spot temperature of a transformer in real time, solves the problems that methods in the prior art are susceptible to the external environment, have short service life and cannot correctly measure the internal temperature of the transformer.

The present disclosure provides a system and a method for measuring hot-spot temperature of a transformer, wherein the measurement system comprises a processor, an oscilloscope and a plurality of ultrasonic sensors, wherein the ultrasonic sensors are oppositely arranged on an outer wall of a transformer oil tank and electrically connected with the oscilloscope, and the oscilloscope is electrically connected with the processor; the ultrasonic sensors receive signals transmitted by the oppositely arranged ultrasonic sensors and transmit them to the oscilloscope. The method, by applying an ultrasonic wave to measure the hot-spot temperature of a transformer in real time, solves the problems that methods in the prior art are susceptible to the external environment, have short service life and cannot correctly measure the internal temperature of the transformer.

A transformer fault diagnosis method and system using induced ordered weighted evidence reasoning is provided. The method includes the following steps. A typical data sample of transformer sweep frequency response analysis is loaded and a diagnostic label is set as an identification framework. Test data of a device to be diagnosed is loaded. Basic probability assignment is calculated and a reliability decision matrix is constructed. An induced ordered weighted averaging operator and its induction vector are calculated according to a sample source of the data. An index weight vector is calculated. All evidence is fused by the induced ordered weighted evidence theory and reliability of comprehensive evaluation is calculated, so as to determine a diagnosis result. The disclosure realizes fault identification, fault type distinction and fault position of power equipment by interpreting detection waveforms.

A transformer fault diagnosis method and system using induced ordered weighted evidence reasoning is provided. The method includes the following steps. A typical data sample of transformer sweep frequency response analysis is loaded and a diagnostic label is set as an identification framework. Test data of a device to be diagnosed is loaded. Basic probability assignment is calculated and a reliability decision matrix is constructed. An induced ordered weighted averaging operator and its induction vector are calculated according to a sample source of the data. An index weight vector is calculated. All evidence is fused by the induced ordered weighted evidence theory and reliability of comprehensive evaluation is calculated, so as to determine a diagnosis result. The disclosure realizes fault identification, fault type distinction and fault position of power equipment by interpreting detection waveforms.