138 results about "Power transformer windings" patented technology

The invention relates to a failure diagnostic method for the dynamic stable state of power transformers. In the failure diagnostic method, the deformation condition of power transformer windings is analyzed by combining a frequency response process and an impedance process, the power transformers which have the same types and different serial numbers, the same windings with different phases and indexes of the correlation degree of frequency curves of the dynamic stable state are obtained by the frequency response process. The failure diagnostic method comprises the following steps of: analyzing the dynamic stable state of the power transformers according to related coefficients by synthesizing the advantages of the synthesize technology and the impedance process; when exceeding a permissible value, judging the related coefficients by the impedance process; and when numerical values of parameters also exceed the permissible value, determining that the failure of the dynamic stable state of the power transformers occurs.

The invention discloses an intelligent on-line diagnosis and location method of power transformer winding deformation. A winding deformation is called that after the power transformer is lashed by short-circuit or impacted by transportation, characteristics such as distortion and bulging of a local winding can occur under an electrodynamic force or a mechanical force, and buries a huge hidden danger to safe operation of a power network. The common methods of the winding deformation diagnosis are off-line diagnosis, and has the shortcomings of need of transformer shutdown and high requirementsfor professional skills of operators. The invention provides an intelligent on-line diagnosis method of the winding deformation combining information entropy and a support vector machine, the characteristics of current and voltage signals are extracted by using permutation entropy and wavelet entropy, variations of each monitoring index of the power transformer in the aspects of complexity, time-frequency domain and so on are synthesized, and automatic learning of diagnostic logic from fault features is achieved by a machine learning algorithm, the intelligent diagnosis of the winding deformation is achieved, so that the manpower cost is lowered, and the diagnostic efficiency is improved.

The invention discloses a power transformer winding fault diagnosis method based on a GSMallat-NIN-CNN network, and the method comprises the steps: carrying out the measurement of a vibration condition of a transformer winding through a multi-channel sensor, and obtaining multi-source vibration data of a transformer; converting the multi-source vibration data obtained by measurement into grayscaleimages by using GST gray level transformation; decomposing each grayscale image into a high-frequency component sub-image and a low-frequency component sub-image layer by layer by adopting a Mallat algorithm, and performing image fusion on a high-frequency component sub-image and a low-frequency component sub-image; reconstructing the fused grayscale images, and encoding the vibration grayscale images according to the fault state of the transformer winding; establishing a transformer fault diagnosis model based on a GSMallat-NIN-CNN network; randomly initializing network parameters, dividinga training set and a test set, and training and optimizing the network through the training set; and storing the trained network, and testing the network through the test set. According to the method,t noise in a multi-source signal is effectively suppressed, the integrity of feature information is improved, the calculated amount is reduced, and the fault diagnosis accuracy is improved.