72 results about "Wavelet entropy" patented technology

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.

Disclosed is an intelligent on-line diagnosis method for winding deformation of power transformer. When a transformer is subjected to short-circuit shock or transportation collision, transformer windings may undergo local twisting, swelling or the like under the action of an electric power or mechanical force, which is called winding deformation and will cause a huge hidden danger to the safe operation of the power network. Commonly used diagnosis methods for winding deformation are all off-line diagnosis methods, which have the disadvantages that transformers need to be shut down and highly skilled operators are required. The present invention provide an intelligent on-line diagnosis method for winding deformation on the basis of combination of information entropy and support vector machine. By carrying out feature extraction of current and voltage signals based on permutation entropy and wavelet entropy, integrating the variation of the monitoring indicators of the power transformers in complexity, time-frequency domain and the like and automatically learning the diagnostic logic from fault features through the machine learning algorithm, intelligent diagnosis of winding deformation is realized, thereby reducing labor costs and improving diagnosis efficiency.