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513results about "Temperature measurement of moving solids" patented technology

Use of fiber optic sensor techniques for monitoring and diagnostics of large AC generators

A method for monitoring the operating conditions of an electric generator including the entire stator core and all winding components for conditions of mechanical strain and temperature throughout the machine by means of distributive fiber optic sensors based on both Rayleigh back scattering techniques and Brillouin frequency shift fiber optic sensor analysis both of which do not have the gaps and limitations associated with standard fiber Bragg grating fiber optic point sensors, by virtue of the fact that both Rayleigh and Brillouin scans and allow accurate strain and temperature determinations at all points along standard fiber optic cables of considerable length, approximately two kilometers in the case of the Brillouin, which effectively yields many tens of thousands of sensors throughout the entire standard fiber optic cable. Raman distributive temperature sensing also has a limited application. Single mode and polarizing maintaining fibers can both be analyzed and read with any Rayleigh or Brillouin distributive fiber optic sensor laser system allowing great flexibility in sensor spatial resolution, total sensed length, resolution and other factors not possible with conventional fiber Bragg gratings. A sealed fiber collection box located outside the electric generator permits enhanced reliability and reconfiguration into any number of desirable fiber layouts necessary for specific static and dynamic measurements in an optimal manner.
Owner:INNOVATIVE DIAGNOSTIC SYST

Method for early warning and diagnosis of temperature of main bearing of wind turbine generator

The invention relates to the field of new energy wind power generation systems, in particular to a method for early warning and diagnosis of the temperature of a main bearing of a wind turbine generator. The method comprises the following steps that firstly, wind power plant monitoring data is acquired; secondly, parameters related to the temperature of the main bearing of the wind turbine generator are obtained; thirdly, a normal temperature model of the main bearing of the wind turbine generator is established; fourthly, the theoretical value of the real-time normal temperature of the main bearing of the wind turbine generator is calculated, wherein the real-time values of the parameters related to the temperature of the main bearing of the wind turbine generator in the second step are selected from the real-time data collected in the first step, the real-time values of the related parameters are input into a neural network trained in the third step, and the normal temperature valueof the main bearing of the wind turbine generator is generated; fifthly, whether the real-time temperature of the main bearing of the wind turbine generator is normal or not is judged. By means of themethod, faults of the main bearing of the wind turbine generator are effectively judged in advance, an extra sensor does not need to be installed, and the diagnosis precision and the diagnosis time advance are remarkably improved.
Owner:湖南优利泰克自动化系统有限公司 +1
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