Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

14100results about How to "Increased sensitivity" patented technology

Low current neutral grounding system fault route selecting method by wavelet package decompose and correlation analysis

InactiveCN101162838ARealize correct line selectionStrong anti-arc grounding abilityEmergency protective circuit arrangementsFault locationElectric power systemDecomposition
The present invention relates to a small current grounding system fault line selecting method by wavelet package decomposition and relevant analysis, belonging to the power system relay protection technical field. The method comprises: starting the fault line selecting device and recording wave to acquire transient zero-order current on each of the feeder lines when bus zero-order voltage transient value exceeds limit; calculating energy on each of frequency bands of the transient zero-order current after wavelet package decomposition, summing the energy of transient zero-order current on all the lines according to frequency bands and selecting the frequency bands with the maximum and secondary value of energy and values as the characteristic frequency bands, applying relevant analysis method to line transient zero-order current on the selected characteristic frequency bands in order; and finally determining fault point integrating the relevant analysis results of two frequency bands. The method uses wavelet package decomposition and relevant analysis, thereby effectively using information (amplitude and phase) contained in fault transient process and reflecting differences between fault line and non-fault line to maximum degree. Principle analysis and simulations demonstrate that the method has precise and reliable line selection.
Owner:KUNMING UNIV OF SCI & TECH

A rolling bearing fault identification method under variable working conditions based on ATT-CNN

The invention discloses a rolling bearing fault identification method under variable working conditions based on ATT-CNN, and relates to a rolling bearing fault identification technology. The problemthat the generalization ability of an existing rolling bearing fault recognition method under variable working conditions is limited to a certain extent for a complex classification problem is solved.The method comprises the following steps: firstly, mapping vibration data to a nonlinear space domain through a convolutional neural network (CNN), and adaptively extracting rolling bearing fault characteristics under variable working conditions by utilizing the characteristic that the CNN has invariance on micro displacement, scaling and other distortion forms of an input signal; Secondly, an attention mechanism (ATT) thought is put forward to be fused into a CNN structure, and the sensitivity of bearing vibration characteristics under variable working conditions is further improved; And meanwhile, more abundant and diverse training samples are obtained through a data enhancement method, so that the network can be learned more fully, and the robustness is improved. The proposed fault diagnosis model based on the attention mechanism CNN (ATT-CNN) can realize multi-state recognition and classification of the rolling bearing under variable working conditions, and compared with other methods, higher accuracy can be obtained.
Owner:HARBIN UNIV OF SCI & TECH

Method for thermal deformation error compensation of digital control gear hobbing machine

The invention discloses a method for thermal deformation error compensation of a digital control gear hobbing machine, which comprises the following steps of: 1, adopting temperature and displacement sensors to detect variable values of a temperature and a thermal deformation displacement on line when the digital control gear hobbing machine is in the course of working; 2, using a fuzzy clustering analytic method to calculate linearly dependent coefficients of variables of the temperature and the displacement, performing classification and optimization on the variable of the temperature, and determining the displacement variable Xi for model building and optimized p temperature independent variables T1, T2, T3, ..., and Tp; 3, adopting a multiple linear regression-least square method to establish a mathematic model of thermal errors and temperature variables; and 4, realizing online real-time compensation of thermal deformation errors of the digital control gear hobbing machine by using a zero programming system. The method solves thermal deformation error problems of a processing gear of the digital control gear hobbing machine, and by performing the online real-time error compensation on the digital control gear hobbing machine, the method improves the gear processing quality, the accuracy and the efficiency, reduces the rejection rate, saves the cost and shortens the processing cycle.
Owner:CHONGQING MACHINE TOOL GROUP +1
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products