Order Tracking Filtering Based on Instantaneous Frequency Estimation and Zero-Phase Distortion Digital Filtering

Author(s):  
Shuren Qin ◽  
Yu Guo

A new method for run-up or coast down vibration signal order tracking filtering of rotating machinery based on instantaneous frequency estimation and zero-phase distortion digital filtering is proposed in this paper. By contrast with traditional methods of order tracking filtering, the features of tacholess, no hardware-based tracking filter required and no frequency shift to original sampling data, etc, make it more attractive. The theorems and algorithms of the method are detailed discussed in this paper. The filtering of overlapped data blocks is used to restrain the edge effect, which caused by digital filtering, is also introduced. An actual test example of a motor’s run-up and coast down vibration is introduced to demonstrate the validity of the method.

2005 ◽  
Vol 295-296 ◽  
pp. 747-752
Author(s):  
S.R. Qin ◽  
Y. Guo

A new method for order tracking filtering of rotating machinery based on instantaneous frequency estimation and zero-phase distortion digital filtering is proposed. Compared with the traditional methods for order tracking filtering, the new method has a number of attractive features such as tacholess, no hardware-based tracking filter and no frequency shift to the original sampling data. The theorems and algorithms of the method are discussed. Filtering of overlapped data blocks, used to restrain the edge effect, which is caused by digital filtering, is introduced. An actual test example of run-up and coast down vibration of a motor is presented to demonstrate the validity of the method.


Author(s):  
Igor Djurović

AbstractFrequency modulated (FM) signals sampled below the Nyquist rate or with missing samples (nowadays part of wider compressive sensing (CS) framework) are considered. Recently proposed matching pursuit and greedy techniques are inefficient for signals with several phase parameters since they require a search over multidimensional space. An alternative is proposed here based on the random samples consensus algorithm (RANSAC) applied to the instantaneous frequency (IF) estimates obtained from the time-frequency (TF) representation of recordings (undersampled or signal with missing samples). The O’Shea refinement strategy is employed to refine results. The proposed technique is tested against third- and fifth-order polynomial phase signals (PPS) and also for signals corrupted by noise.


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