Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary

CATEGORY: FAULT DIAGNOSIS
Quantitative fault analysis of roller bearings based on a novel matching pursuit method with a new step-impulse dictionary

Type	Journal Article
Author	Lingli Cui
Author	Na Wu
URL	http://www.sciencedirect.com/science/article/pii/S0888327015002873
Volume	68–69
Pages	34-43
Publication	Mechanical Systems and Signal Processing
Date	February 2016
Abstract	Offers an innovative matching pursuit method based on a novel step-impulse dictionary to measure the size of a bearing׳s spall-like fault. Based on the double-impact theory and the rolling bearing fault mechanism, authors explain a theoretical model for the bearing fault with different spall-like fault sizes is developed and analyzed, and the double-impact characteristic of the bearing faults. The first action that causes a bearing fault is due to the entry of the roller element into the spall-like fault which can be described as a step-like response. The second action is the exit of the roller element from the spall-like fault, which can be described as an impulse-like response. Based on the quantitative relationship between the time interval of the seemingly double-impact actions and the fault size, a novel matching pursuit method is proposed based on a new step-impulse dictionary. In addition, the quantitative matching pursuit algorithm is proposed for bearing fault diagnosis based on the new dictionary model. Finally, an atomic selection mechanism is proposed to improve the measurement accuracy of bearing fault size. Simulation results suggest that the new matching pursuit method based on the new step-impulse dictionary can be reliably used to measure the sizes of bearing spall-like faults. The applications of this method to the fault signals of bearing outer-races measured at different speeds show that the proposed method can effectively measure a bearing׳s spall-like fault size.

Multi-scale morphology analysis of acoustic emission signal and quantitative diagnosis for bearing fault

CATEGORY: FAULT DIAGNOSIS
Multi-scale morphology analysis of acoustic emission signal and quantitative diagnosis for bearing fault

Type	Journal Article
Author	Wen-Jing Wang
Author	Ling-Li Cui
URL	http://link.springer.com/article/10.1007/s10409-015-0529-z
Volume	32
Issue	2
Pages	265-272
Publication	Acta Mechanica Sinica
Date	2016/04/01
Abstract	Monitoring potential bearing faults in operation is critical to safe operation of high speed trains. A major challenge is how to differentiate relevant signals to operational conditions of bearings from noises emitted from the surrounding environment. Authors describe a procedure for analyzing acoustic emission signals collected from rolling bearings for diagnosis of bearing health conditions by examining their morphological pattern spectrum (MPS) through a multi-scale morphology analysis procedure. Results reveal that acoustic emission signals resulted from a given type of bearing faults share rather similar MPS curves. Further examinations in terms of sample entropy and Lempel-Ziv complexity of MPS curves suggest that these two parameters can be utilized to determine damage modes.

A Review on Fault Diagnosis of Gear-Box by Using Vibration Analysis Method

CATEGORY: FAULT DIAGNOSIS
A Review on Fault Diagnosis of Gear-Box by Using Vibration Analysis Method

Type	Journal Article
Author	Mr Sagar B. Ghodake
Author	A. K. Mishra
URL	Free Full Text Source:  http://www.academia.edu/download/41760111/IIJME-2016-01-20-11.pdf
Volume	4
Issue	1
Publication	IPASJ International Journal of Mechanical Engineering
Date	January 2016
Abstract	Gearboxes are important part of mechanical transmission systems, and they are used to transmit power, torque etc. between shafts of machineries. Generally gearbox work 24 hours a day in the production system so that any failures in the gearboxes may introduce unwanted downtime, expensive repair cost, and even danger of human casualties. So that it is very important to detect and diagnose faults in gearbox working at initial stage for its effective working. There are various methods to detect faults in gearbox. Among them vibration measurement is an effective way to detect any abnormality/fault produced in a gearbox as every machine has its own specific vibration signature as faults occurs in any part of gearbox/machinery its vibration signature changes accordingly. By measuring and analysing the machine’s vibration, it is possible to govern both the nature and severity of the defect, and hence predict the machine’s failure. The vibration signal of a gearbox conveys the signature of the fault in the gears, and early fault detection of the gearbox is possible by examining the vibration signal using different signal processing techniques. This paper gives a brief review on various techniques used for analysing the faults of gearbox based on vibration analysis method with small insight on new approach used for diagnosis of gearbox such as Artificial Neural Network, fuzzy sets and some emerging technology in gear fault analysis.