scholarly journals Best Time Domain Features for Early Detection of Faults in Rotary Machines Using RAT and ANN

2021 ◽  
Author(s):  
Mohammed Al-SAAD ◽  
MOHAMMED Al-Mosallam ◽  
Ahmed Alsahlani
Keyword(s):  
Early Detection ◽  
Time Domain ◽  
Rotating Machinery ◽  
Bearing Failure ◽  
Rotary Machines ◽  
Different Types ◽  
The Common ◽  
Processing Techniques ◽  
Signal Processing Techniques ◽  
Mechanical Defect

Abstract The common mechanical defect of rotating machinery is bearing failure which is considered the most common failure mode in rotating machinery. This kind of failure can lead to large losses as financial during work. Early detection of different faults in rotating machines such as bearing fault, misalignment, and others is considered one of the techniques in which is achieved by further signal processing techniques. Thus, using statistical methods such as reverse arrangement tests (RAT) to obtain the best a feature associated with these different faults is the perfect solution to find the failure which is widespread in the early detection of a fault. This type of feature will be used in Artificial Neural networks (ANN) as input for auto diagnosis. These characteristics are independently associated with different types of fault. Using RAT is considered very important in the process of linking different kinds of failures with the most important features.

scholarly journals Evaluation of Audio Compression Artifacts

10.14311/906 ◽  
2007 ◽  
Vol 47 (1) ◽  
Author(s):  
M. Herrera Martinez
Keyword(s):  
State Of The Art ◽  
Subjective Evaluation ◽  
Audio Coding ◽  
Coding System ◽  
Audio Compression ◽  
Coding Systems ◽  
Wide Range ◽  
Different Types ◽  
Processing Techniques ◽  
Signal Processing Techniques

This paper deals with subjective evaluation of audio-coding systems. From this evaluation, it is found that, depending on the type of signal and the algorithm of the audio-coding system, different types of audible errors arise. These errors are called coding artifacts. Although three kinds of artifacts are perceivable in the auditory domain, the author proposes that in the coding domain there is only one common cause for the appearance of the artifact, inefficient tracking of transient-stochastic signals. For this purpose, state-of-the art audio coding systems use a wide range of signal processing techniques, including application of the wavelet transform, which is described here. 

Rolling Element Bearings Fault Identification in Rotating Machines, Existing Methods of Vibration Signal Processing Techniques and Practical Considerations

2013 ◽  
Vol 430 ◽  
pp. 70-77
Author(s):  
Ninoslav Zuber ◽  
Dragan Cvetkovic
Keyword(s):  
Real Life ◽  
Vibration Signal ◽  
Vibration Monitoring ◽  
Universal Method ◽  
Bearing Failures ◽  
Rolling Element ◽  
Different Types ◽  
Processing Techniques ◽  
Failure Monitoring ◽  
Signal Processing Techniques

This paper addresses the suitability of vibration monitoring and analysis techniques to detect different types of defects in roller element bearings. Processing techniques are demonstrated on signals acquired from the test rig with defective bearings. As a result it is shown that there is no reliable universal method for bearing failure monitoring from its early occurence up to bearings failure. Two real life case studies with different types of bearing failures are presented with practical considerations on methods used for failure identification.

Fault Diagnosis of Rotating Machineries and its Development Trend

2012 ◽  
Vol 591-593 ◽  
pp. 2118-2122
Author(s):  
Hou Yao Zhu ◽  
Chun Liang Zhang ◽  
Bao Jian Yang
Keyword(s):  
Fault Diagnosis ◽  
Research And Development ◽  
Vibration Signal ◽  
Signal Amplitude ◽  
Development Trend ◽  
Rotating Machinery ◽  
Future Trends ◽  
Different Types ◽  
The Common ◽  
Frequency Diagram

This paper introduces the need for the development of fault diagnosis technology. Then the fault diagnosis procedures and principles were analyzed. The common faults of rotating machinery were classified and elaborated in detail, and presented different types of fault vibration signal amplitude-frequency diagram. Then the paper mainly described the fault diagnosis of rotating machinery commonly used method, an overview of domestic and foreign research and development, future trends and prospects of the fault diagnosis technology.

Noise processing techniques for time‐domain EM systems

Geophysics ◽  
1984 ◽  
Vol 49 (7) ◽  
pp. 934-948 ◽  
Author(s):  
James C. Macnae ◽  
Y. Lamontagne ◽  
G. F. West
Keyword(s):  
Time Domain ◽  
Noise Spectrum ◽  
Signal To Noise ◽  
Coherent Noise ◽  
Equal Time ◽  
Transmitter Power ◽  
Digital Integration ◽  
The Time Domain ◽  
Processing Techniques ◽  
Signal Processing Techniques

A variety of signal processing techniques can be used to minimize the effects of noise on linear, wideband, electromagnetic (EM) systems operating in the time‐domain. All systems use repetitive waveforms with polarity reversal in alternate half‐cycles. Exponential averaging or digital integration (stacking) is employed to increase signal‐to‐noise (S/N) ratios by limiting the noise acceptance to narrow frequency bands centered on odd harmonics of the repetition frequency, the width of the acceptance bands being inversely proportional to stacking time. For certain types of nonstationary noise (e.g., occasional transients) or coherent noise (e.g., powerlines) it is possible to increase S/N ratios above those obtained by simple stacking for an equal time by use of techniques such as pruning, tapered stacking or randomized stacking. With some system waveforms and when the noise spectrum is not “white”, use of preemphasis filtering in the transmitter and a corresponding de‐emphasis filter in the receiver may significantly improve the input S/N ratio before stacking. Specific applications of the various techniques are discussed with reference to one particular time‐domain EM system, the UTEM 3 system. By their use, improvements in S/N ratio of as much as 6 to 1 have been regularly achieved without any increase in transmitter power, depending on the nature of the local noise.

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