Abstract
This paper described a development of the fault gear identification system using the vibration signal with discrete wavelet transform and fuzzy-logic inference for a gear-set experimental platform. The proposed system consisted of a combination of signal feature extraction using discrete wavelet transform technique and fault identification using fuzzy-logic inference. Traditionally, the technique for fault diagnosis in rotating machinery depends on the experience of the technician. However, the rotating machinery may be operated in a complex and noisy environment. The conventional diagnosis technique has difficulty detecting the fault features, such as in a noisy environment. In the present study, a discrete wavelet transform technique using vibration signals in a gear-set experimental platform is studied. The extraction method of feature vector is based on discrete wavelet transform with energy spectrum. Further, the fuzzy-logic inference is proposed to develop the diagnostic rules of the data base in the present fault identification system. The experimental works are performed to evaluate the effect of fault diagnosis in a gear-set platform under various operation conditions. The experimental results indicated the proposed expert system is effective for increasing accuracy in fault gear identification of the gear-set platform.
| Original language | English |
|---|---|
| Pages (from-to) | 3785-3794 |
| Number of pages | 10 |
| Journal | Expert Systems with Applications |
| Volume | 36 |
| Issue number | 2 PART 2 |
| DOIs | |
| Publication status | Published - 2009 Jan 1 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Engineering(all)
- Computer Science Applications
- Artificial Intelligence
Cite this
}
Fault gear identification using vibration signal with discrete wavelet transform technique and fuzzy-logic inference. / Wu, Jian-Da; Hsu, Chuang Chin.
In: Expert Systems with Applications, Vol. 36, No. 2 PART 2, 01.01.2009, p. 3785-3794.Research output: Contribution to journal › Article
TY - JOUR
T1 - Fault gear identification using vibration signal with discrete wavelet transform technique and fuzzy-logic inference
AU - Wu, Jian-Da
AU - Hsu, Chuang Chin
PY - 2009/1/1
Y1 - 2009/1/1
N2 - This paper described a development of the fault gear identification system using the vibration signal with discrete wavelet transform and fuzzy-logic inference for a gear-set experimental platform. The proposed system consisted of a combination of signal feature extraction using discrete wavelet transform technique and fault identification using fuzzy-logic inference. Traditionally, the technique for fault diagnosis in rotating machinery depends on the experience of the technician. However, the rotating machinery may be operated in a complex and noisy environment. The conventional diagnosis technique has difficulty detecting the fault features, such as in a noisy environment. In the present study, a discrete wavelet transform technique using vibration signals in a gear-set experimental platform is studied. The extraction method of feature vector is based on discrete wavelet transform with energy spectrum. Further, the fuzzy-logic inference is proposed to develop the diagnostic rules of the data base in the present fault identification system. The experimental works are performed to evaluate the effect of fault diagnosis in a gear-set platform under various operation conditions. The experimental results indicated the proposed expert system is effective for increasing accuracy in fault gear identification of the gear-set platform.
AB - This paper described a development of the fault gear identification system using the vibration signal with discrete wavelet transform and fuzzy-logic inference for a gear-set experimental platform. The proposed system consisted of a combination of signal feature extraction using discrete wavelet transform technique and fault identification using fuzzy-logic inference. Traditionally, the technique for fault diagnosis in rotating machinery depends on the experience of the technician. However, the rotating machinery may be operated in a complex and noisy environment. The conventional diagnosis technique has difficulty detecting the fault features, such as in a noisy environment. In the present study, a discrete wavelet transform technique using vibration signals in a gear-set experimental platform is studied. The extraction method of feature vector is based on discrete wavelet transform with energy spectrum. Further, the fuzzy-logic inference is proposed to develop the diagnostic rules of the data base in the present fault identification system. The experimental works are performed to evaluate the effect of fault diagnosis in a gear-set platform under various operation conditions. The experimental results indicated the proposed expert system is effective for increasing accuracy in fault gear identification of the gear-set platform.
UR - http://www.scopus.com/inward/record.url?scp=56349099610&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=56349099610&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2008.02.026
DO - 10.1016/j.eswa.2008.02.026
M3 - Article
AN - SCOPUS:56349099610
VL - 36
SP - 3785
EP - 3794
JO - Expert Systems with Applications
JF - Expert Systems with Applications
SN - 0957-4174
IS - 2 PART 2
ER -