The appearance of overlapping in the results derived by continuous wavelet transform (CWT) smears the spectral features and makes the results difficult to interpret. This will significantly affect the accuracy of analysis of anomalous signals. Aiming at minimizing the undesired effect of overlapping, a new soft-thresholding method in terms of exponential functions is proposed. Using the proposed soft-threshold and combining with Donoho’s approach for reducing the structures induced by noise, a strategy for purifying the results derived by the CWT is designed. A series of simulated and practical experiments show that, after adopting the proposed strategy, the results of CWT are further purified and thereby the spectral features of the inspected signal become more explicit and much more easily identified.

1.
Tse
P.
, and
Yang
W.X.
,
2002
, “
The practical use of wavelet transforms and their limitations in machine fault diagnosis
,” International Symposium on Machine Condition Monitoring and Diagnosis, Tokyo, Japan, pp.
9
16
.
2.
Donoho
D. L.
,
1995
, “
De-noising by soft-thresholding
,”
IEEE Trans. Inf. Theory
,
41
(
3
), pp.
613
627
.
3.
Newland
D. E.
,
1999
, “
Ridge and phase identification in the frequency analysis of transient signals by harmonic wavelets
,”
Trans. ASME, J. Vib. Acoust.
,
121
, pp.
149
155
.
4.
Lang
M.
,
Guo
H.
,
Odegard
J. E.
,
Burrus
C. S.
, and
Wells
R.
,
1996
, “
Noise reduction using an undecimated discrete wavelet transform
,”
IEEE Signal Process. Lett.
,
3
(
1
), pp.
10
12
.
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