Application of Noise Cancelling and Damage Detection Algorithms in NDE of Concrete Bridge Decks Using Impact Signals

Journal Article · Tue Sep 13 04:00:00 EDT 2011 · Journal of Nondestructive Evaluation

DOI:https://doi.org/10.1007/s10921-011-0114-8· OSTI ID:1029084

Zhang, Gang; Harichandran, Ronald S; Ramuhalli, Pradeep

Delamination is a commonly observed distress in concrete bridge decks. Among all the delamination detection methods, acoustic methods have the advantages of being fast and inexpensive. In traditional acoustic inspection methods, the inspector drags a chain along or hammers on the bridge deck and detects delamination from the 'hollowness' of the sounds. The signals are often contaminated by ambient traffic noise and the detection of delamination is highly subjective. This paper describes the performance of an impact-bases acoustic NDE method where the traffic noise was filtered by employing a noise cancelling algorithm and where subjectivity was eliminated by introducing feature extraction and pattern recognition algorithms. Different algorithms were compared and the best one was selected in each category. The comparison showed that the modified independent component analysis (ICA) algorithm was most effective in cancelling the traffic noise and features consisting of mel-frequency cepstral coefficients (MFCCs) had the best performance in terms of repeatability and separabillty. The condition of the bridge deck was then detected by a radial basis function (RBF) neural network. The performance of the system was evaluated using both experimental and field data. The results show that the selected algorithms increase the noise robustness of acoustic methods and perform satisfactorily if the training data is representative.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1029084
• Report Number(s): PNNL-SA-77730
• Journal Information: Journal of Nondestructive Evaluation, Journal Name: Journal of Nondestructive Evaluation Journal Issue: 4 Vol. 30; ISSN 0195-9298; ISSN JNOED5
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
ACOUSTICS
ALGORITHMS
Acousitc NDE
CHAINS
CONCRETES
Concrete bridge decks
DETECTION
Delamination
Mel-frequency cepstral coefficients
NEURAL NETWORKS
Neural Network
Noise cancellation
PATTERN RECOGNITION
PERFORMANCE
TRAINING