Detection of internal defects of concrete structures based on statistical evaluation of healthy part of concrete by the noncontact acoustic inspection method

Abstract

A noncontact acoustic inspection method was developed to perform measurements from a long distance (usually about 5 to 7 m but even over 30 m) and detect internal defects (up to 10 cm in depth) of concrete structures using a long-range acoustic device and a laser Doppler vibrometer. An algorithm was also proposed to detect internal defects of concrete by combining two acoustic features, the vibrational energy ratio and spectral entropy obtained by our measurement. However, in actual concrete structures, it is difficult to distinguish a boundary between a healthy part and a defective part owing to influences such as the shape of internal defects, age-induced deterioration, and the surface condition of concrete. Therefore, we propose a method to statistically evaluate the distribution of the healthy part of concrete and extract the healthy part to identify the defective part. By this proposed method, the actual concrete floor slab bridge was measured from 33 m away and some internal defects were detected and visualized. Furthermore, a result for a railroad tunnel was compared with the Schmidt hammer rebound value and elastic wave velocity to verify the validity of the proposed method.

Detection of Internal Defects in Concrete and Evaluation of a Healthy Part of Concrete by Noncontact Acoustic Inspection Using Normalized Spectral Entropy and Normalized SSE

“…Taking advantage of this fact, measuring points in a healthy part can be found by statistical methods. Using the healthy part extraction algorithm [ 11 ], a healthy part of concrete can be identified as shown in Figure 6 . Since it is not necessary to divide the three areas by a straight line in this method, it can be effectively applied to a real concrete structure.…”

“…On the other hand, if the return light of the SLDV cannot be sufficiently obtained depending on the surface condition, an abnormal measurement point is observed and it is a problem at the time of measurement. However, since the vibration velocity spectrum measured in that case can be regarded as white noise, the defect detection algorithm [ 10 ] and the healthy part extraction algorithm [ 11 ] using the vibrational energy ratio [ 9 ] and the spectral entropy were devised. Further, since a scanning laser Doppler vibrometer (SLDV) for measuring the target surface two-dimensionally has high sensitivity, there is the issue that it is affected by strong reflected sound waves and causes a resonance phenomenon in the internal mechanism such as a Galvano mirror of a laser head.…”

Research on improvement of defect detection accuracy by resonance judgment for noncontact acoustic inspection method by acoustic irradiation-induced vibration

“…In addition, since the temperature distribution is measured using a heater, it is not suitable for work in high places. In our previous studies, defect detection algorithms, 12,13) vibration energy ratio, 14) spectral entropy, 15,16) evaluation of healthy parts 17) have been proposed as methods for evaluating inspection results. In addition, sound waves have also been studied in order to improve the efficiency of inspection and the signal-to-noise ratio.…”

A fundamental study for long-distance noncontact shallow underground exploration technology by acoustic irradiation-induced vibration

“…12,13,14) First, it was clarified that the detected phenomena are based on the flexural resonance. 15,16) Then, a defect detection algorithm 17,18) using the vibrational energy ratio (VER) 19) and the spectral entropy was constructed and the method for evaluating a healthy part of concrete 20) was proposed. In addition, a tone burst wave was devised to realize measurement with a high S/N ratio.…”