Satoru Doi

Study on automated inspection robot and quantitative detection of outer tile wall exfoliation by wavelet analysis

This paper describes an automated inspection robot for detecting tile exfoliation and a new diagnostic method for determining its existence and extent. The robot moves quickly along a vertical wall and stops to detect a tiles inner condition using a hammering sound. Tile separation commonly comprises outer exfoliation where the tile separates from the mortar concrete and inner exfoliation where the space between the substrate and the mortar concrete deteriorates. In order to detect these two exfoliations, we focused attention on wavelet analysis, which enables us to analyze the frequency element of the sound waveform on time phase continuously. By comparing the wavelet volume rate expressing the characteristics of tile deterioration for several scale tiles and striking hammers, the quantitative detection and its scale effects of visually distinguishing the two exfoliation modes was established. The automated robot and the diagnostics method were used to perform a fast and highly accurate inspection of the outer tile wall.

Development of automated inspection robot and diagnosis method for tile wall separation by wavelet analysis

This paper describes the development of an automated inspection robot for detecting tile deterioration and a new diagnostic method for determining its existence and extent. The robot moves quickly along a vertical wall and stops to detect a tile’s inner condition using a hammering sound. Tile separation commonly comprises outer exfoliation where the tile separates from the mortar concrete and inner exfoliation where the space between the substrate and the mortar concrete deteriorates. In order to detect these two modes by a hammering sound, we focused attention on wavelet analysis, which enables us to analyze the frequency element of the sound waveform. By comparing the wavelet volume rate expressing the characteristics of tile deterioration, a method of visually distinguishing the two exfoliation modes was established. The automated robot and the diagnostics method were used to perform a fast and highly accurate inspection of a tile wall.

Nondestructive inspection of voids in concrete by multi-layered scanning method with electromagnetic waves

The tiles that are used to protect the exterior of a building may separate from the concrete substrate and fall off as they age. To prevent accidents, a tiled wall can be inspected using various methods. In this paper, nondestructive inspection (NDI) with microwave electromagnetic waves (EMWs) is used for detecting tile separation, and the chance of detecting separation by this method is discussed. Here, the inspection apparatus is used to detect voids in concrete including voids that simulates tile separation. An antenna attached to the apparatus transmits and receives microwaves to obtain a reflection intensity from the concrete. In addition, the distribution of reflection intensity is obtained using a proposed scanning method, multi-layered scanning. This involves several scans along the concrete surface at different antenna-to-surface distances. Typically, EMWs have to be analyzed with an expensive network analyzer in the time or frequency domain. However, we demonstrate that voids are detected from the obtained distribution of reflected intensity of EMWs measured by a simple device without a network analyzer. The proposed method of NDI with EMWs is cheaper and simpler than conventional inspection methods.

Research on Quantitative Detection of Outer Tile Exfoliation by Wavelet Analysis

This paper describes a detection method of two types of exfoliations for outward tile wall. One of the tile exfoliations is an outer exfoliation separated the tile surface from mortar concrete, the other is an inner exfoliation deteriorated space between the substrate and mortar concrete. In order to research these exfoliations, we focused attention on the wavelet analysis that enable to analyze the frequency element of a waveform on time phase continuously. In part 2 of this study, comprising the conventional detection methods in which the inspection robot was applied and new method used by wavelet analysis, the characteristics of these methods were verified respectively. As a result, it found that the peak rate method detected outer exfoliation, the cross correlation method detected inner exfoliation and that the wavelet method detected this exfoliation instantly. A best effective detection flowchart inspected the tile exfoliations to apply to the inspection robot was proposed.