Elsevier

Automation in Construction

Volume 18, Issue 7, November 2009, Pages 929-941
Automation in Construction

Bridge inspection robot system with machine vision

https://doi.org/10.1016/j.autcon.2009.04.003Get rights and content

Abstract

A robotic system for inspecting the safety status of bridges is proposed in this paper. Currently, most bridge inspections have been done manually by counting the number of cracks, measuring their lengths and widths and taking pictures of them. Thus the quality and reliability of diagnosis reports on bridges are greatly dependent upon the diligence and education of inspection workers. The robotic inspection system to be proposed consists of three parts: a specially designed car, a robot mechanism and control system for mobility and a machine vision system for automatic detection of cracks. Ultimately, this robot system has been developed for gathering accurate data in order to record the biennial changes of the bridge's safety circumstances as well as check the safety status of bridges. We also demonstrate the effectiveness of the suggested crack detecting and tracing algorithms through experiments on a real bridge crack inspection.

Introduction

Bridge inspection is a critical responsibility. Failure to properly inspect bridges has resulted in abrupt bridge collapses; for instance, the Songsu Bridge collapse in Korea in 1994 and the Minneapolis Bridge collapse in the US in 2007. The number of bridges has gradually increased in Korea resulting in increased need for inspections, as shown in Table 1. Currently; about 12,000 bridges should be inspected every other year for safety tests according to Korean law [1]. Also, the maintenance and repair cost of bridges has rapidly increased every year with an increase of 200 times in the last 10 years since 1995. Thus it is increasingly necessary to find a more efficient and economical method to maintain the bridges through precise diagnosis.

Although robot technologies have evolved in a variety of industrial areas, robot application technologies for the safety diagnosis and maintenance of real bridges have lagged behind. Until recently, bridge inspection and maintenance have been manually conducted by the trained inspection workers working in the outdoors [2], [3]. The inspection workers check the safety status beneath the bridge by counting the number of cracks, measuring the maximum widths and lengths of the crack lines and taking pictures of them. Thus the accuracy and quality of diagnosis report becomes subjective and results differ according to the diligence of the inspection workers. Also, since the bridge inspection is performed outdoors, especially beneath the bridge, there may be the problem concerning the safety of inspection workers. The Fig. 1 shows the inspection workers standing on a temporary scaffolding in order to inspect the safety status of a real bridge [4], [5], [6].

An industrial accident may be caused during the period of the bridge inspection as shown in Fig. 1. Besides cost reduction, improvement of the work environment has become one of the main considerations in the bridge inspection. To help solve these problems, the bridge inspection robot system equipped with machine vision is proposed in this paper. An inspection robot is more useful when it can dispatch sensors or manipulators into inaccessible or hazardous areas, thereby, making the inspection workers safer. As similar applications, an underwater inspection robot system for the bridge piers has already been developed in [7], also, other types of inspection robot have been suggested such as a climbing robot composed of wheel mechanism with vacuum suctions in [8], [9], [10], a pipe inspection robot for magnetic crack detection of iron pipes in [11] and a mobile robot for bridge girder inspection in [12].

For visual inspections, we have developed not only a robotic motion control system but also a machine vision system. During the last decades, machine vision has evolved into various fields embracing a wide range of applications including surveillance, automated inspection and vehicle guidance [13], [14]. The machine vision system is able to extract useful information about a scene from its two-dimensional projections. The machine vision system takes images as inputs and produces other types of outputs, such as crack lengths, crack widths and an outlined sketch of the bridge status. By using the machine vision system, the accuracy of crack assessment is guaranteed and a variety of information for bridge maintenance is provided through the results of bridge inspection. In contrast to most existing crack detection methods in [19], [20], [21] that find and display detected cracks, this paper introduces batch processes including the crack detecting/tracing algorithms and the corresponding crack panorama images conversion into CAD files for a bridge management system. In practice, crack progress speed should be estimated through biennial reports on the bridge inspection, thus the batch processes to be suggested are essentially required for assessing the safety of bridge. In this paper, we aim at raising the consistency of inspection results, improving the exactness and reliability of biennial diagnosis report about the bridge and reducing the industrial accidents. Also, the bridge inspection robot system to be suggested is not fully autonomous, but semi-autonomous type requiring the role of a human as a supervisor or operator. With these research objectives, we suggest a robotic system for detecting and tracing cracks with a machine vision system and a variety of sensors.

This paper is organized as follows: Section 2 describes the total robot mechanism and control system to be proposed; Section 3 suggests the image processing algorithms for detecting and tracing cracks; Section 4 explains an integration method for the total system; Section 5 shows the experimental results; and Section 6 draws the conclusion.

Section snippets

Overview

The total mechanical system for the bridge inspection is composed of a specially designed car and the inspection robot which is mounted on an end-point of a specially designed car as shown in Fig. 2. The specially designed car has the multi-linkage mechanism of seven DOF's (degrees-of-freedom) equipped with the hydraulic actuators system. This multi-linkage mechanism was designed for dispatching the inspection robot system into the lower surface of bridge. Also, the inspection robot mounted on

Machine vision system

The purpose of the machine vision system is to detect the cracks of bridge lower surface automatically from the captured images. As a matter of fact, there are many kinds of damages according to the bridge types, for example, cracks, corrosions, subsidence, fatigue. Among these damages, crack information becomes one of the most important factors in deciding the bridge repairs [18]. The utilized machine vision system is composed of a charged couple device (CCD) camera, a digital video recorder

Total system integration

The multi-linkage system, the inspection robot, and the machine vision system suggested in the previous sections should be integrated into the specially designed car. Also, the server computer as a total manager has to control the whole functions in real time as shown in Fig. 15. It is important for the server computer to be synchronized between the entire motion control system and the machine vision for the real time operation. First, the server computer sends the first command signal to the

Experimental results

For field tests, we have designed a mock-up for the inspection robot as shown in Fig. 17. The total weight of inspection robot including mock-up is about 25 kg.

As a first experiment, the control performance for keeping the constant orientations of machine vision system from the external disturbances is shown in Fig. 18. The camera orientations are recovered fast using the nonlinear PD controller suggested in Fig. 8. As aforementioned, for large orientation errors, large control inputs (fast

Conclusion

A robotic system for bridge inspection has been developed for practical use with both automatic inspection mode and manual inspection (tele-operation) mode; both supervised by a human. In addition, this robotic system has been developed for batch processes to write the bridge safety diagnosis reports from the image capturing using robot motion control to the bridge management system. The proposed bridge inspection system is composed of three main parts; a specially designed car, robot mechanism

Acknowledgements

This work was supported in part by the Bridge Inspection Robot Development Interface Program of the Ministry of Construction and Transportation and in part by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (R01-2008-000-20631), and in part by the Ministry of Knowledge Economy(MKE) and Korea Industrial Technology Foundation (KOTEF) through the Human Resource Training Project for Strategic Technology and in part by the Gyeonggi Regional Research

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