Independent residuals are constructed for each different sensor failure. Residuals are designed so that they respond to an individual failure and not to the others. In general, residuals rk are functions of the squared difference between real (ci) and estimated (?i) sensor outputs:rk=��i=1nmi(ci?c^i)2(2)where mi are weighting coefficients that are determined for each failure based on experience and experimentation. Ideally, if no fault is present, the residual would be zero. In practice, the residual will take non-zero values due to estimation errors, sensor noise, etc. Usually, the residual for a specific sensor will be bounded, and therefore a ��threshold level�� can be defined so that the residual is always below it in absence of failures.

The system has been tested with different sensors and failure types.

The implemented sensor FDI system is able to detect many of these errors.2.2. Differ
Automation of welding processes has been a challenging field of research in robotics, sensor technology, control systems and artificial intelligence because of its severe environmental conditions such as intense heat, fumes and so on [1]. In the field of robotics, industrial robot welding is by far the most popular application worldwide, since various manufacturing industries require welding operations AV-951 in their assembly processes [2]. The most significant application of robot welding can be found in the automobile industry.

In the case of the representative Korean automobile company, Hyundai Motor Company, the most manufacturing processes, except for delicate assembly processes, are automated with automotive assembly lines, and the welding process is almost fully automated.

As a result, the productivity and quality of the products have been improved remarkably. On the contrary, the shipbuilding process is much less automated than the automobile manufacturing process due to its large-scale unstructured production environment. The welding process in shipbuilding is automated just 60%. Thus, the fact is that the study of robotic welding is still required in the field of shipbuilding, taking into consideration its complex and unstructured production environment.

Shipbuilding is achieved by welding numerous steel plates according to a ship blueprint. Since the steel plates are too big and heavy to carry as is, a lug is attached to the plates as a handle, Brefeldin_A as shown in Figure 1. In this study, for robotic welding of the lug to the steel plate, a 3D lug pose detection sensor is proposed based on a structured-light vision system. In fact, a structured-light vision system has been commonly used for robotic welding with high precision and low disturbance [3,4].