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Global diagnosis for bridges involves identifying the existence of deterioration or damage, as well as its location or vicinity. This research project develops a new technique for global diagnosis—the probabilistic advancing cross-diagnosis (PAC) method—by using a recently developed coherent laser radar system (CLRS). The PAC method takes advantage of CLRS’s efficient deformation-data acquisition by scanning a large area and then processing the data to perform probability-based cross-diagnosis. This method was applied in the structures lab at Wayne State University to a model structure, with the cooperation of FHWA’s Turner-Fairbank Highway Research Center. Several damage scenarios were simulated by increasing and reducing stiffness of the test beam in the model structure. Results show that the proposed PAC method is promising and should be tested in the field.

A new method of global diagnosis for bridge safety monitoring using high-resolution coupled current device (CCD) images is presented. Its advantages are as follows: ( a) no sensors need to be attached to the structure, ( b) no mathematical modeling is required (such as finite element methods), ( c) a probability-based diagnosis approach is used to deal with measurement noise associated with image data, and ( d) CCD cameras are affordable now and are expected to continue to drop in price, which will make this new technique workable for implementation. The new method was applied in the laboratory to a bridge structure model, as presented. Experimental results show that the method is able to identify stiffness losses as small as 3 percent for both their presence and their location. It is concluded that the proposed approach is promising for experimentation in the field.