This chapter describes different methods and devices that can be used in optical scanning systems (OSS), especially applied to structural health and monitoring (SHM) in order to reduce the interference and losing of resolution in the measurements of the displacements and coordinates calculated by the OSS of a specific structure to be monitored. The principal parts of the OSS are a photo-detector, non-rotating emitter source of light, a DC electrical motor, lens, and mirror. All the measurements and experiments have been realized in a controlled environmental; the optical noise was simulated with a similar intensity than the intensity of the reference signal of the emitter source. Applying analogue filters has disadvantages because part of signal with important information for the performance of the system is removed, but particularly the components will often be too costly. However, there are digital filters and techniques of computational statistics that can solve these problems.
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Existing research in 3D & 2D machine vision technologies, medical scanning, and optoelectronic sensors represent a challenge, particularly in industrial applications of structural health monitoring (SHM) due to the environmental conditions. SHM methodology has received considerable attention in the technical literature, where there has been a concerted effort to develop a firm mathematical and physical foundation for this technology (Sohn, Hoon, Czarnecki, Jerry & Farrar, 2000). Optical scanning systems (OSS) allow monitoring and extracting patterns of structures. These systems consist principally of a set of elements as an optoelectronic sensor, lens, mirror and non-rotating incoherent light emitter; however, these systems and structures to be monitored are subject to the environmental conditions that can affect the measured signals. The basic premise of the OSS is to characterize the normal conditions of a structure, however, in occasional cases the system and structure are exposed to excessive bright sunlight that might lead to cause problems with measured data, because the optoelectronic sensor and incoherent light are in the same spectral ranges of environmental conditions like bright sunlight.
The principal environmental condition factor is the bright sunlight that affects the optical system due to the system could detect two or more patterns at the same time. One pattern belongs to the reference source of a light mounted on the structure and the second pattern is caused by other optical radiations (ultraviolet, visible light, infrared). In order to ensure accuracy and precision of the measurements, it is very important to filter the undesired signals and noise the best it could be. Likewise, the system should also include some filters to distinguish the noise of the reference source. These filters can be optical filters, digital and analog filters. Machine learning technics and statistical pattern recognition methodologies could also be applied to establish difference with a specific pattern from a structure to being monitored. Statistical pattern recognition methodologies have gained considerable attention for SHM applications to detect changes in a structure (Gul & Necati Catbas, 2009).
The bright of sunlight provoke an interference with the wavelength of the emitter source and the phenomena as reflection, diffraction, absorption, and refraction (Fischer, 2008). The signal generated by the optoelectronic sensor inside of Scanning Aperture (SA) is similar in shape to the Gaussian curve, when the SA system is exposed to the sunlight, the Gaussian curve changes dramatically affecting the signal energy center, which is the reference to measure the position of the incoherent light source mounted on the structure. If signal energy center of incoherent light is changing by environmental conditions factors, the coordinates measured using the SA system will also change, in other words the signal energy center is the reference to calculate the spatial coordinates, in this way it is detected a light emitter mounted on the infrastructure being monitored (Flores-Fuentes et al., 2016). In preliminary experimentations, it has been achieved satisfactory results with this method. It is possible to increase the resolution by decreasing the rate of scanning, and however, this creates sources of error that can be minimized with an appropriate method for the measurement (Sergiyenko, Tyrsa, Hernandez, Starostenko, & Rivas, 2009). Despite good results in the laboratory, when the experiments were carried out in the exterior, the measurements were affected by environmental noise such as bright of sunlight, dust and high temperatures. The present chapter will provide a general overview of the methods and devices currently used in optical scanning system to minimize the effects of environmental conditions caused primarily by excessive exposure to the bright sunlight. Furthermore, it will be shown the results of a method to discriminate the classes generated by reference source and the environmental noise by using computational statistics and digital filters. These methods have been proved in optical scanning system with satisfactory results.