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Ideal sensors for the future should be economical, efficient, highly intelligent, and capable of obtaining their operation power from the environment. The use of piezoelectric fiber composites coupled with a low power microprocessor and backpropagation type neural networks is proposed for the development of a simple sensor to estimate the characteristics of harmonic forces. Three neural networks were used for the estimation of amplitude, gain and variation of the load in the time domain. The average estimation errors of the neural networks were less than 8% in all of the studied cases.

Self‐powering sensors have been desired for future platform sensor networks to minimize wiring and related problems. The selection of the proper area of piezoelectric patches at various operating conditions is an important challenge since the selection of a large patch area increases the complexity and weight. The small patch area could not provide enough energy to operate the electronics continuously. Many Finite Element Method (FEM) packages are capable of estimating the electricity after the stress or strain distribution is calculated. In this paper, the required energy for smart sensors is briefly discussed and the use of FEM is suggested for selection of the size and best location of the piezoelectric patch. The study indicated that the oscillation frequency affects the mode shape and the generated energy drastically. FEM is very useful to determine the mode shapes and the selection of patch locations with maximum dynamic strain.

The strain monitoring capability of piezoelectric materials was experimentally studied. Patches and fibers were considered for this purpose. A piezoelectric stripe actuator was used to obtain the typical signal of patches. Two designs were considered for the piezoelectric fibers. The first one was a commercial energy harvesting device with long fibers. The ends of the fibers were loose. In contrast, we designed a small piezoelectric strain gage with short fibers. Fibers were attached to wires at two ends with conductive resin. The piezoelectric strip actuator, and commercial energy harvesting device were connected to digital oscilloscope directly. A charge amplifier was used to condition the signals of the small piezoelectric strain gage with short fibers. All the units were attached to a beam and excited at different frequencies to evaluate the characteristics of their signals.