The versatility of piezoelectric sensors in measurement techniques and their performance in applications has given rise to an increased interest in their use for structural and manufacturing component monitoring. They enable wireless and sensor network solutions to be developed in order to directly integrate the sensors into machines, fixtures and tools. Piezoelectric sensors increasingly compete with strain-gauges due to their wide operational temperature range, load and strain sensing accuracy, low power consumption and low cost. This research sets out the use of piezoelectric sensors for real-time monitoring of mechanical strength in metallic structures in the ongoing operational control of machinery components. The behaviour of aluminium and steel structures under flexural strength was studied using piezoelectric sensors. Variations in structural behaviour and geometry were measured, and the load and μstrains during operational conditions were quantified in the time domain at a specific frequency. The lead zirconium titanate (PZT) sensors were able to distinguish between material types and thicknesses. Moreover, this work covers frequency selection and optimisation from 20 Hz to 300 kHz. Significant differences in terms of optimal operating frequencies and sensitivity were found in both structures. The influence of the PZT voltage applied was assessed to reduce power consumption without signal loss, and calibration to μstrains and loads was performed.

A piezoelectric energy harvester generator is a device capable of transforming environmental mechanical energy into electrical energy. The piezoelectric electromechanical parameters determine the maximum electrical power which is able to be transferred to an electric load. In this research work, an exhaustive study of the electromechanical parameters related to the piezoelectric material is carried out, modeling them as components of an electrical circuit, in order to analyze their influence on the transmitted power. On the other hand, some electrical loads are simulated to determine different matrix scenarios for a model developed by state-space equations in the Laplace transform domain. The results obtained have allowed to know how the piezoelectric material properties and mechanical characteristics influence the electrical power output of the energy harvester generator and the energy transmission behavior for different electric loads. The conclusions show how the different electromechanical parameters are related to each other, and how their combination transforms the mechanical environmental energy into the required electrical energy. The novelty of this research is the presentation of a model capable of obtaining the optimized working point of the harvester, taking into account not only the electric loads and current demands but also the piezoelectric material parameters.

Piezoelectric harvesters use the actuation potential of the piezoelectric material to transform mechanical and vibrational energies into electrical power, scavenging energy from their environment. Few research has been focused on the development and understanding of the piezoelectric harvesters from the material themselves and the real piezoelectric and mechanical properties of the harvester. In the present work, the authors propose a behavior real model based on the experimentally measured electromechanical parameters of a homemade PZT bimorph harvester with the aim to predict its V_rms output. To adjust the harvester behavior, an iterative customized algorithm has been developed in order to adapt the electromechanical coupling coefficient, finding the relationship between the harvester actuator and generator behavior. It has been demonstrated that the harvester adapts its elongation and its piezoelectric coefficients combining the effect of the applied mechanical strain and the electrical behavior as a more realistic behavior due to the electromechanical nature of the material. The complex rms voltage output of the homemade bimorph harvester in the frequency domain has been successfully reproduced by the proposed model. The Behavior Real Model, BRM, developed could become a powerful tool for the design and manufacturing of a piezoelectric harvester based on its customized dimensions, configuration, and the piezoelectric properties of the smart materials.