Industrial wireless networks are gradually being adopted in industry, especially due to the low installation costs and low maintenance provided by these systems. For the use in harsh environments, the communication system should provide reliable radio links and low power to allow battery powered devices. In this context, WirelessHART, ISA SP100.11a and WIA-PA protocols were developed to meet these requirements. The standards of these protocols define a minimum number of RF fixed power and selectable only by commissioning. Within this scenario, it is important to adapt RF power modulation, a procedure already used in several communication protocols to minimize the energy consumption of transceivers while maintaining link quality. In this paper, three ways to modulate RF power are analyzed within WirelessHART field devices. A specific approach that works in a decentralized way is developed and the results show it can save 50% of energy in certain cases. The proposal has the extra advantage to be compatible with the standard.

Three different techniques for measuring wear in brake pads are compared: a gravimetric method (electronic balance), a linear measuring touch probe method, and a three-dimensional laser scanning method. Laboratory-scale wear tests were performed on two different types of brake friction materials: a semi-metallic (SM) and a non-asbestos organic (NAO). All three techniques were able to show clear differences in the wear rates of the materials selected for study. It was observed that choosing only a few points of measurement in the thickness determination using a touch probe can lead to significant errors. These errors were higher than those caused by moisture absorption effects when using the gravimetric method. The laser scanning method proved adequate for investigating the wear profiles produced by braking tests. Results from the tests showed that SM material exhibits a higher coefficient of friction and wear rate than the NAO material. An increase of the contact pressure resulted in increased wear rates for both SM and NAO materials. The ratio between volume loss and mass loss also increased when contact pressure was higher indicating that samples had suffered from compressive deformation.

This paper presents the identifiability analysis of a nonlinear model for a batch bioreactor and the estimation of the identifiable parameters within the prediction error framework. The output data of the experiment are the measurements of the methane gas generated by the process, during 37 days, and knowledge of the initial conditions is limited to the initial quantity of chemical oxygen demand. It is shown by the identifiability analysis that only three out of the eight model parameters can be identified with the available measurements and that identification of the remaining parameters would require further knowledge of the initial conditions. A prediction error algorithm is implemented for the estimation of the identifiable parameters. This algorithm is iterative, relies on the gradient of the prediction error, whose calculation is implemented recursively, and consists of a combination of two classic optimization methods: the conjugated gradient method and the Gauss?Newton method.