Reliable prognostics have become indispensable to provide predictive service solutions. In fact, by assessing the residual useful life of a product, a condition-based maintenance strategy can be adopted. Consequently, the appropriate service activity can be assigned and scheduled only if and when required. Hence cost and time related to unnecessary preventive service tasks is saved. Prognostics algorithms are usually affected by different types of uncertainties stemming, for example, by randomness and lack of knowledge in the degradation behaviour, the inherent failure mechanism and the usage of the product by the customer. Such uncertainties can have potentially large effects on the determination of the residual useful life and, consequently, on the planning and scheduling of the subsequent service activity. This paper is focused on the customer usage as a main source of uncertainty. A statistical and a fuzzy approach are presented. The application case is given by the determination of the electrical overhaul for a generator circuit breaker (GCB). Nevertheless, the suggested approaches can be generally used for any type of products.

Power supplies for LHC experiments require DC-DC power converters able to work in very hostile environment. The APOLLO collaboration, funded by the Italian Istituto Nazionale di Fisica Nucleare (INFN), aims to study dedicated topologies and to design, build and test demonstrators, developing the needed technology for the industrialization phase.
Besides the presence of radiation and magnetic fields, thermal specifications are particularly stringent in the working environment. In order to have the wanted features in terms of reliability and availability during the experimental activity, these power electronics circuits must be cooled by specifically designed water heat sinks, and an accurate thermal design is mandatory in order to guarantee safe and reliable operation.
In this paper thermal characterization is used for tuning a coupled thermo-fluid-dynamic 3D numerical model, for both the water heat sink and the whole system. Based on this model an optimized water heat sink was designed and fabricated. Thermal characterization of the power converter demonstrator in different operating conditions shows good agreement with simulation results.

In recent years renewable sources of power are being increasingly exploited to address the challenges of climate change and fossil fuel depletion. Wind power and solar power are two of the few renewable energy sources capable of rapidly satisfying a reasonable proportion of future energy requirements.
Acceptance testing of medium-sized and large photovoltaic (PV) plants requires functional tests executed to verify the proper working and energy efficiency. A final certificate ensures the compliance with the technical requirements, as required by Italian Conto Energia program. Tests must be conducted according to several technical norms. The paper describes a measurement system, implemented for testing medium-sized PV plants in full compliance with the international standards; moreover, the measurement system can be configured to measure additional parameters, because it is software based. The measurement system has been adopted for the performance evaluation of a 842 kWp PV plant, with satisfactory results.

Paper deals with accuracy and stability evaluation of PPS signals generated by timing GPS receivers (uBlox LEA-6T and Trimble ICM SMT) using UTC(TP) reference time.

The paper presents the application of selected statistical methods to process the training and testing data sets and prepare them for the artificial intelligence-based method used in the diagnostics of analog systems. The size of the set (especially the number of processed attributes – stamps) determines the efficiency of the selected algorithm and minimizes the amount of information to be measured in the actual system. The preprocessing operations include elimination of constant or quasi-stationary stamps and selection of their most important set, allowing for the efficient fault detection or parameter identification. The paper presents two methods from the econometrics domain adjusted to the technical diagnostics applications. Their implementation is tested on the electronic analog filter. Also, efficiency of the artificial neural network (ANN) working with the original and preprocessed data is verified.