Monica Tiboni

Machine condition monitoring is used in a variety of industries as a very efficient strategy for equipment maintenance. This paper presents a study on monitoring a pneumatic system using a feed-forward backpropagation neural network as a classifier and compares the results obtained with different sensor signals and associated extracted features as input for classification. The vibrations of the body of a pneumatic cylinder are acquired using both common industrial sensors and low-cost sensors integrated into an Arduino board. Pressure sensors for both chambers and a position sensor are also used. Power spectral density (PSD) is used to extract features from the acceleration signals, as well as statistical indices. Statistical indices are considered for pressure and position sensors. The results, which are based on experimental data obtained on a test bench, show that a feed-forward neural network makes it possible to identify the operating states with a good degree of reliability. Even with low-cost instrumentation, it is possible to realize reliable condition monitoring based on vibrations. This last result is particularly important as it can help to further increase the uptake of this maintenance approach in the industrial environment.

Electric transport vehicles offer sustainable transportation solutions with benefits, such as reduced emissions, noise, and operating costs. This paper draws an overview of the available technical solutions to actuate transport vehicles with electric drives, as depicted by patent literature. A dataset of 1784 patents was created; the documents were selected through a systematic approach, and the patents were then classified according to a number of user-defined categories. The dataset was analyzed by applying two different methods: (i) a quantitative analysis (literature overview), enabling glance evaluations about the defined categories, and (ii) a qualitative analysis (detailed analysis), which focuses on the detection of interesting design features or innovative solutions. The results of this work not only provide an alternative and complementary overview to the analysis of solutions that may emerge from a scientific literature review, but can also offer support in strategic planning to companies wishing to protect their innovations and remain competitive in the evolving market of transport vehicles.

In recent decades, extensive attention has been paid to the study and development of robotic devices specifically designed for hand rehabilitation. Accordingly, a many concepts concerning rigid, soft, and hybrid types have emerged in the literature, with significant ongoing activity being directed towards the development of new solutions. In this context, the paper focuses on the technical features of devices conceived for the robotic rehabilitation of the hand with reference to the three kinds of exoskeleton architecture and the clinical requirements demanded by the target impairment of the end-user. The work proposes a roadmap (i) for both the design and selection of exoskeletons for hand rehabilitation, (ii) to discriminate among the peculiarities of soft, rigid, and hybrid devices, and (iii) with an impairment-oriented rationale. The clinical requirements expected for an exoskeleton are identified by applying a PICO-inspired approach focused on the impairment analysis; the technical features are extracted from a proposed design process for exoskeletons combined with a narrative literature review. A cross-analysis between device families and features is presented to provide a supporting tool for both the design and selection of exoskeletons according to an impairment-oriented rationale.

Soft-robotics for biomedical applications, such as rehabilitation robots, is a field of intense research activity. Different actuation solutions have been proposed in the last decades, involving study and development of soft actuators of different types and materials. The purpose of the paper is to present procedures for an optimized design, and for easy and low cost production and characterization of monolithic PneuNets soft-actuators. An innovative design approach has been developed. The parameterization of the geometry, combined with FEM simulations is the basis for an optimized design of the actuator, as a function of the obtained bending and of the generated forces. Simple and cheap characterization setup and procedures have been identified for the actuator characterization and for simulation results validation. An easy and low-cost fabrication method based on lost wax core obtained through a silicone based mold has been developed for a monolithic PneuNets soft-actuator. The proposed solution performs well in bending, without the need for a strain limiting layer. Experimental results validated simulations, confirming the feasibility of adopting an optimized simulation-based design approach.