Optimal sensor placement is one of the important issues in monitoring the condition of structures, which has a major influence on monitoring system performance and cost. Due to this, it is still an open problem to find a compromise between these two parameters. In this study, the problem of optimal sensor placement was investigated for a composite plate with simulated internal damage. To solve this problem, different sensor placement methods with different constraint variants were applied. The advantage of the proposed approach is that information for sensor placement was used only from the structure’s healthy state. The results of the calculations according to sensor placement methods were subsets of possible sensor network candidates, which were evaluated using the aggregation of different metrics. The evaluation of selected sensor networks was performed and validated using machine learning techniques and visualized appropriately. Using the proposed approach, it was possible to precisely detect damage based on a limited number of strain sensors and mode shapes taken into consideration, which leads to efficient structural health monitoring with resource savings both in costs and computational time and complexity.

This article presents a methodology for building an AGV (automated guided vehicle) power supply system simulation model with a polymer electrolyte membrane fuel cell stack (PEMFC). The model focuses on selecting the correct parameters for the hybrid energy buffering system to ensure proper operating parameters of the vehicle, i.e., minimizing vehicle downtime. The AGV uses 2 × 1.18 kW electric motors and is a development version of a battery-powered vehicle in which the battery has been replaced with a hybrid power system using a 300 W PEMFC. The research and development of the new power system were initiated by the AGV manufacturer. The model-based design (MBD) methodology is used in the design and construction of a complete simulation model for the system, which consists of the fuel cell system, energy processing, a storage system, and an energy demand models. The energy demand model has been developed based on measurements from the existing AGV, and the remaining parts of the model are based on simulation models tuned to the characteristics obtained for the individual subsystems or from commonly available data. A parametric model is created with the possibility for development and determination by simulation of either the final system or from the parameters of the individual models’ elements (components of the designed system). The presented methodology can be used to develop alternative versions of the system, in particular the selection of the correct size of supercapacitors and batteries which depend on the energy demand profile and the development of the DC/DC converter and controllers. Additionally, the varying topology of the whole system was also analyzed. Minimization of downtime has been presented as one of many possible uses of the presented model.

The robotization of the non-destructive inspection of aircraft is essential for improving the accuracy and duration of performed inspections, being an integral part of inspection and data management systems within the currently developed NDT 4.0 concept. In this paper, the authors presented the design and testing of a universal mobile platform with interchangeable sensing systems for the non-destructive inspection of aircraft structures with various angles of inclination. As a result of the performed studies, a low-cost approach of automation of existing measurement devices used for inspection was proposed. The constructed prototype of the mobile platform was equipped with eddy current testing probe and successfully passed both laboratory and environmental tests, demonstrating its performance in various conditions. The presented approach confirms the effectiveness of the automation of the inspection process using climbing robots and defining the directions of possible development of automation in non-destructive testing in aviation.

This work describes the implementation of an eddy current sensor for the non-destructive testing of damage of carbon fiber-reinforced polymer (CFRP) composite materials. The designed sensor has a single pot-core coil, straightforward design, and compact size. In addition, its simplistic structure allows for the development of an analytical model, efficient computer simulations, and rapid identification of optimal testing parameters. CFRP composite specimens with flat bottom holes (FBH) and barely visible impact-induced damage (BVID) were investigated, similarly to the damage observed in the on-life stages of an aircraft exploitation. Inspection results with high sensitivity to detection of damage of both types were presented and compared with the results of the ultrasonic testing. Greater than 3 mm FBH damage, regardless of the hole depths and BVID which was result of 15 J impact energy were successfully detected by proposed pot-core coil. Detailed investigations of the damage attributed to subsurface damage, observable by the eddy current sensor, but not observable for the ultrasonic technique, were evaluated. For the considered BVID about 20% of the change in the resistance value can be atrributed to the subsurface defects. This part of the analysis was supported, among others, by computational tomography scans. The results reported in this study confirm that the proposed sensor can be used individually or as a complementary technique for ultrasonic testing in the detection of CFRP composite damage, especially for subsurface damage, which is often not detectable by ultrasonic techniques.