This paper presents a multipurpose UAV (unmanned aerial vehicle) for mountain rescue operations. The multi-rotors based flying platform and its embedded avionics are designed to meet environmental requirements for mountainous terrain such as low temperatures, high altitude and strong winds, assuring the capability of carrying different payloads (separately or together) such as: avalanche beacon (ARTVA) with automatic signal recognition and path following algorithms for the rapid location of snowcovered body; camera (visible and thermal) for search and rescue of missing persons on snow and in woods during the day or night; payload deployment to drop emergency kits or specific explosive cartridge for controlled avalanche detachment. The resulting small (less than 5 kg) UAV is capable of full autonomous flight (including takeoff and landing) of a pre-programmed, or easily configurable, custom mission. Furthermore, the autopilot manages the sensors measurements (i.e. beacons or cameras) to update the flying mission automatically in flight. Specific functionalities such as terrain following were developed and implemented. Ground station programming of the UAV is not needed, except compulsory monitoring, as the rescue mission can be accomplished in a full automatic mode.

The present paper discusses the use of a Kalman filter-based method to identify fall events during rock climbing activity. The proposed technique relies on the acquisition of three-axis acceleration and altitude by means of a data logger integrated within the climber's sit harness. Time-domain results exhibit the working principle of the algorithm. Furthermore, the data provided by eight climbers is analysed and discussed to validate the method.

From an athlete’s perspective, the identification of falls during rock climbing is of major importance. It constitutes a solid performance indicator, but more importantly, it could be used to trigger an instantaneous alarm to rescue teams, thus reducing the negative health consequences for the climber. In this context, an artificial neural network–based technique for fall detection during rock climbing is presented in this study. The output of this tool could be used for safety and performance monitoring purposes. The proposed method exploits a neural network for binary pattern recognition. This network is fed with a set of features extracted in real time from the acceleration and altitude signals acquired by means of a wearable device. The classifier is trained and validated with experimental datasets recorded during real climbing sessions of eight athletes through different route grades and conditions. This article illustrates the architecture of the proposed algorithm, feature extraction process, and evaluation of its accuracy. In addition, an analysis of the severity level of the detected falls is conducted. The method is able to identify real fall events with a high success rate, while yielding very few false positive indications of a fall.

Multiribbed serpentine belt drive systems are widely adopted in accessory drive automotive applications due to the better performances relative to the flat or V-belt drives. Nevertheless, they can generate unwanted noise and vibration which may affect the correct functionality and the fatigue life of the belt and of the other components of the transmission. The aim of the paper is to analyze the effect of the shear deflection in the rubber layer between the pulley and the belt fibers on the rotational dynamic behavior of the transmission. To this end the Firbank’s model has been extended to cover the case of small amplitude vibrations about mean rotational speeds. The model evidences that the shear deflection can be accounted for by an elastic term reacting to the torsional oscillations in series with a viscous term that dominates at constant speed. In addition, the axial deformation of the belt spans are taken into account. The numerical model has been validated by the comparison with the experimental results obtained on an accessory drive transmission including two pulleys and an automatic tensioner. The results show that the first rotational modes of the system are dominated by the shear deflection of the belt.

No abstract

In the present work, an experimental analysis of the performances of a twin arm tensioner is conducted. The investigated device is used in an automotive belt drive system mounting a belt starter generator. This configuration represents the latest trend of micro-hybrid technologies and is devoted to keep the tension of the belt within a reasonable range, while obtaining the highest possible efficiency in both motor and generator modes. At first, the functionality of a twin arm tensioner is investigated with a static model. Afterward, the performances of a real tensioner are experimentally assessed through a dedicated test rig in quasi-static conditions. The system is benchmarked in terms of angular displacement of the tensioner arms, belt tensions on the corresponding spans, and sliding arc in different operating conditions. Finally, experimental and simulation results are compared. It is shown that the proposed static model is able to capture the behavior of the real device and highlight its functionality.

No abstract

Safety improvements in mountaineering gear have enabled the increasing popularity of rock climbing as a sport. Both amateurs and experts want to know the condition of their equipment with a high degree of reliability. For climbing ropes, diagnostics are only carried out qualitatively by visual inspection. The assessment is left to the personal judgment of the user, thus leaving considerable margins of uncertainty on the rope’s condition. To address this shortcoming, this article explores the possibility of estimating fatigue damage from the impact force on the rope. This value is estimated from the measurements of the climber’s acceleration using a wearable device. Then, force data are correlated to the fatigue characteristic of the rope. In this study, three ropes were used by professional climbers through different routes. After this field conditioning, the ropes were tested following the UIAA standard and compared to a control rope. The results show that the proposed method can estimate the rope cumulative damage, but it relies on the accuracy of the damage model. In particular, the parameter describing the contact between the rope and the runner is important for a correct estimate.