Detection of rockfall using structure-borne noise on rockfall nets

Flexible rockfall barriers (rockfall nets) are an effective measure to reduce the risk of falling rocks and are therefore used worldwide to protect infrastructure such as roads, railways and residential areas. The monitoring of these protective structures is essential to ensure their functionality and to carry out necessary maintenance work in a timely manner. Automatic systems are increasingly being used to monitor rockfall nets. The most common systems for monitoring nets are based on several acceleration sensors that are attached to the nets or supports. However, this requires several sensors per net, with at least 4 to 6 sensors required for net lengths of up to 100 meters. Initial investigations have shown that rockfalls in nets induce a characteristic acoustic signal in the guy ropes running along the entire length of the net. These structure-borne sound signals have not yet been investigated, but can be used for the detection of rockfalls on nets. This project therefore aims to develop a new type of detection system that reliably detects rockfalls using acoustic sensors via structure-borne sound on the ropes of rockfall nets. The system can enable the detection of rockfalls with just one monitoring station per net, providing a cost-effective, easy-to-install alternative to currently available monitoring systems. The planned setup of a station comprises a contact microphone, which is attached to the tensioned rope, a microcontroller for data evaluation and a communication module. The project aims to investigate which signals can be expected for different sizes of rockfall and which interference signals must be expected. The optimal hardware components that best meet the requirements, such as difficult accessibility of the sensor locations, harsh alpine environment, etc., are to be determined. The project will then determine a detection algorithm that reliably detects rockfalls, has low error rates and can be executed on a resource-limited system such as a microcontroller. Furthermore, a method is to be developed that will enable an estimate of the location of the impact by analyzing the signal propagation times using two measuring points at the end of the rope of the rockfall network. It will also be investigated whether an initial estimate of the magnitude of the impact is possible based on the amplitude of the signal.