Structural Health Monitoring

Structural health monitoring of machines or structures refers to the monitoring of the “state of health” with the help of sensor technology during the ongoing operation of the machine or during use or work on a structure. The sensor data measured in this way is intended to provide information as to whether, for example, a machine needs to be overhauled, whether tools need to be changed or whether the plant is running under optimum conditions. The information obtained can help to increase the operating times and throughput times of a machine.

Accelerometers are often used as sensors to detect rather low frequency vibrations (< 10kHz). Further information can be obtained with the help of acoustic emission sensors. These detect signals in the spectrum from 50 kHz to 1 MHz. A change in the signal signature in the frequency range can provide conclusions about material wear or stresses and thus help to detect failures at an early stage or prevent quality losses in the end product.

For the evaluation of sensor data, various research projects are currently underway to develop self-regulating machine controls with the help of machine learning algorithms and AI.

Typical applications:

• Cavity formation in turbines
• Detection of tool wear or incorrect process settings on CNC milling machines
• Optimization of tool shape or process speed for metal deep drawing