Improved failure detection with higher degree of statistical confidence

Abstract: This master thesis has been performed by a request from Scania CV AB in Södertälje. Scania CV AB is a global company manufacturing heavy vehicles, such as busses and trucks. When developing a gearbox, an endurance test is made that shows failures, such as damaged gears or bearings. STP and delta-ANALYSER are used to discover this kind of failure. STP is developed by Scania CV AB, and it measures the vibration, oil pressure, temperature, etc. delta-ANALYSER is developed by Reilhofer. It is a measuring system that detects failures in the gearbox by comparing the vibrations with a reference. The main issue is that these tests are time consuming. The goal is to cut time and still be able to follow the results more accurately and in an early stage receive failure reports from bearings and gears. Accelerate the tests is not possible, because the test-rig is already heavily accelerated. The purpose of the thesis is to investigate existing methods for a more precise detection of a damage that has reached a certain size, also be able to isolate the source of a defect to a specific gear. In this thesis project different methods for detection of damages has been identified: vibration, thermography, acoustic emission, ultrasonic, oil analysis, etc. After an internal discussion, a combination of two methods: oil analysis and vibration, were chosen. Companies demonstrated their oil analysis systems. Advantages and disadvantages were discussed and it was decided to continue with an oil particle sensor, OPCom FerroS, from ARGO HYTOS, that detect the oil particles with a magnet in the flow of oil. The final system for detection of damages is a combination of OPCom FerroS and Scania’s current system: delta-ANALYSER and STP. The developed detection system was evaluated by the set system requirements, showing that the system meet 22 of the 33 tested requirements. All requirements could not be verified and needs more investigation and tests.