SITARIS - Smart dIagnostics based on disTributed sensor ARrays and Image Signature recognition (Feasibility study)
| Reference number | |
| Coordinator | KUNGLIGA TEKNISKA HÖGSKOLAN - Dept of Aeronautical and Vehicle Engineering |
| Funding from Vinnova | SEK 169 000 |
| Project duration | November 2018 - February 2019 |
| Status | Completed |
| Venture | The strategic innovation programme Electronic Components and Systems: |
| Call | Electronic Components and Systems. Research and innovation feasibility studies 2018. |
Important results from the project
Conduct a feasibility study in order to develop a radically new approach to smart monitoring based on identifying and extracting characteristic signatures from distributed sensor array images. In particular, this study comprises an experimental proof-of-concept with a specific target industrial application (electric motor).
Expected long term effects
Experimental results show that the motor signatures are sparse, which is a positive result towards the classification of the images into few patterns: signatures of the electric motor indicate that the noise due to the fan differs in pattern from the noise due to the electromagnetically-induced vibrations. Besides the possibility of diagnosing the machine, the signatures also provide indicators about the operation, performance, and future design of the machine
Approach and implementation
An ABB electric motor is chosen as the target industrial application, and it is driven with a PWM control signal at varying operational speed. Microphones and accelerometers record time data at various locations on (and in the vicinity of) the motor. Pressure and vibration data are used to calculate the signatures, whose sparsity (few characteristic patterns) is compared with that of the time data.