A market for a low-cost vibration protection device in the rotating machine industry has been identified that satisfies the needs of small firms unable to afford and sustain a condition monitoring operation.
In this project, a system is developed that satisfies the need for a low-cost, conservative, configurable and intuitive device that can perform vibration measurements on a range of gearboxes and make an inference as to the level of vibrations coming from the bearings on the shafts.
The inference made by the device, derived from the frequency content of the measured signal, may be used by the operator of the gearbox to make a judgment of whether to have the gearbox investigated by a competent authority. In order to assist this investigation, a vibration history of the device is stored, both in time and frequency domain formats, as well as a full history of the relevant diagnostic information.
To reach this point of maturity, the project evolved through three different hardware configurations. The various iterations were tested within the scope for which they were designed and the lessons learned after each test was incorporated into the next iteration. The final iteration incorporated all the refinements of the system up to that point as well as the anticipated scope of further development into the commercial realm.
To verify the inference credibility of the device, the results of the final specification of the device was evaluated against data obtained from the condition monitoring department of SASOL in Secunda. The results were analysed on two accounts. Firstly the signal reproduction accuracy was evaluated, which established how accurately the signal was digitized and how the processing algorithms performed. Secondly, the inference accuracy was gauged against the practices of SASOL. On both accounts, the final device performed satisfactorily.
The end result of this project is considered a ‘near-commercial ready’ prototype with all the hardware on-board for user interaction, signal processing, 3rd party viewing of the data and future expandability.
Dissertation (MEng)--University of Pretoria, 2015.