Design and performance evaluation of smart vibration sensor for industrial applications with built-in MEMS accelerometers

Paper deals with design and experimental evaluation of performance of a smart vibration sensor for industrial applications based on two built-in MEMS accelerometers and signal pre-processing using a low power microcontroller. Sensor contains one single axis low noise broadband MEMS accelerometer with analog output and one tri-axial low noise MEMS accelerometer with a narrower frequency range and digital SPI interface. Data from both MEMS devices are processed using TI MSP430 microcontroller. The smart sensor has digital output interface, which allows easier connection to the subsequent data processing system and ensures higher immunity to electro-magnetic interference. The smart sensor is intended for measurements of overall vibration velocity in frequency range defined in ISO standard up to 1 kHz while applications above ISO frequency range up to 10 kHz for acceleration measurement used in bearing diagnostics are also expected. Performance parameters of each sensing device built-in inside the common housing have been evaluated in two steps. The first step dealt with precise measurement of metrological parameters of each device including nominal value of vibration sensitivity in the main axis, its frequency dependence and transverse sensitivity with cross-axial excitation. These measurements were performed on the accredited calibration system SPEKTRA CS18, which offers outstanding measurement uncertainty, and achieved results confirmed the correctness of the design of the whole system and its critical parts. The second step was intended for evaluation of the sensor in practical application, where comparison between both internal sensing systems and external reference accelerometer was performed on test stand with industrial actuators to perform real vibration measurement task. Also this step indicated suitability of the designed sensor for these range of applications. Further and more detailed evaluation is expected in the near future when complete signal processing and autodiagnostic features will be implemented in the system thanks to utilization of two separated sensing elements.