Micro-electromechanical system sensors in unscented Kalman filter-based condition monitoring of hydraulic systems

Nurmi, Jarmo; Honkakorpi, Janne; Vihonen, Juho; Mattila, Jouni

doi:10.1109/aim.2013.6584117

Cited by 2 publications

(4 citation statements)

References 14 publications

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“…The IAS measurement is widely used in the area of fault diagnosis, condition monitoring and control of rotating machines. By studying the IAS variations, a large amount of information about the health status of the machine can be obtained (Nurmi 2013). Many different methods have been developed for angular speed measurement.…”

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

“…Many different methods have been developed for angular speed measurement. Each successive method has attempted to improve measurement performance using a different strategy to process encoder signals based on two basic principles: counting the number of pulses in a given time duration and measuring the elapsed time for a single cycle of encoder signal (Nurmi 2013). In general, average angular speed may be defined as:…”

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

“…It uses a slotted wheel with a single LED and photo detector pair to generate pulses as the wheel turns and the speed of an object can be calculated by measuring the pulse duration Δti (i.e. elapsed time or time span for a pulse i) between successive pulses (Nurmi 2013). Assuming that, M is encoder pulses in one revolution, the duration of the clock cycle is ts and the number of clock cycles in a speed pulse is Nc, then the IAS in rad/sec can be calculated as:…”

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

“…However, these sensors are usually expensive, their installation is difficult and not suitable for isolated environment. Therefore, many researches have tried to use MEMS sensors, which are low-cost, small in size and easy to install as an alternative for encoders (Nurmi 2013).…”

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

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Performance evaluation of wireless MEMS accelerometer for reciprocating compressor condition monitoring

Mones¹,

Feng²,

Ogbulaor³

et al. 2016

Power Engineering

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With recent development in wireless communication and Micro Electro Mechanical Systems (MEMS) technology, it becomes easier to monitor rotating machinery conditions by mounting compact wireless MEMS accelerometers directly on the rotor. This has the potential to provide more accurate dynamic characteristics of the rotating machine and hence achieving high monitoring performance. In this paper, a tiny MEMS accelerometer together with a battery powered microcontroller is mounted on the flywheel to acquire the on-rotor accelerations of a two-stage reciprocating compressor. The measured acceleration data is streamed to a host computer wirelessly via Bluetooth Low Energy (BLE) module. The true tangential acceleration is reconstructed by combining two orthogonal outputs of the sensor, which contain gravitational accelerations. To evaluate the performance of the wireless sensor, three different fault conditions including intercooler leakage, second stage discharge valve leakage and asymmetric stator winding of the motor driver are simulated individually on the compressor test rig. To confirm the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the Instantaneous Angular Speed (IAS) signal for comparison with signals from the wireless sensor. The experimental results show that the running status of the compressor can be remotely monitored, allowing different leakages and motor faults to be diagnosed based on the tangential acceleration reconstructed from a wireless on-rotor MEMS accelerometer.

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Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

Section: Ias Measurement Based On a Shaft Encodermentioning

confidence: 99%

See 2 more Smart Citations