Measurement of Rotational Speed and Vibration Through Electrostatic Sensing and Digital Signal Processing

Rotating machines exist in a wide variety of industrial processes such as power generation, vehicle transportation, manufacturing and other industries. Often, they operate continuously for a long time and under a variety of harsh conditions. Thus, they are prone to failure in one or more of their components, causing a decrease in system efficiency and, ultimately, a complete breakdown. It is well known that when a machine component begins to deteriorate, its dynamic behaviour changes. Monitoring relevant parameters allows rapid identification of any changes that are taking place and possible failure modes. Rotational speed and vibration are key parameters in the condition monitoring of rotating machinery. These parameters usually contain abundant fault-related information about the machines.

A literature review is conducted to examine all existing techniques for rotational speed and vibration measurements. Advantages and existing limitations of the reviewed techniques are discussed. Consequently, a technical strategy, incorporating electrostatic sensing and digital signal processing techniques is proposed. Mathematical modelling is established and used to determine the characteristics of electrostatic sensors. The results of the model are used to optimise the electrode and markers design.

A novel electrostatic measurement system, including sensing electrodes, signal conditioning circuit and signal processing unit, has been designed and implemented to provide a solution to a robust online monitoring of rotational speed and vibration of rotating metallic shafts.

Extensive evaluations of the prototype system were conducted on purpose-built laboratory scale test rigs. Experimental results from the rotational speed measurement suggest that the measurement error is within ±0.2% over the speed range from 40 rpm to 3000 rpm with a repeatability less than 0.7%. Results obtained from the vibration displacement measurement of an unbalanced metallic shafts with 0.5mm eccentricity have demonstrated that the measurement system has a relative error no greater than ±0.6% under all test conditions. The developed measurement system can potentially be incorporated into a condition monitoring system, integrated with fault detection and diagnosis algorithms, to assess the working condition of rotating machinery, detect incipient faults and allow repairs to be scheduled.