Khaldoon F. Brethee

An investigation of electrical motor parameters in a sensorless variable speed drive for machine fault diagnosis

Motor current signature analysis (MCSA) is regarded as an effective technique for motor and its downstream equipment fault diagnostics. However, limited work has been carried out for motors based on a sensorless variable speed drive (VSD). This study focuses on investigation of mechanical fault detection and diagnosis using electrical signatures from a VSD system. An analytic analysis was conducted to show that the fault can induce sidebands in instantaneous current, voltage and power signals in the VSD system, rather than just the sideband in a drive without closed loop control. Then different degrees of tooth breakages in an industrial two-stage helical gearbox were experimentally studied. It has found that even though the measured signal is very noisy, common spectrum analysis can discriminate the small sidebands for the fault detection and diagnosis. However, it has found that the power signals resulted from the multiplication of the current and voltage can provide a better diagnostic results.

Frictional effects on the dynamic responses of gear systems and the diagnostics of tooth breakages

ABSTRACT To develop accurate diagnostic techniques, this study examines the dynamic responses of spur gear transmission system with including frictional effects on a tooth mesh process. An 8-degree-of-freedom model is developed to include the effects of supporting bearings, a driving motor and a loading system. Moreover, it takes into account not only the time-varying stiffness, but also the time-varying forces and moments due to the frictional effect. The latter causes additional vibration responses in the direction of the off-line-of-action (OLOA). To show the quantitative effect of the friction, vibration responses are simulated under different friction coefficients. It shows that an increase in friction coefficient value causes a nearly linear increase in the vibration features of diagnostics. However, features from torsional responses and the principal responses in the line-of-action show less changes in the vibration level, whereas the most significant increasing is in the OLOA direction. Furthermore, the spectral peaks at the rotational and sideband frequencies are influenced significantly by small breakage defects, especially when the friction effect is taken into account. In addition, the second and third harmonics of the mesh frequency are more influenced than the first harmonic component for all motions, which can be effective features for both indicating lubrication deterioration and improving conventional diagnostic features.

Analysis of frictional effects on the dynamic response of gear systems and the implications for diagnostics

To develop accurate diagnostic techniques, this study examines gear dynamic responses based on a model including the frictional effect of tooth mesh process. An 8-DOF (degree-of-freedom) model is developed to include the effect of not only gear dynamics but also supporting bearings, a driving motor and a loading system. Moreover, it takes into account the nonlinearity of both the time varying stiffness and the time-varying forces due to the friction effect. The latter causes additional vibration responses in the direction of the off-line-of-action (OLOA). To show the quantitative effect of the friction, vibration responses are simulated under different friction coefficients. It shows that an increase in friction coefficient value causes a nearly linear increase in the vibration features. However, features from torsional responses and the principal responses in the line-of-action (LOA) show less changes in the vibration level, whereas the most significant increasing is in the OLOA direction. In addition, the second and third harmonics of the meshing frequency are more influenced than the first harmonic component for all motions. These vibration responses are more sensitive for indicating lubrication changes and enhancing conventional diagnostic features.

Monitoring gearbox using a wireless temperature node powered by thermal energy harvesting module

Condition monitoring (CM) of gearbox is a crucial activity due to its importance in power transmission for many industrial applications. Monitoring temperature is an effective mean to collect useful information about the healthy conditions of the gearbox. This study investigates the use of a novel wireless temperature node to monitor and diagnose different faults on a gearbox transmission system under different conditions. The wireless temperature node was fabricated with a novel feature that it is supplied by a thermoelectric generator module mounted on the gearbox house to be monitored so that the measurement system avoids the shortage of using a wired power sources or the requirement for recharging or changing batteries. Moreover, the temperatures from lubricating oils and housing are modelled empirically to implement a model based detection. The results show that this monitoring approach allows a number of common faults: tooth breakage, oil shortage, and shaft misalignment to be separated under different loads, which demonstrates the outstanding performance of the proposed system and thus suitable for online and automated condition monitoring.

The detection of lubricating oil viscosity changes in gearbox transmission systems driven by sensorless variable speed drives using electrical supply parameters

Lubrication oil plays a decisive role to maintain a reliable and efficient operation of gear transmissions. Many offline methods have been developed to monitor the quality of lubricating oils. This work focus on developing a novel online method to diagnose oil degradation based on the measurements from power supply system to the gearbox. Experimental studies based on an 10kW industrial gearbox fed by a sensorless variable speed drive (VSD) shows that measurable changes in both static power and dynamic behaviour are different with lube oils tested. Therefore, it is feasible to use the static power feature to indicate viscosity changes at low and moderate operating speeds. In the meantime, the dynamic feature can separate viscosity changes for all different tested cases.