Numerous novel bearing monitoring and diagnosis techniques have been explored in the last two decades to provide a technique that is capable of picking up an incipient bearing fault. On general terms, this is in line with condition monitoring – a process which involves tracking and assessing of the health of critical machines on the basis of detection, diagnosis and prognosis of failure. Bearings are crucial elements of rotating machinery with their purpose being to reduce friction between rotating parts and also support moving parts. Consequently, they are prone to unexpected failures that can yield irreversible damages.
Some authors suggested the utilization of vibration signals to detect imminent failures, success was achieved but under the condition that the sensor be located as close to the bearing defect as possible. On the other hand, optical fibers have demonstrated promising potential. Specifically, strain sensing, silica-based Fiber Bragg Grating (FBG) sensors that have been widely used in static structural health monitoring of bridges, blades and aeronautical structures. However, regarding the subject matter, little information has been published. In fact, no studies on the bearing diagnosis on strain time series have been reported.
In this context, researchers at Ben-Gurion University of the Negev comprised of Prof. Jacob Bortman and Dr. Shlomi Konforty in collaboration with Dr. Hasib Alian (Israel Air Force), Dr. Uri Ben-Simon (Israel Aerospace Industries), Dr. Renata Klein (R.K. Diagnostics) and Dr. Moshe Tur at the Tel Aviv University investigated the capabilities of FBG sensors to monitor bearing defects, including the determination of their sizes. The proposed system was based on the advantage and the ability of the FBG to provide a signal whose contents were mostly determined by the bearing-induced mechanical effects, rather than being influenced by remotely-induced irrelevant and disturbing sources of mechanical noise. Their work is currently published in the research journal, Mechanical Systems and Signal Processing.
In brief, they started by providing a brief description of the FBG sensor following which the experimental setup, test setup, position of the fibers and the defect locations were clearly elucidated. The team then presented test results that included a comparison between healthy and faulty bearings, as well as the techniques for the detection of spalls, and a method to measure the spall width using the FBG signals was proposed and validated.
The Israeli scientists demonstrated that the FBG sensors could be placed in the immediate proximity of bearings, thereby considerably enhancing the strain signal generated by the bearing through an improved signal-to-noise ratio and a reduction of remote influences: local strain was measured rather than the combined local and global acceleration, as in standard vibration measurements.
In summary, a comprehensive pioneering research on diagnostics of bearings by strain measured using FBG fiber optical sensors was presented by Jacob Bortman and his colleagues. Overall, all housing measurement points provided acceptable sensitivity, which was found to be inversely proportional to the geometric distance between the sensor and the fault being indifferent to global, remotely-induced vibrations of the system. Altogether, fiber-optic sensors appear to have promising diagnostic potential for spall-like faults in both the outer and inner races of ball bearings with a very good discrimination power.
Hasib Alian, Shlomi Konforty, Uri Ben-Simon, Renata Klein, Moshe Tur, Jacob Bortman. Bearing fault detection and fault size estimation using fiberoptic sensors. Mechanical Systems and Signal Processing, volume 120 (2019) page 392–407.Go To Mechanical Systems and Signal Processing