Early Fault Detection in Bearing Using Time Domain Technique: Faulty Bearing Seeded on Inner Raceway and Ball

Abstract

One of the most important assets in an industry would be rotating machines. The reliability and availability are very crucial in order to support the accomplishment of an industry field. Major and even minor faults in rotating machines cause a decrease in both productivity and cost efficiency. Various methods have been studied by researcher and introduced in the industry for the detection of an early fault in rotating machines. Vibration signal analysis is one of a standout amongst other methods. This research paper focused on early fault detection in the bearing component at two different positions; inner raceway and ball. The faults were established at three different diameters of 0.007 inches, 0.021 inches, and 0.028 inches. By utilizing time domain technique, parameters such as mean, median, standard deviation, RMS, skewness, impulse factor and shape factor were determined. The vibration signal for both healthy and faulty bearing was deliberated by using the MATLAB software. All the data obtained were represented in graphs where the healthy and faulty bearing values were compared and analyzed.

Rolling bearing fault detection based on vibration signal analysis and cumulative sum control chart

“…The graph can be skewed on one hand or the other. The value of skewness can be both positive and negative [1]. In terms of the skewness values that are depicted in Figure 11, it can be observed that the skewness patterns for the five bearing health states are overlapping, and there is not any useful information that can be gained from them.…”

“…Rotating machinesare important for different industries, such as oil and gas industries, construction, and power plant industries.A catastrophic failure of rotating machinery would have a huge effect on the manufacturing sector. As the malfunction progresses, the machine's energy consumption will increase, while its performance will decrease.Gradually, followed by a sudden failure, will not only decrease production volume but will also result in increased operating costs for the reconstruction, as well as wasting time for the employees as they wait.On a larger scale, continued use of a defective machine could result in physical injury to the person operating the machine, and in the worst-case scenario, death [1]. A rolling bearing part is a critical com-ponent in engineering machinery, and even minor damage can result in unexpected production halts or industrial accidents.Bearing faults can occur for various reasons, including heavy loads that are unstable and inadequate lubrication [2].…”

“…As a result, early identification and diagnosis of faults will greatly reduce the impact of defective machinery. It is highly cost-effective, reducing output losses and increasing productivity while also improving human and environmental protection [1]. Acoustic analysis, temperature control, oil analysis, stator current, and vibration analysis can all be used to detect bearing defects [3].…”