Monitoring the health of gearboxes has become necessary in manufacturing field, as unnoticed defects can result significant interruptions and expensive periods inactivity. Vibration diagnostics is a technique used to analyze vibration measured on gearbox housing detect internal fault symptoms. To identify these defects, it continuously record vibrations over long period time with high sample frequency. Consequently, essential have powerful computational capabilities for analyzing collected...

Prognostic problems related to a packing set usedin plunger-type high-pressure hypercompressor are investigatedin this study, focusing on predicting the remaining usefullife (RUL) of packing. A comprehensive health index(HI) for is based consumed energy. This consumedenergy corresponds cumulative area under the(1 − Ri)2 curve, where Ri denotes correlation coefficient ofthe singular-value vectors obtained from chronological Hanelmatrices leakage-flow data. By using domain knowledgeand...

Rolling bearings always operate under variable speed conditions, which poses a challenge for researchers in identifying and classifying bearing faults. In contrast to the stationary condition, Fault Characteristic Frequency (FCF) conditions exhibits value that depends on instantaneous shaft rotational (ISRS). The representation of FCFs frequency domain reveals overlapping patterns among them. To solve mentioned problem, novel tool is proposed established by mixing two methods: Fourier-based...

Wavelet transform is a powerful time-frequency-based analysis method often used in gear fault diagnostics. The development of wavelet closely linked to the improvement resolution. When high-frequency resolution allows for easy observation different frequency components, it symptom damage an individual part machine. This study effectively applied technique diagnose faulty gearboxes operated non-stationary conditions. complex problem that usual diagnostic approaches need help solve due its...

Wind power is increasingly seen as a global, sustainable, and eco-friendly energy option. However, one significant obstacle to further wind investment the high failure rate of turbines. The gearbox plays pivotal role in turbine performance. In recent years, there has been surge focus on fault diagnosis, reflecting its criticality prevalence industry. Time synchronous averaging (TSA) primary technique identify faults gearboxes using mechanical vibration signals. Generally, implementing TSA...

Abstract Fault diagnosis of gearboxes has attracted increasing interest in recent decades due to their ubiquity and importance the industry. Modern research trends focus on developing a system that works automatically with application artificial intelligence. These previous studies have used Deep Learning (DL) network without adequately addressing noise input data, requiring more data achieve effective training. Thus, this work proposes novel Transfer method using time–frequency...

Machine fault diagnostic techniques by vibration signal analysis have been applied and widely developed in the industry. In recent years, using least number of measuring devices to simplify process gear has attracted many researchers. Various digital methods time frequency domains effectively detect faults gearboxes operated stationary conditions or rotational speeds with minor fluctuations. However, reality, often work at large fluctuations variable loads due technological progress. such...

Wind energy is increasingly recognized as a worldwide sustainable and environmentally friendly power source. Nevertheless, an important barrier to further investment in wind the large rate of failure that occurs turbines. The gearbox, crucial component, has major effect on performance It consists complex planetary cylindrical gear systems, making it prone causing defects Therefore, there urgent need minimize downtime improve productivity turbine gearbox operations. Recent decades have...