The importance of preventing failures in bearings has led to a large amount research being conducted find methods for fault diagnostics and prognostics. Many these solutions, such as deep learning methods, require significant data perform well. This is reason why publicly available are important, there currently exist several open datasets that contain different conditions faults. However, one ...

Large mechanical equipment is subject to periodic vibrations in harsh operating environments for a long time. Bearing failure produces violent changes the behaviors of large rotating machinery as safety and reliability scene. Therefore, it especially significant effectively identify early bearing. Since signal bearing fault belongs low-frequency weak fault, hard classify characteristic frequenc...

Fault detection is a crucial step in condition based maintenance requiring. The importance of fault diagnosis necessitates an efficient and effective failure pattern identification method. Artificial Neural Networks (ANN) and Support Vector Machines (SVM) emerging as prospective pattern recognition techniques in fault diagnosis have been showing its adaptability, flexibility and efficiency. Reg...

The rotating machinery is a common class of machinery in the industry. The root cause of faults in the rotating machinery is often faulty rolling element bearings. This paper presents a novel technique using artificial neural network learning for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (harmmean and median), whic...

In the paper, two novel negative selection algorithms (NSAs) were proposed: FB-NSA and FFB-NSA. FBNSA has two types of detectors: constant-sized detector (CFB-NSA) and variable-sized detector (VFBNSA). The detectors of traditional NSA are generated randomly. Even for the same training samples, the position, size, and quantity of the detectors generated in each time are different. In order to el...

The periodic impulse feature is the most typical fault signature of the vibration signal from fault rolling element bearings (REBs). However, it is easily contaminated by noise and interference harmonics. In order to extract the incipient impulse feature from the fault vibration signal, this paper presented an autocorrelation function periodic impulse harmonic to noise ratio (ACFHNR) index base...