This paper presents a new method for bearing fault diagnosis using the fusion of two primary
sensors: an accelerometer and a load cell. A novel condition-based monitoring (CBM) …

This paper presents the novel technique for fault diagnosis of bearing by fusion of two
different sensors: Vibration based and acoustic emission-based sensor. The diagnosis …

Sound-vibration signal fusion methods are widely applied in fault diagnosis, but the
acquisition of the sound signal is obviously affected by the position of the measurement …

The rolling bearing is a key element of rotating machine and its fault diagnosis is a research
focus. When a single fault of a rolling bearing fails to be addressed in time, it will cause …

The extraction of significant features is essential for efficient fault diagnosis and prognosis of
rolling element bearing. Data fusion is the predominant technology for extracting significant …

Rotating machinery breakdowns are most commonly caused by failures in bearing
subsystems. Consequently, condition monitoring of such subsystems could increase …

Classification of faults in mechanical components using machine learning is a hot topic in
the field of science and engineering. Generally, every real-world running mechanical system …

In the rolling bearing fault diagnosis, the vibration signal of single sensor is usually
nonstationary and noisy, which contains very little useful information, and impacts the …

In condition based maintenance, different signal processing techniques are used to sense
the faults through the vibration and acoustic emission signals, received from the machinery …

Intelligent operation and maintenance is an important part of Industry 4.0. In order to realize
the intelligent of plant equipment, it will make full use of artificial intelligence methods to …