Deep transfer learning for rolling bearing fault diagnosis under variable operating conditions
نویسندگان
چکیده
منابع مشابه
Fault Diagnosis for Rolling Bearings under Variable Conditions Based on Visual Cognition
Fault diagnosis for rolling bearings has attracted increasing attention in recent years. However, few studies have focused on fault diagnosis for rolling bearings under variable conditions. This paper introduces a fault diagnosis method for rolling bearings under variable conditions based on visual cognition. The proposed method includes the following steps. First, the vibration signal data are...
متن کاملImproved Ensemble Empirical Mode Decomposition for Rolling Bearing Fault Diagnosis
Rolling bearing is an important part in mechanical system and faults occur frequently with vibration noise. Empirical mode decomposition (EMD) is a tool for nonlinear and non-stationary signals analysis. However, the major drawbacks of EMD are mode mixing problem, ensemble empirical mode decomposition (EEMD) provides a new tool for signal analysis, and it is an improved technique of EMD. In ord...
متن کاملThe Rolling Bearing Fault Feature Extraction Method Under Variable Conditions Based on Hilbert-Huang Transform and Singular Value Decomposition
The fault diagnosis precision for rolling bearings under variable conditions has always been unsatisfactory. For solving this problem, a feature extraction method combing the Hilbert-Huang transform with singular value decomposition was proposed in this paper. The method includes three steps. Firstly, instantaneous amplitude matrices were obtained by Hilbert-Huang transform from rolling bearing...
متن کاملA Robust Bearing Fault Detection and Diagnosis Technique for Brushless DC Motors Under Non-stationary Operating Conditions
Rolling element bearing defects are among the main reasons for the breakdown of electrical machines, and therefore, early diagnosis of these is necessary to avoid more catastrophic failure consequences. This paper presents a novel approach for identifying rolling element bearing defects in brushless DC motors under non-stationary operating conditions. Stator current and lateral vibration measur...
متن کاملPoint processes for bearing fault detection under non-stationary operating conditions
Bearing faults represent the most frequent mechanical faults in rotational machines. They are characterized by repetitive impacts between the rolling elements and the damaged surface. The time intervals between two impacts are directly related with the type and location of the surface fault. These time intervals can be elegantly analyzed within the framework of renewal point processes. With suc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Advances in Mechanical Engineering
سال: 2019
ISSN: 1687-8140,1687-8140
DOI: 10.1177/1687814019897212