Machinery Fault Diagnosis Scheme Using Redefined Dimensionless Indicators and mRMR Feature Selection
نویسندگان
چکیده
منابع مشابه
Global geometric similarity scheme for feature selection in fault diagnosis
This work presents a global geometric similarity scheme (GGSS) for feature selection in fault diagnosis, which is composed of global geometric model and similarity metric. The global geometric model is formed to construct connections between disjoint clusters in fault diagnosis. The similarity metric of the global geometric model is applied to filter feature subsets. To evaluate the performance...
متن کاملFusion of the Dimensionless Parameters and Filtering Methods in Rotating Machinery Fault Diagnosis
For the problem of large dimensionless index fluctuations in rotating machinery complex fault and that the corresponding scope is difficult to determine. In this paper proposes a rotating machinery complex fault method that combined dimensionless and the least squares method filtering. This method implementation filtering and determine the scope of the dimensionless index. By doing experiments ...
متن کاملFeature Extraction and Selection for Automatic Fault Diagnosis of Rotating Machinery
In this work we present three feature extraction models used in vibratory data from rotating machinery for bearing fault diagnosis. Vibrations signals are acquired by accelerometers which are then submitted to different feature extraction modules. Our tests suggest that pooling heterogeneous feature sets achieve better results than using a single extraction model. Besides, different classifiers...
متن کاملAn improved wrapper-based feature selection method for machinery fault diagnosis
A major issue of machinery fault diagnosis using vibration signals is that it is over-reliant on personnel knowledge and experience in interpreting the signal. Thus, machine learning has been adapted for machinery fault diagnosis. The quantity and quality of the input features, however, influence the fault classification performance. Feature selection plays a vital role in selecting the most re...
متن کاملPrediction of Protein Domain with mRMR Feature Selection and Analysis
The domains are the structural and functional units of proteins. With the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop effective methods for predicting the protein domains according to the sequences information alone, so as to facilitate the structure prediction of proteins and speed up their functional annotation. However, although many effor...
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: IEEE Access
سال: 2020
ISSN: 2169-3536
DOI: 10.1109/access.2020.2976832