Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 186, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2022.109833
Keywords
Building materials machinery; Data acquisition; Feature extraction; Fault diagnosis
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This paper introduces the characteristics and challenges of fault diagnosis in building materials machinery equipment, discusses the research status and development directions.
Building materials machinery equipment play an important role in the production of cement, brick and tile, glass and other building materials, which are high energy consumption industries. Due to advanced sensors, continuous improvement of signal acquisition technologies and increasing data storage space, a large amount of data can be used by scholars, which makes data -based fault diagnosis gradually studied by more and more scholars. With increasing amount of data, new challenges are as follows: there is very little data that can really be used; the research on compound fault diagnosis and weak fault diagnosis is still not mature; the diagnosis accuracy of variable speed components is low. These problems restrict the further development of fault diagnosis. In this paper, the characteristics of fault diagnosis of building materials equipment are first expounded, the principles and characteristics of main building materials equipment, signal classification, sensor selection and error correction are briefly introduced, then the research status are discussed, the existing difficulties and challenges are summarized, and the potential development directions and trends in this field are given.
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