scholarly journals Prognostics and health management technology for radar system

2020 ◽  
Vol 309 ◽  
pp. 04009
Author(s):  
Yongle Lyu ◽  
Zhuo Pang ◽  
Chuang Zhou ◽  
Peng Zhao

Information-based war in the future has a higher requirement to the maintenance and support ability of radar system. Prognostics and Health Management(PHM) technology represents the research hotspot of maintenance system, and following key techniques need to be resolved to research on the radar PHM technology such as the acquirement and selection of health information and fault signs of a radar’s electronical components, mass data warehousing and mining, fusion of multi-source test data and multi-field characteristic information, failure model building and forecasting, automatic decision-making on maintenance, and at the same time improving the self built-in test abilities of radar’s components based on the optimization of Design For Testability(DFT). The radar PHM technology has the trend of “built-in to integrate”, “together with DFT” and “long-distance and distributed”. However, subjected to radar’s complexity and current PHM technique level, radar PHM engineering still meets many challenges, but has bright future.

2012 ◽  
Vol 591-593 ◽  
pp. 1938-1941
Author(s):  
Xin Jie Shao ◽  
Li Jun Cao ◽  
Jin Hua Liu ◽  
Qiao Ma ◽  
Guang Tian ◽  
...  

Considering the encapsulation, tremendous working stress, complicated fault mechanism and process, an object-oriented architecture Prognostics and Health Management (PHM) system of Self-Propelled Gun is put forward to solve the difficulties in modern equipments’ maintenance decision and safeguard. The relative key techniques, such as fault characteristics extraction, system identification, data fusion among sensors, adaptive fault thresholds setting, intelligent fault inference mechanism and fault prediction mechanism are discussed in detail. Above functional modules compose the PHM system. Their mutual relationships and data flow are shown as architecture graph, which is the basis of PHM system establishment. Simulation verification experiments indicate that the proposed architecture can satisfy the requirements of standardization, hierarchy and evolvement, as well as reducing the maintenance cost and difficulties.


2020 ◽  
Vol 10 (16) ◽  
pp. 5639
Author(s):  
Jinwoo Sim ◽  
Seokgoo Kim ◽  
Hyung Jun Park ◽  
Joo-Ho Choi

Gears and bearings are one of the major components of many machines, which can result in operation downtime or even catastrophic failure of a whole system. This paper addresses a tutorial for the features extraction and selection of the gears and bearings, which is known as feature engineering, a prerequisite step for the prognostics and health management (PHM) of these components. While there have been many new developments in this field, no studies have addressed the tutorial aspects of features engineering to aid engineers in solving problems by their own effort, which is of practical importance for successful PHM. The paper aims at helping beginners learn the basic concepts, and implement the algorithms using the public datasets as well as those made by the authors. Matlab codes are provided for them to implement the process by their own hands.


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