摘要 :
Battlefield situational awareness is the core condition that determines the success or failure of the battlefield, and it is also an important application direction of photodetectors. The rapid development of AI technology in rece...
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Battlefield situational awareness is the core condition that determines the success or failure of the battlefield, and it is also an important application direction of photodetectors. The rapid development of AI technology in recent years is about to cause major changes in future wars. The new AI battlefield will also put forward new urgent needs for situational awareness. This article summarizes the current main modes of collaborative detection of battlefield situation awareness and its research status, including radar / infrared composite detection, multi-source data fusion of radar / infrared detection, cooperative target recognition, target tracking, etc. On this basis, combined with the current development trend of the intelligence level of the main battlefield equipment, we get the development needs of future intelligent battlefield situational awareness for new types of collaborative detection, including requirements for its style, angle, speed, and detection targets of distributed collaborative detection. Based on this, the key development directions and core issues to be solved for intelligent battlefield situational awareness in the future are proposed.
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摘要 :
Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limi...
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Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limitation of spatial information bandwidth and initial information, few shot learning based incremental fault diagnosis provides a new way for on-line fault detection of on-orbit equipment. In this paper, an incremental fault diagnosis method for on-orbit equipment based on cut edge weight estimation is proposed by combining the framework of collaborative learning and the idea of graph theory data editing. The experiment of applying above method to space actuating system was also carried out.
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摘要 :
Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limi...
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Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limitation of spatial information bandwidth and initial information, few shot learning based incremental fault diagnosis provides a new way for on-line fault detection of on-orbit equipment. In this paper, an incremental fault diagnosis method for on-orbit equipment based on cut edge weight estimation is proposed by combining the framework of collaborative learning and the idea of graph theory data editing. The experiment of applying above method to space actuating system was also carried out.
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摘要 :
Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limi...
展开
Prognostics and systems health management (PHM) have been manifested the pivotal role for guaranteeing the on-orbit service capacity of space equipment with high reliability, high security and maintainability. Considering the limitation of spatial information bandwidth and initial information, few shot learning based incremental fault diagnosis provides a new way for on-line fault detection of on-orbit equipment. In this paper, an incremental fault diagnosis method for on-orbit equipment based on cut edge weight estimation is proposed by combining the framework of collaborative learning and the idea of graph theory data editing. The experiment of applying above method to space actuating system was also carried out.
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