For some repeatedly occurring failure with root cause,the reliability centered maintenance(RCM)can’t deal with them effectively.So,the logic diagram of RCM was improved by combining it with proactive maintenance tech...For some repeatedly occurring failure with root cause,the reliability centered maintenance(RCM)can’t deal with them effectively.So,the logic diagram of RCM was improved by combining it with proactive maintenance technology.First,root cause analysis is used to build a key result-cause chain of the repeatedly occur failure.Then,a reasonable link in the chain,which work station is suitable to be monitored and repaired,should be selected.Finally,the corresponding proactive maintenance measure should be adopted to prevent the matter occur on the chain and broken the key result-cause chain,and the repeatedly occur failure is to be prevent at a deeper level or from the root cause.By doing this,a system engineering method comes into being,not only it can determine the needs of preventive maintenance for equipment,but also determine the proactive maintenance needs for equipment.The analysis result of reliability centered maintenance and the analysis result considering proactive maintenance are combined to form a maintenance guideline containing proactive maintenance strategy.展开更多
The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data ...The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.展开更多
In recent years,with the deterioration of mineral resource endowment and the development of intelligent technologies,traditional flotation machine technology has been rapidly integrated with cutting-edge technologies,...In recent years,with the deterioration of mineral resource endowment and the development of intelligent technologies,traditional flotation machine technology has been rapidly integrated with cutting-edge technologies,such as modern sensing,artificial intelligence,big data,and the Internet of Things.This integration aims to improve the efficiency and controllability of the flotation process,thereby driving the transformation of the mineral processing field toward intelligent,automated,and green directions.However,as a new development,intelligent flotation machines have not yet achieved a unified and clear understanding.This study interprets intelligent flotation machines from three aspects:definition,connotation,and development path.The core characteristics of intelligent flotation machines have been proposed,including self-sensing and self-diagnosis abilities in the whole spatial domain,data-based intelligent control algorithms,predictive maintenance of core components,and coordination of global and local optimization in flotation processes.This study identifies the current challenges faced by intelligent flotation machines,and proposes the future development paths,including enhancing the comprehensive monitoring and intelligent regulation of flotation parameters,improving equipment fault prediction and precise localization,and achieving unmanned operations and intelligent maintenance.By continuously optimizing and refining the design and application of intelligent flotation machines,they can play an increasingly important role in the sustainable development of the mining industry.展开更多
文摘For some repeatedly occurring failure with root cause,the reliability centered maintenance(RCM)can’t deal with them effectively.So,the logic diagram of RCM was improved by combining it with proactive maintenance technology.First,root cause analysis is used to build a key result-cause chain of the repeatedly occur failure.Then,a reasonable link in the chain,which work station is suitable to be monitored and repaired,should be selected.Finally,the corresponding proactive maintenance measure should be adopted to prevent the matter occur on the chain and broken the key result-cause chain,and the repeatedly occur failure is to be prevent at a deeper level or from the root cause.By doing this,a system engineering method comes into being,not only it can determine the needs of preventive maintenance for equipment,but also determine the proactive maintenance needs for equipment.The analysis result of reliability centered maintenance and the analysis result considering proactive maintenance are combined to form a maintenance guideline containing proactive maintenance strategy.
基金supported by National Key Natural Science Foundation of China (Grant No. 50635010)
文摘The currently prevalent machine performance degradation assessment techniques involve estimating a machine＇s current condition based upon the recognition of indications of failure features,which entail complete data collected in different conditions.However,failure data are always hard to acquire,thus making those techniques hard to be applied.In this paper,a novel method which does not need failure history data is introduced.Wavelet packet decomposition（WPD） is used to extract features from raw signals,principal component analysis（PCA） is utilized to reduce feature dimensions,and Gaussian mixture model（GMM） is then applied to approximate the feature space distributions.Single-channel confidence value（SCV） is calculated by the overlap between GMM of the monitoring condition and that of the normal condition,which can indicate the performance of single-channel.Furthermore,multi-channel confidence value（MCV）,which can be deemed as the overall performance index of multi-channel,is calculated via logistic regression（LR） and that the task of decision-level sensor fusion is also completed.Both SCV and MCV can serve as the basis on which proactive maintenance measures can be taken,thus preventing machine breakdown.The method has been adopted to assess the performance of the turbine of a centrifugal compressor in a factory of Petro-China,and the result shows that it can effectively complete this task.The proposed method has engineering significance for machine performance degradation assessment.
文摘In recent years,with the deterioration of mineral resource endowment and the development of intelligent technologies,traditional flotation machine technology has been rapidly integrated with cutting-edge technologies,such as modern sensing,artificial intelligence,big data,and the Internet of Things.This integration aims to improve the efficiency and controllability of the flotation process,thereby driving the transformation of the mineral processing field toward intelligent,automated,and green directions.However,as a new development,intelligent flotation machines have not yet achieved a unified and clear understanding.This study interprets intelligent flotation machines from three aspects:definition,connotation,and development path.The core characteristics of intelligent flotation machines have been proposed,including self-sensing and self-diagnosis abilities in the whole spatial domain,data-based intelligent control algorithms,predictive maintenance of core components,and coordination of global and local optimization in flotation processes.This study identifies the current challenges faced by intelligent flotation machines,and proposes the future development paths,including enhancing the comprehensive monitoring and intelligent regulation of flotation parameters,improving equipment fault prediction and precise localization,and achieving unmanned operations and intelligent maintenance.By continuously optimizing and refining the design and application of intelligent flotation machines,they can play an increasingly important role in the sustainable development of the mining industry.
