The state of cutting tool determines the quality of surface produced on the machined parts.A faulty tool produces poor sur face,inaccurate geometry and non-economic production.Thus,it is necessary to monitor tool cond...The state of cutting tool determines the quality of surface produced on the machined parts.A faulty tool produces poor sur face,inaccurate geometry and non-economic production.Thus,it is necessary to monitor tool condition for a.machining process to have superior quality and economic production.In the pre-sent study,fault classification of single point cutting tool for hard turning has been carried out by employing machine learning technique.Cutting force and vibration signals were acquired to monitor tool condition during machining.A set of four tooling conditions namely healthy,worn flank,broken insert and extended tool overhang have been considered for the study.The machine learning technique was applied to both vibration and cutting force signals.Discrete wavelet features of the signals have been extracted using discrete wavelet trans formation(DWT).This transformation represents a large dataset into approximation coeffcients which contain the most useful information of the dataset.Significant features,among features extracted,were selected using J48 decision tree technique.Clas-sification of tool conditions was carried out us ing Naive Bayes algorithm.A 10 fold cross validation was incorporated to test the validity of classifier.A comparison of performance of classifier was made between cutting force and vibration signal to choose the best signal acquisition method in classifying tool fault conditions using machine learning technique.展开更多
The ancient structure characteristic,correlation of the oil and the hydrocarbon source rock characteristics,hydrocarbon migration trace,types and conditions of traps,migration passages and characteristic of hydrocarbo...The ancient structure characteristic,correlation of the oil and the hydrocarbon source rock characteristics,hydrocarbon migration trace,types and conditions of traps,migration passages and characteristic of hydrocarbon accumulation are researched in this paper.It is shown through the analysis that two main large tectonic activities after the Early Hercynian orogeny resulted in different tectonic patterns in the study area.Two main hydrocarbon infills occurred in the Donghetang Formation,the first occurred in the Early Hercynian resulting in the ancient hydrocarbon accumulation in the northern Tahe,the second infill was a large amount that occurred in places beneficial for hydrocarbon accumulation,such as structural traps and structural-stratigraphic traps formed in the Early Himalayan orogeny after migration along the faults through source rocks and other passages.Before the earlier period of the Himalayan orogeny,the petroleum mainly migrated to the north,whereas petroleum migrated to the south and southeast because of the structural reverse in the Himalayan orogeny,so the middle and later period of the Himalayan orogeny is the key period for hydrocarbon accumulation.The model of"oil generation formed early,hydrocarbon accumulation controlled by the faults through source rocks and structures formed late"is proposed.It is pointed out that the south of the research area is currently the beneficial district for hydrocarbon accumulation, which provides the basis for future petroleum exploration.展开更多
文摘The state of cutting tool determines the quality of surface produced on the machined parts.A faulty tool produces poor sur face,inaccurate geometry and non-economic production.Thus,it is necessary to monitor tool condition for a.machining process to have superior quality and economic production.In the pre-sent study,fault classification of single point cutting tool for hard turning has been carried out by employing machine learning technique.Cutting force and vibration signals were acquired to monitor tool condition during machining.A set of four tooling conditions namely healthy,worn flank,broken insert and extended tool overhang have been considered for the study.The machine learning technique was applied to both vibration and cutting force signals.Discrete wavelet features of the signals have been extracted using discrete wavelet trans formation(DWT).This transformation represents a large dataset into approximation coeffcients which contain the most useful information of the dataset.Significant features,among features extracted,were selected using J48 decision tree technique.Clas-sification of tool conditions was carried out us ing Naive Bayes algorithm.A 10 fold cross validation was incorporated to test the validity of classifier.A comparison of performance of classifier was made between cutting force and vibration signal to choose the best signal acquisition method in classifying tool fault conditions using machine learning technique.
基金supported by State Key Laboratory of Petroleum Reservoir Geology and Reservoir Engineering and partly by Northwest Bureau of Petroleum of SINOPEC
文摘The ancient structure characteristic,correlation of the oil and the hydrocarbon source rock characteristics,hydrocarbon migration trace,types and conditions of traps,migration passages and characteristic of hydrocarbon accumulation are researched in this paper.It is shown through the analysis that two main large tectonic activities after the Early Hercynian orogeny resulted in different tectonic patterns in the study area.Two main hydrocarbon infills occurred in the Donghetang Formation,the first occurred in the Early Hercynian resulting in the ancient hydrocarbon accumulation in the northern Tahe,the second infill was a large amount that occurred in places beneficial for hydrocarbon accumulation,such as structural traps and structural-stratigraphic traps formed in the Early Himalayan orogeny after migration along the faults through source rocks and other passages.Before the earlier period of the Himalayan orogeny,the petroleum mainly migrated to the north,whereas petroleum migrated to the south and southeast because of the structural reverse in the Himalayan orogeny,so the middle and later period of the Himalayan orogeny is the key period for hydrocarbon accumulation.The model of"oil generation formed early,hydrocarbon accumulation controlled by the faults through source rocks and structures formed late"is proposed.It is pointed out that the south of the research area is currently the beneficial district for hydrocarbon accumulation, which provides the basis for future petroleum exploration.