The widespread adoption of tunnel boring machines(TBMs)has led to an increased focus on disc cutter wear,including both normal and abnormal types,for efficient and safe TBM excavation.However,abnormal wear has yet to ...The widespread adoption of tunnel boring machines(TBMs)has led to an increased focus on disc cutter wear,including both normal and abnormal types,for efficient and safe TBM excavation.However,abnormal wear has yet to be thoroughly investigated,primarily due to the complexity of considering mixed ground conditions and the imbalance in the number of instances between the two types of wear.This study developed a prediction model for abnormal TBM disc cutter wear,considering mixed ground conditions,by employing interpretable machine learning with data augmentation.An equivalent elastic modulus was used to consider the characteristics of mixed ground conditions,and wear data was obtained from 65 cutterhead intervention(CHI)reports covering both mixed ground and hard rock sections.With a balanced training dataset obtained by data augmentation,an extreme gradient boosting(XGB)model delivered acceptable results with an accuracy of 0.94,an F1-score of 0.808,and a recall of 0.8.In addition,the accuracy for each individual disc cutter exhibited low variability.When employing data augmentation,a significant improvement in recall was observed compared to when it was not used,although the difference in accuracy and F1-score was marginal.The subsequent model interpretation revealed the chamber pressure,cutter installation radius,and torque as significant contributors.Specifically,a threshold in chamber pressure was observed,which could induce abnormal wear.The study also explored how elevated values of these influential contributors correlate with abnormal wear.The proposed model offers a valuable tool for planning the replacement of abnormally worn disc cutters,enhancing the safety and efficiency of TBM operations.展开更多
SEN is a key relative technology to TSCC, the quality of which influences not only the heats of continuous casting but also the stream field in the mould. The powder line is the key part of SEN, that determines the co...SEN is a key relative technology to TSCC, the quality of which influences not only the heats of continuous casting but also the stream field in the mould. The powder line is the key part of SEN, that determines the continuous casting life. In this study the microstructure of used SEN samples were examined by SEM, the causes of the abnormal erosion phenomena were analyzed from slag corrosion mechanism, reactions between carbon containing refractories and slag and molten steel, properties of refractories. The improvement of the quality of SEN were achieved by adjusting the graphite content and composite structure designing of SEN＇s powder line.展开更多
With the continuous improvement of the accuracy requirements of clinical base or base tooth and denture,the design of denture neck edge is becoming thinner and thinner,and the presintering zirconia dioxide billet for ...With the continuous improvement of the accuracy requirements of clinical base or base tooth and denture,the design of denture neck edge is becoming thinner and thinner,and the presintering zirconia dioxide billet for denture making evacuation and low strength material mechanical characteristics make the certain probability of denture neck edge fragmentation and peeling in the cutting process.Based on this phenomenon,the abnormal wear is the main reason,and a method of high frequency ultrasonic time cleaning to reduce the fracture of the denture neck in actual cutting is proposed.展开更多
基金support of the“National R&D Project for Smart Construction Technology (Grant No.RS-2020-KA157074)”funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land,Infrastructure and Transport,and managed by the Korea Expressway Corporation.
文摘The widespread adoption of tunnel boring machines(TBMs)has led to an increased focus on disc cutter wear,including both normal and abnormal types,for efficient and safe TBM excavation.However,abnormal wear has yet to be thoroughly investigated,primarily due to the complexity of considering mixed ground conditions and the imbalance in the number of instances between the two types of wear.This study developed a prediction model for abnormal TBM disc cutter wear,considering mixed ground conditions,by employing interpretable machine learning with data augmentation.An equivalent elastic modulus was used to consider the characteristics of mixed ground conditions,and wear data was obtained from 65 cutterhead intervention(CHI)reports covering both mixed ground and hard rock sections.With a balanced training dataset obtained by data augmentation,an extreme gradient boosting(XGB)model delivered acceptable results with an accuracy of 0.94,an F1-score of 0.808,and a recall of 0.8.In addition,the accuracy for each individual disc cutter exhibited low variability.When employing data augmentation,a significant improvement in recall was observed compared to when it was not used,although the difference in accuracy and F1-score was marginal.The subsequent model interpretation revealed the chamber pressure,cutter installation radius,and torque as significant contributors.Specifically,a threshold in chamber pressure was observed,which could induce abnormal wear.The study also explored how elevated values of these influential contributors correlate with abnormal wear.The proposed model offers a valuable tool for planning the replacement of abnormally worn disc cutters,enhancing the safety and efficiency of TBM operations.
文摘SEN is a key relative technology to TSCC, the quality of which influences not only the heats of continuous casting but also the stream field in the mould. The powder line is the key part of SEN, that determines the continuous casting life. In this study the microstructure of used SEN samples were examined by SEM, the causes of the abnormal erosion phenomena were analyzed from slag corrosion mechanism, reactions between carbon containing refractories and slag and molten steel, properties of refractories. The improvement of the quality of SEN were achieved by adjusting the graphite content and composite structure designing of SEN＇s powder line.
文摘With the continuous improvement of the accuracy requirements of clinical base or base tooth and denture,the design of denture neck edge is becoming thinner and thinner,and the presintering zirconia dioxide billet for denture making evacuation and low strength material mechanical characteristics make the certain probability of denture neck edge fragmentation and peeling in the cutting process.Based on this phenomenon,the abnormal wear is the main reason,and a method of high frequency ultrasonic time cleaning to reduce the fracture of the denture neck in actual cutting is proposed.
