Undesirable self-excited chatter has always been a typical issue restricting the improvement of robotic milling quality and efficiency.Sensitive chatter identification based on processing signals can prompt operators ...Undesirable self-excited chatter has always been a typical issue restricting the improvement of robotic milling quality and efficiency.Sensitive chatter identification based on processing signals can prompt operators to adjust the machining process and prevent chatter damage.Compared with the traditional machine tool,the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process make it more challenging to extract chatter information.This paper proposes a novel method of chatter identification using optimized variational mode decomposition(OVMD)with multi-band information fusion and compression technology(MT).During the robotic milling process,the number of decomposed modes k and the penalty coefficient a are optimized based on the dominant component of frequency scope partition and fitness of the mode center frequency.Moreover,the mayfly optimization algorithm(MA)is employed to obtain the global optimal parameter selection.In order to conquer information collection about the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process,MT is presented to reduce computation and extract signal characteristics.Finally,the cross entropy of the image(CEI)is proposed as the final chatter indicator to identify the chatter occurrence.The robotic milling experiments are carried out to verify the proposed method,and the results show that it can distinguish the robotic milling condition by extracting the uncertain multiple chatter frequency bands and overcome the band-moving of the chatter frequency in robotic milling process.展开更多
Sodium silicate and that calcined at 400℃ for 2 h were used to catalyze the transesterification of cottonseed oil with methanol. Calcined sodium silicate （CSS） catalyst exhibited much higher catalytic activity and ...Sodium silicate and that calcined at 400℃ for 2 h were used to catalyze the transesterification of cottonseed oil with methanol. Calcined sodium silicate （CSS） catalyst exhibited much higher catalytic activity and stability. A maximum biodiesel yield of 98.9~ was achieved at methanol/oil mole ratio of 12：1, reaction temperature 65℃, reaction time 3.0 h, and CSS/oil mass ratio of 2 Wffo. After 7 consecutive reactions without any treatment, biodiesel yield reduced to 82.5%. Considering technological and economic feasibility, CSS base catalyst supported on 0 rings was prepared for continuous transesterification. The maximum yield was 99.1% under optimum conditions （reaction temperature 55 ~C, methanol velocity 1 ml. rain- 1, oil velocity 3 ml- rain- 1, and 5 tower sec- tions）. These results indicate that this new continuous biodiesel production process and apparatus present a great potential for industrial application in biodiesel.展开更多
基金supported by the Civil Aircraft Project(No.MJZ4-1N22),National Natural Science Foundation of China(No.51975053)Inversion and Application Project of Outcome(Nos.D44F9A65 and 2B0188E1)+1 种基金Key R&D Program of Inner Mongolia(No.2022YFHH0121)the Basic Research Fund of Beijing Institute of Technology(No.2021CX01023).
文摘Undesirable self-excited chatter has always been a typical issue restricting the improvement of robotic milling quality and efficiency.Sensitive chatter identification based on processing signals can prompt operators to adjust the machining process and prevent chatter damage.Compared with the traditional machine tool,the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process make it more challenging to extract chatter information.This paper proposes a novel method of chatter identification using optimized variational mode decomposition(OVMD)with multi-band information fusion and compression technology(MT).During the robotic milling process,the number of decomposed modes k and the penalty coefficient a are optimized based on the dominant component of frequency scope partition and fitness of the mode center frequency.Moreover,the mayfly optimization algorithm(MA)is employed to obtain the global optimal parameter selection.In order to conquer information collection about the uncertain multiple chatter frequency bands and the band-moving of the chatter frequency in robotic milling process,MT is presented to reduce computation and extract signal characteristics.Finally,the cross entropy of the image(CEI)is proposed as the final chatter indicator to identify the chatter occurrence.The robotic milling experiments are carried out to verify the proposed method,and the results show that it can distinguish the robotic milling condition by extracting the uncertain multiple chatter frequency bands and overcome the band-moving of the chatter frequency in robotic milling process.
基金Supported by the National Natural Science Foundation of China(21306088)National Key Technologies R&D Program of China(2015BAD15B07)+1 种基金State Key Laboratory of Chemical Engineering(SKL-Ch E-13A01,Tsinghua University,China)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD,China)
文摘Sodium silicate and that calcined at 400℃ for 2 h were used to catalyze the transesterification of cottonseed oil with methanol. Calcined sodium silicate （CSS） catalyst exhibited much higher catalytic activity and stability. A maximum biodiesel yield of 98.9~ was achieved at methanol/oil mole ratio of 12：1, reaction temperature 65℃, reaction time 3.0 h, and CSS/oil mass ratio of 2 Wffo. After 7 consecutive reactions without any treatment, biodiesel yield reduced to 82.5%. Considering technological and economic feasibility, CSS base catalyst supported on 0 rings was prepared for continuous transesterification. The maximum yield was 99.1% under optimum conditions （reaction temperature 55 ~C, methanol velocity 1 ml. rain- 1, oil velocity 3 ml- rain- 1, and 5 tower sec- tions）. These results indicate that this new continuous biodiesel production process and apparatus present a great potential for industrial application in biodiesel.
