This paper proposes a hybrid multi-object optimization method integrating a uniform design,an adaptive network-based fuzzy inference system(ANFIS),and a multi-objective particle swarm optimizer(MOPSO)to optimize the r...This paper proposes a hybrid multi-object optimization method integrating a uniform design,an adaptive network-based fuzzy inference system(ANFIS),and a multi-objective particle swarm optimizer(MOPSO)to optimize the rigid tapping parameters and minimize the synchronization errors and cycle times of computer numerical control(CNC)machines.First,rigid tapping parameters and uniform(including 41-level and 19-level)layouts were adopted to collect representative data for modeling.Next,ANFIS was used to build the model for the collected 41-level and 19-level uniform layout experiment data.In tapping center machines,the synchronization errors and cycle times are important consid-erations,so these two objects were used to build the ANFIS models.Then,a MOPSO algorithm was used to search for the optimal parameter combinations for the two ANFIS models simultaneously.The experimental results showed that the proposed method obtains suitable parameter values and optimal parameter combinations compared with the nonsystematic method.Additionally,the optimal parameter combination was used to optimize existing CNC tools during the commissioning process.Adjusting the proportional and integral gains of the spindle could improve resistance to deformation during rigid tapping.The posi-tion gain and prefeedback coefficient can reduce the synchronization errors significantly,and the acceleration and deceleration times of the spindle affect both the machining time and synchronization errors.The proposed method can quickly and accurately minimize synchronization errors from 107 to 19.5 pulses as well as the processing time from 3,600 to 3,248 ms;it can also shorten the machining time significantly and reduce simultaneous errors to improve tapping yield,there-by helping factories achieve carbon reduction.展开更多
The underwater tapping machine is composed of a center bit, a tapping cutter, a seal box, a main drive box, a boring bar assembly, a envelop, a gear case, a counter and so on. The drive system in underwater tapping ma...The underwater tapping machine is composed of a center bit, a tapping cutter, a seal box, a main drive box, a boring bar assembly, a envelop, a gear case, a counter and so on. The drive system in underwater tapping machine consists of a worm drive, a gear drive system and a screw drive. The worm drive is in the main drive box. The worm is connected with a hydraulic motor and driven by the hydraulic motor. The gear drive system is a combined gear train which is the combinations of the fixed axes and differential gear train in the gear case. On the one hand, by means of the fixed axes gear trains the turn and power of transmission shaft are transferred to the boring bar and the screw rod, causing differential turn between the boring bar and the screw rod. On the other hand, the turns of the boring bar and the screw rod are transferred to the differential gear train. The differential gear train is used to drive a special counter to count axial travel of the boring bar. The screw drive is composed of a feed screw and a nut on the boring bar. There is the differential turn between the boring bar and the feed screw. By means of the nut, the boring bar can feed automatically. With the movement of the sliding gear 7 in the gear case, the designed drive system can also be provided with the ability of fast forward and fast backward movement of the boring bar in its idle motion, resulting in the increase of the tapping efficiency.展开更多
为进一步提高有载分接开关(on-load tap changer,OLTC)机械状态监测的准确性,文中基于优化品质因数可调小波变换(tunable quality wavelet transform,TQWT)对OLTC切换过程中的振动信号进行了分析。即使用人工鱼群算法(artificial fish s...为进一步提高有载分接开关(on-load tap changer,OLTC)机械状态监测的准确性,文中基于优化品质因数可调小波变换(tunable quality wavelet transform,TQWT)对OLTC切换过程中的振动信号进行了分析。即使用人工鱼群算法(artificial fish swarm algorithm,AFSA)基于分解余量与整体正交系数研究了TQWT的优化分解方法,计算得到了OLTC振动信号的多个子序列,构建了基于优化孪生支持向量机(twin support vector machine,TWSVM)的OLTC机械故障诊断模型。对某CM型OLTC正常与典型机械故障下振动信号的分析结果表明,所提优化TQWT分解方法有效提高了OLTC振动信号分解结果的准确性。相对于其他诊断模型,所构建AFSA-TWSVM的OLTC机械故障诊断模型分类效果好且收敛速度更快。展开更多
基金Publication costs are funded by the Ministry of Science and Technology, Taiwan, underGrant Numbers MOST 110-2221-E-153-010.
文摘This paper proposes a hybrid multi-object optimization method integrating a uniform design,an adaptive network-based fuzzy inference system(ANFIS),and a multi-objective particle swarm optimizer(MOPSO)to optimize the rigid tapping parameters and minimize the synchronization errors and cycle times of computer numerical control(CNC)machines.First,rigid tapping parameters and uniform(including 41-level and 19-level)layouts were adopted to collect representative data for modeling.Next,ANFIS was used to build the model for the collected 41-level and 19-level uniform layout experiment data.In tapping center machines,the synchronization errors and cycle times are important consid-erations,so these two objects were used to build the ANFIS models.Then,a MOPSO algorithm was used to search for the optimal parameter combinations for the two ANFIS models simultaneously.The experimental results showed that the proposed method obtains suitable parameter values and optimal parameter combinations compared with the nonsystematic method.Additionally,the optimal parameter combination was used to optimize existing CNC tools during the commissioning process.Adjusting the proportional and integral gains of the spindle could improve resistance to deformation during rigid tapping.The posi-tion gain and prefeedback coefficient can reduce the synchronization errors significantly,and the acceleration and deceleration times of the spindle affect both the machining time and synchronization errors.The proposed method can quickly and accurately minimize synchronization errors from 107 to 19.5 pulses as well as the processing time from 3,600 to 3,248 ms;it can also shorten the machining time significantly and reduce simultaneous errors to improve tapping yield,there-by helping factories achieve carbon reduction.
基金supported by the National High Technology Research and Development Program of China(863 Program, Grant No.2002AA602012-2)
文摘The underwater tapping machine is composed of a center bit, a tapping cutter, a seal box, a main drive box, a boring bar assembly, a envelop, a gear case, a counter and so on. The drive system in underwater tapping machine consists of a worm drive, a gear drive system and a screw drive. The worm drive is in the main drive box. The worm is connected with a hydraulic motor and driven by the hydraulic motor. The gear drive system is a combined gear train which is the combinations of the fixed axes and differential gear train in the gear case. On the one hand, by means of the fixed axes gear trains the turn and power of transmission shaft are transferred to the boring bar and the screw rod, causing differential turn between the boring bar and the screw rod. On the other hand, the turns of the boring bar and the screw rod are transferred to the differential gear train. The differential gear train is used to drive a special counter to count axial travel of the boring bar. The screw drive is composed of a feed screw and a nut on the boring bar. There is the differential turn between the boring bar and the feed screw. By means of the nut, the boring bar can feed automatically. With the movement of the sliding gear 7 in the gear case, the designed drive system can also be provided with the ability of fast forward and fast backward movement of the boring bar in its idle motion, resulting in the increase of the tapping efficiency.
文摘为进一步提高有载分接开关(on-load tap changer,OLTC)机械状态监测的准确性,文中基于优化品质因数可调小波变换(tunable quality wavelet transform,TQWT)对OLTC切换过程中的振动信号进行了分析。即使用人工鱼群算法(artificial fish swarm algorithm,AFSA)基于分解余量与整体正交系数研究了TQWT的优化分解方法,计算得到了OLTC振动信号的多个子序列,构建了基于优化孪生支持向量机(twin support vector machine,TWSVM)的OLTC机械故障诊断模型。对某CM型OLTC正常与典型机械故障下振动信号的分析结果表明,所提优化TQWT分解方法有效提高了OLTC振动信号分解结果的准确性。相对于其他诊断模型,所构建AFSA-TWSVM的OLTC机械故障诊断模型分类效果好且收敛速度更快。
