表面技术
錶麵技術
표면기술
Surface Technology
2015年
10期
86-92
,共7页
亚激光瞬间熔%再制造%抗拉强度%优化算法%响应曲面法%BP神经网络-模拟退火算法
亞激光瞬間鎔%再製造%抗拉彊度%優化算法%響應麯麵法%BP神經網絡-模擬退火算法
아격광순간용%재제조%항랍강도%우화산법%향응곡면법%BP신경망락-모의퇴화산법
sub laser instant cladding%remanufacture%tensile strength%optimization algorithm%response surface methodolo-gy%back propagation neural network-integrated simulated annealing algorithm
目的：探讨不同优化算法下HT250基体再制造工艺参数的优化效果。方法利用Taguchi试验设计方法设计4因子3水平共18组试验,通过亚激光瞬间熔技术修复HT250基体的表面缺陷,利用响应曲面法( RSM)和BP神经网络-模拟退火算法( BPNN/SAA)对其修复过程的工艺参数进行优化,分析输入功率P,单次修复时间t,速度v和保护气体流量G等4个因素对修复后试样抗拉强度的影响,并对不同优化算法的优化效果、准确性和稳定性进行探讨。结果 HT250基体修复过程中最优工艺参数为：输入功率2960 W,持续时间0.62 s,速度6 mm/s,气体流量3 L/min。在此参数下所获取的修复试样最大抗拉强度为230.52 MPa。结论抗拉强度受输入功率P和单次修复时间t影响显著,对其他元素呈弱依赖性。 BP神经网络-模拟退火算法较响应曲面法更适合对亚激光瞬间熔的工艺参数进行优化。
目的：探討不同優化算法下HT250基體再製造工藝參數的優化效果。方法利用Taguchi試驗設計方法設計4因子3水平共18組試驗,通過亞激光瞬間鎔技術脩複HT250基體的錶麵缺陷,利用響應麯麵法( RSM)和BP神經網絡-模擬退火算法( BPNN/SAA)對其脩複過程的工藝參數進行優化,分析輸入功率P,單次脩複時間t,速度v和保護氣體流量G等4箇因素對脩複後試樣抗拉彊度的影響,併對不同優化算法的優化效果、準確性和穩定性進行探討。結果 HT250基體脩複過程中最優工藝參數為：輸入功率2960 W,持續時間0.62 s,速度6 mm/s,氣體流量3 L/min。在此參數下所穫取的脩複試樣最大抗拉彊度為230.52 MPa。結論抗拉彊度受輸入功率P和單次脩複時間t影響顯著,對其他元素呈弱依賴性。 BP神經網絡-模擬退火算法較響應麯麵法更適閤對亞激光瞬間鎔的工藝參數進行優化。
목적：탐토불동우화산법하HT250기체재제조공예삼수적우화효과。방법이용Taguchi시험설계방법설계4인자3수평공18조시험,통과아격광순간용기술수복HT250기체적표면결함,이용향응곡면법( RSM)화BP신경망락-모의퇴화산법( BPNN/SAA)대기수복과정적공예삼수진행우화,분석수입공솔P,단차수복시간t,속도v화보호기체류량G등4개인소대수복후시양항랍강도적영향,병대불동우화산법적우화효과、준학성화은정성진행탐토。결과 HT250기체수복과정중최우공예삼수위：수입공솔2960 W,지속시간0.62 s,속도6 mm/s,기체류량3 L/min。재차삼수하소획취적수복시양최대항랍강도위230.52 MPa。결론항랍강도수수입공솔P화단차수복시간t영향현저,대기타원소정약의뢰성。 BP신경망락-모의퇴화산법교향응곡면법경괄합대아격광순간용적공예삼수진행우화。
Objective To investigate the optimization effect of the remanufacturing process parameters of the HT250 matrix un-der different optimization algorithms. Methods Experiments were designed using a factorial design based on a Taguchi L18 orthogo-nal array. The surface defects of HT250 substrate were repaired by sub laser instant cladding technology, and a hybrid method that included the response surface methodology ( RSM)-back propagation neural network ( BPNN)-integrated simulated annealing algo-rithm ( SAA) was proposed to search for an optimal parameter setting of the remanufactured HT250 matrix, and the effects of input power, processing time, velocity and gas flow on the tensile strength of the remanufactured sample were also analyzed in detail. In addition, the optimization results, stability and veracity were analyzed to compare the results of BPNN integrated SAA with that of the RSM approach. Results The optimal remanufactured HT250 matrix conditions were input power of 2960 W, processing time of 0. 6 s, speed of 6 mm/s, gas flow of 3 L/min. The maximum tensile strength of the remanufactured sample under these conditions was 230. 52 MPa. Conclusion The results showed that the tensile strength was significantly influenced by the input power P and single repair time t, while the influences of other factors were weak. The BPNN/SAA method was more effective than RSM for the optimization of remanufactured HT250 matrix.
