智能系统学报
智能繫統學報
지능계통학보
CAAI TRANSACTIONS ON INTELLIGENT SYSTEMS
2015年
4期
599-606
,共8页
李鑫%张利剑%何银铜
李鑫%張利劍%何銀銅
리흠%장리검%하은동
金属橡胶%卡箍%管道隔振%隔振传递率%记忆恢复力%非线性刚度%飞行剖面%改进粒子群算法
金屬橡膠%卡箍%管道隔振%隔振傳遞率%記憶恢複力%非線性剛度%飛行剖麵%改進粒子群算法
금속상효%잡고%관도격진%격진전체솔%기억회복력%비선성강도%비행부면%개진입자군산법
metal rubber%clamp%vibration isolation%isolation rate%memory restoring force%nonlinear stiffness%flight profile%modified particle swarm optimization
因金属橡胶干摩擦特性具有高能量耗散能力，将金属橡胶材料置入液压管道卡箍中作为隔振材料。建立了考虑三次非线性刚度以及干摩擦记忆恢复力的振动方程，并得到其隔振传递率模型。分析了非线性刚度、记忆恢复力对隔振传递率的影响，并与试验结果做了对比，发现两者基本一致。通过分析某型号飞机的飞行剖面，得到不同工况下的转速比例以及相对应的隔振传递率的加权和；针对传统粒子群的弊端，改进了学习因子的变化规律并引入模拟退火算法判断最优点更新，通过仿真验证了其具有较快收敛速度并避免陷入局部最优，同时得到了金属橡胶卡箍最优参数以及最小隔振传递率。
因金屬橡膠榦摩抆特性具有高能量耗散能力，將金屬橡膠材料置入液壓管道卡箍中作為隔振材料。建立瞭攷慮三次非線性剛度以及榦摩抆記憶恢複力的振動方程，併得到其隔振傳遞率模型。分析瞭非線性剛度、記憶恢複力對隔振傳遞率的影響，併與試驗結果做瞭對比，髮現兩者基本一緻。通過分析某型號飛機的飛行剖麵，得到不同工況下的轉速比例以及相對應的隔振傳遞率的加權和；針對傳統粒子群的弊耑，改進瞭學習因子的變化規律併引入模擬退火算法判斷最優點更新，通過倣真驗證瞭其具有較快收斂速度併避免陷入跼部最優，同時得到瞭金屬橡膠卡箍最優參數以及最小隔振傳遞率。
인금속상효간마찰특성구유고능량모산능력，장금속상효재료치입액압관도잡고중작위격진재료。건립료고필삼차비선성강도이급간마찰기억회복력적진동방정，병득도기격진전체솔모형。분석료비선성강도、기억회복력대격진전체솔적영향，병여시험결과주료대비，발현량자기본일치。통과분석모형호비궤적비행부면，득도불동공황하적전속비례이급상대응적격진전체솔적가권화；침대전통입자군적폐단，개진료학습인자적변화규률병인입모의퇴화산법판단최우점경신，통과방진험증료기구유교쾌수렴속도병피면함입국부최우，동시득도료금속상효잡고최우삼수이급최소격진전체솔。
Metal rubber has a significant energy dissipation property due to its dry friction characteristic.In this pa-per, the test system and the metal rubber was placed in the clamp of hydraulic pipe as the vibration isolation mate-rial.The vibration equations of pipe and clamp considering the cubic nonlinear rigidity and memory restoring force of dry friction were established.The model of vibration isolation ratio of the metal rubber clamp was also obtained. The influence of cubic nonlinear stiffness and memory restoring force on the ratio was analyzed and then compared with the experiment.The results were consistent.The speed ratio under different working conditions and the weigh-ted sum of vibration isolation with different characteristic frequencies were obtained based on the flight profile of a certain type of large aircraft and the weighted sum was set as the objective function.Considering the disadvantages of the traditional particle swarm optimization ( PSO) , the change rule of learning factor was changed and the simu-lated annealing algorithm was introduced to judge the updating of optimal point.The simulation validated that the improved algorithm has faster convergence rate and avoids trapping into local optimum.However,the minimum vi-bration isolation transferring rate and the optimal parameters of the metal rubber clamp were received.
