双运带式输送机的模糊可靠性优化设计  

The optimal design of fuzzy reliability on double transporting belt conveyer based on neural network algorithm

作　　者：李阳星[1] 周广林[1] 

机构地区：[1]黑龙江科技学院,哈尔滨150027

出　　处：《机械设计与制造》2006年第4期29-31,共3页Machinery Design & Manufacture

摘　　要：带式输送机应该是技术合理,整机成本和运行费用低。一般输送带的成本约占整机成本的50%,电费为主要运行费用。所以这里以双运带式输送机牵引电机的功率最小为目标函数,以输送带运行速度、输送带宽度、输送带最小张力点张力、托辊间距为设计变量,考虑影响约束边界的模糊性、输送带强度的模糊性和输送带计算应力的随机性,建立双运带式输送机主参数的模糊可靠性优化设计的数学模型,应用Hopfield型神经网络算法对模型进行求解。结果表明:Hopfield型神经网络算法应用于双运带式输送机主参数的模糊可靠性优化设计十分有效。The belt conveyer＇ s technology should be rational, complete machine cost and operating expenses be low. The cost of the general conveyer belt accounts for 50% of complete machine cost; is the main operating expenses are electric expense. So it takes the minimum driving power of double transporting belt conveyer drawing electrical machine as the goal function, with the operating speed of conveying belt, its width, its minimum tension, interval of roller as variables of designing, considers the fuzziness of influencing restraining border and intensity of conveying belt, and the randomness of the gauge stress of conveying belt, sets up mathematical models of the fuzzy reliability optimal design on the main parameter of conveyer, uses the Hopfield neural network algorithm to ask solving to the model. The result shows： it is effective that we apply Hopfield neural network algorithm to the fuzzy reliability optimal design on the main parameter of conveyer.

关 键 词：带式输送机 HOPFIELD型神经网络 模糊理论 可靠性优化 

分 类 号：O224[理学—运筹学与控制论]