【作者】 杜义贤；

【导师】 田启华；

【作者基本信息】 三峡大学 ， 机械设计及理论， 2004， 硕士

【摘要】 本文将评价决策基本原理和理论应用于机械产品性能评价，总结出一般机械产品性能评价的过程，提出了新的机械产品性能评价方法，使机械产品性能评价分析更准确可靠。主要的研究内容包括如下几个方面： 在确定评价指标体系时，根据数理统计方法，利用相关公式消除指标之间的相关性，减小了指标之间重叠性的影响。 在总结指标标准化方法的基础上，将指标的标准化分为四种情况，这样，既简化了指标的分类情况，又满足了机械产品性能评价的实际情况。 研究了熵权与模糊综合评判法在机械产品性能评价中应用的原理和方法，利用熵理论确定模糊评价的客观权重，结合专家权重，利用相关集结公式，得到符合实际情况的综合权重。并在对产品性能模糊评价的基础上，得出了产品的性能评价结果排序。 根据机械产品性能评价实际情况，改造一股的神经网络，得到与实际情况相符的模糊神经网络。网络中采用梯形函数的四元组形式构造模糊隶属函数，并用隶属函数的端点值和中间值作为样本，用改进的反向传播算法训练网络，得到与待评价产品情况相符合的权重值。 本文按上述理论方法，开发了机械产品性能辅助评价系统。该系统能够完成对产品性能的常规评价和模糊评价，帮助决策者进行评价分析。 最后，利用本文的理论方法，对ZL50系列挖掘机进行了实例分析，表明在进行机械产品性能评价时，本文方法的有效性和准确性。更多还原

【Abstract】 This thesis applies the methods of evaluation in the field of mechanical engineering and summarizes the procedure of performance evaluation for mechanical products. New evaluation approaches are proposed, which make the evaluation exacter and more dependable. In this thesis, the following key problems are studied.In order to minimize the correlation among all indicators, based on mathematic statistic methods, the synthetic function of every indication is given.Based on the summarization of standardization for indicators, we put the methods of summarization into four classes. In this way, not only the classes of indicators are predigested, but also the factual needs of performance evaluation for mechanical products are meted.The theory and method of application of entropy fuzzy comprehensive evaluation method in performance evaluation of mechanical products is studied. On the basis of entropy, the objective coefficient can be gotten. The compositive coefficient can be gained by combining the subjective coefficient and the objective coefficient. From the results of fuzzy comprehensive evaluation for performance evaluation for mechanical products, we can get the gradation of the mechanical products’ performance.According to the actual circumstance of performance evaluation for mechanical products, the general neural network is reformed. Therefore, we construct the fuzzy neural network. This paper expresses membership function in the network by trapezium formulae .The indicators are fuzzed using the membership function .The network is trained using the top points and midpoint of membership function and the improved back propagation algorithm. Then we can get the adaptive network coefficients.The software system of performance evaluation for mechanical products is developed, which can complete the routine and fuzzy performance. Those can help the decisionmakers to get the correct conclusions.Finally, an example for loading machines of model ZL50 is then presented to verify these methods in this thesis.更多还原