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In metal cutting industry it is a common practice to search for optimal combination of cutting parameters in order to maximize the tool life for a fixed minimum value of material removal rate(MRR). After the advent of high-speed milling(HSM) pro cess, lots of experimental and theoretical researches have been done for this purpose which mainly emphasized on the optimization of the cutting parameters. It is highly beneficial to convert raw data into a comprehensive knowledge-based expert system using fuzzy logic as the reasoning mechanism. In this paper an attempt has been presented for the extraction of the rules from fuzzy neural network(FNN) so as to have the most effective knowledge-base for given set of data. Experiments were conducted to determine the best values of cutting speeds that can maximize tool life for different combinations of input parameters. A fuzzy neural network was constructed based on the fuzzification of input parameters and the cutting speed. After training process, raw rule sets were extracted and a rule pruning approach was proposed to obtain concise linguistic rules. The estimation process with fuzzy inference showed that the optimized combination of fuzzy rules provided the estimation error of only 6.34 m/min as compared to 314 m/min of that of randomized combination of rules.  相似文献
基于分辨矩阵基元的不完备故障诊断系统的规则提取技术   总被引:1,自引:0,他引:1  
在故障诊断中,从不完备数据中获取规则要比从完备数据中获取规则困难,提出一种直接从不完备数据中获取最优广义诊断决策规则的粗糙集方法.给出分辨矩阵基元的定义,研究分辨矩阵基元的性质以简化分辨矩阵基元的计算过程;根据分辨矩阵基元的定义,给出不完备故障诊断决策表中面向对象的分辨矩阵的定义,并以此来构造面向对象的分辨函数,结合命题逻辑中的基本等价式,如分配律和吸收率等,给出一种计算最小面向对象约简的方法,实现不完备故障诊断决策表中面向对象的约简计算和最优广义故障诊断规则的获取.结合电力系统操作点的安全状态诊断实例给出所提出的方法在工程实践中的应用步骤,并证明该方法的有效性.  相似文献
吕韶  谢先明 《现代机械》2006,(3):72-74,76
从属性约简后的数据集中提取规则实质上就是决策规则的约简计算,一般利用启发信息进行约简计算。提出了一种新的基于差别矩阵的决策表规则提取算法,首先从差别矩阵得到差别集,结合置信度要求得到候选规则集,然后开始提取规则并逐步调整候选规则集,最终提取出决策规则。该算法避免了规则提取过程中条件属性挑选和扩展的计算,并能够快速提取出决策表中存在的最简决策规则,计算实例表明其具有决策规则提取的工程实用性。  相似文献
给出使机器人处于最优运动状态的运动参数。采用模糊神经网络结合常规PD控制器的方法来进行机器人的运动控制,提出了提取模糊规则的方法。实验结果表明该控制算法结构简单,具有实时性好、精度高、鲁棒性强等特点。  相似文献
DeLima PG  Yen GG 《ISA transactions》2005,44(2):315-327
Autonomous temporal linguistic rule extraction is an application of growing interest for its relevance to both decision support systems and fuzzy controllers. In the presented work, rules are evaluated using three qualitative metrics based on their representation on the truth space diagram. Performance metrics are then treated as competing objectives and the multiple objective evolutionary algorithm is used to search for an optimal set of nondominant rules. Novel techniques for data pre-processing and rule set post-processing are designed that deal directly with the delays involved in dynamic systems. Data collected from a simulated hot and cold water mixer are used to validate the proposed procedure.  相似文献
Forging is a cost-effective way to produce net-shape or near-net-shape components. Forged components are used throughout the manufacturing sector in many different applications. Owing to the lack of an accurate process model, modern forging operations still largely rely on operator skills and experience. The expertise of skilled operators can help to develop a forging process model. However, these operators’ expert knowledge is accumulated through years of hands-on experience and is often biased towards their own heuristic. It is well known that accurate acquisition of this type of knowledge is challenging and time-consuming. In this paper, an innovative approach is developed to acquire forging process knowledge automatically by combining learning ability of the neural networks with the structured knowledge representation of rule-based systems. The approach is applied to the classification of process methods used in a type of impression-die forging, namely, drop hammer forming. Specifically, process data from an aerospace company’s production facility are collected. The data are processed and then used to train a back-propagation neural network. By analysing the connections and weights of the trained neural network, concise and intelligible rules are extracted. These rules can be used to allow a clearer specification of the drop hammer forming process plan and to shorten learning curves for novice operators.    相似文献
针对大型决策表规则提取中分辨矩阵级数高,计算复杂和低效的问题,提出了一种分辨矩阵的降级算法。算法以决策等价类为对象,构建简化分辨矩阵,其中每个元素都是由两个决策等价类构成的子分辨矩阵,与传统分辨矩阵相比,简化分辨矩阵的级数低、规模小,从而简化了属性约简,效率高;提取规则时根据需要灵活设置可信度,按照可信度值提取有效规则,使算法对不一致决策表也具有较好的适应性。实例计算表明算法清晰、简捷、有效。  相似文献
针对航空发动机磨损故障诊断自动化及智能化程度不高的问题,提出一种基于油液数据挖掘的航空发动机磨损故障诊断知识获取方法。该方法利用自组织神经网络对原始多维特征数据进行特征融合,得到融合值;利用Parzen窗法制定融合值的界限值,将样本划分为正常、警告和异常3种状态;利用Weka软件对油液数据进行规则提取。该方法能够从油液光谱数据中识别出不同磨损状态信息,并提取出知识规则用于构建航空发动机磨损诊断系统的知识库,实现了基于润滑油光谱磨损数据的航空发动机故障诊断的自动化与智能化。应用某型飞机发动机实际油液光谱数据对提出的磨损故障诊断知识获取方法进行验证,结果表明:经特征融合得到的融合值能够准确反映航空发动机的劣化趋势;利用融合值的界限值划分样本状态,再进行规则提取时具有很高的识别率。  相似文献
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