To promote sustainability, it has become increasingly vital to properly account material and energy flows in industrial production processes. Therefore, a generic process-level input-output （IO） model was developed ...To promote sustainability, it has become increasingly vital to properly account material and energy flows in industrial production processes. Therefore, a generic process-level input-output （IO） model was developed to provide an integrated energy （material） accounting and analysis approach for industrial production processes. By extending the existing processlevel IO models, the production, usage, export and loss of by-products were explicitly considered in the proposed IO model. Moreover, the by-products allocation procedures were incorporated into the proposed IO model to reflect individual contributions of products to energy consumption. Finally, the proposed model enabled calculating embodied energy of main products and total energy consumption under hierarchical accounting scope. Plant managers, energy management consultants, governmental officials and academic researchers could use this input-output model to account material and energy flows, thus calculating energy consumption indicators of a production process with their specific system boundary requirements. The accounting results could be further used for energy labeling, identifying bottlenecks of production activities, evaluating industrial symbiosis effects, improving materials and energy utilization efficiency, etc. The model could also be used as a planning tool to determine the effect that a particular change of technology and supply chains may have on the industrial production processes. The proposed model was tested and applied in a real integrated steel mill, which also provided the reference results for related researches. At last, some concepts, computational issues and limi- tations of the proposed model were discussed.展开更多
针对传统的自回归模型和自回归移动平均模型在齿轮箱早期异常检测中准确性不足的问题,采用有源自回归模型(autoregressive with extra inputs model,ARX)和统计过程控制相结合的方法进行齿轮箱早期异常检测。首先,对原始振动数据进行时...针对传统的自回归模型和自回归移动平均模型在齿轮箱早期异常检测中准确性不足的问题,采用有源自回归模型(autoregressive with extra inputs model,ARX)和统计过程控制相结合的方法进行齿轮箱早期异常检测。首先,对原始振动数据进行时域同步平均降噪处理;然后考虑到负载变化对输出信号的影响,提取信号的包络表征负载变化信息并作为模型的输入结合赤池信息准则(akaike information criterion,AIC)和最小二乘法建立模型;最后分别采用统计过程控制、支持向量数据描述(support vector data description,SVDD)、核主成分分析(kernel principal component analysis,KPCA)对残差数据的均方根值进行处理。结果表明,ARX模型结合指数加权移动平均(exponential weighed moving average,EWMA)控制图在第44个文件发现早期异常,相比于自回归模型、自回归移动平均模型、SVDD和KPCA分别提前11、6个、10和11个文件检测出异常,从而验证了该方法的可行性和有效性,对齿轮箱早期异常检测有重要意义。展开更多
The in-process changes of weld nugget growth during the Resistance Spot Welding were investigated based on the resistance of input electrical impedance. To compute the time varying resistance of input electrical imped...The in-process changes of weld nugget growth during the Resistance Spot Welding were investigated based on the resistance of input electrical impedance. To compute the time varying resistance of input electrical impedance, the welding voltage and current signals are measured simultaneously and then converted into complex-valued signals by using Hilbert transform. Comparing with the dynamic contact resistance as reported in literature, it showed that the time varying resistance of input electrical impedance can be accurately correlated with the physical changes of weld nugget growth. Therefore, it can be used to characterize the in-process changes of weld nugget growth. Several new findings were reported based on the investigation of spot welds under no weld, with and without weld expulsion conditions.展开更多
文摘To promote sustainability, it has become increasingly vital to properly account material and energy flows in industrial production processes. Therefore, a generic process-level input-output （IO） model was developed to provide an integrated energy （material） accounting and analysis approach for industrial production processes. By extending the existing processlevel IO models, the production, usage, export and loss of by-products were explicitly considered in the proposed IO model. Moreover, the by-products allocation procedures were incorporated into the proposed IO model to reflect individual contributions of products to energy consumption. Finally, the proposed model enabled calculating embodied energy of main products and total energy consumption under hierarchical accounting scope. Plant managers, energy management consultants, governmental officials and academic researchers could use this input-output model to account material and energy flows, thus calculating energy consumption indicators of a production process with their specific system boundary requirements. The accounting results could be further used for energy labeling, identifying bottlenecks of production activities, evaluating industrial symbiosis effects, improving materials and energy utilization efficiency, etc. The model could also be used as a planning tool to determine the effect that a particular change of technology and supply chains may have on the industrial production processes. The proposed model was tested and applied in a real integrated steel mill, which also provided the reference results for related researches. At last, some concepts, computational issues and limi- tations of the proposed model were discussed.
文摘针对传统的自回归模型和自回归移动平均模型在齿轮箱早期异常检测中准确性不足的问题,采用有源自回归模型(autoregressive with extra inputs model,ARX)和统计过程控制相结合的方法进行齿轮箱早期异常检测。首先,对原始振动数据进行时域同步平均降噪处理;然后考虑到负载变化对输出信号的影响,提取信号的包络表征负载变化信息并作为模型的输入结合赤池信息准则(akaike information criterion,AIC)和最小二乘法建立模型;最后分别采用统计过程控制、支持向量数据描述(support vector data description,SVDD)、核主成分分析(kernel principal component analysis,KPCA)对残差数据的均方根值进行处理。结果表明,ARX模型结合指数加权移动平均(exponential weighed moving average,EWMA)控制图在第44个文件发现早期异常,相比于自回归模型、自回归移动平均模型、SVDD和KPCA分别提前11、6个、10和11个文件检测出异常,从而验证了该方法的可行性和有效性,对齿轮箱早期异常检测有重要意义。
文摘The in-process changes of weld nugget growth during the Resistance Spot Welding were investigated based on the resistance of input electrical impedance. To compute the time varying resistance of input electrical impedance, the welding voltage and current signals are measured simultaneously and then converted into complex-valued signals by using Hilbert transform. Comparing with the dynamic contact resistance as reported in literature, it showed that the time varying resistance of input electrical impedance can be accurately correlated with the physical changes of weld nugget growth. Therefore, it can be used to characterize the in-process changes of weld nugget growth. Several new findings were reported based on the investigation of spot welds under no weld, with and without weld expulsion conditions.
