A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps

In the aluminum reduction process, aluminum uoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic ef ciency. Making the decision on the amount of AlF3 addi- tion (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into con- sideration a variety of interrelated functions;in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is dif cult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have dif culty covering these complex causalities. In this work, a data and knowl- edge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy deci- sion trees, which are used to amend the initial structure provided by experts. The state transition algo- rithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA.

A Cell Condition-Sensitive Frequency Segmentation Method Based on the Sub-Band Instantaneous Energy Spectrum of Aluminum Electrolysis Cell Voltage

Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell voltage.In this paper,the frequency segmentation of cell voltage is used as the basis for designing filters to obtain these parameters.Based on the qualitative analysis of the cell voltage,the sub-band instantaneous energy spectrum(SIEP)is first proposed,which is then used to quantitatively represent the characteristics of the designated frequency bands of the cell voltage under various cell conditions.Ultimately,a cell condition-sensitive frequency segmentation method is given.The proposed frequency segmentation method divides the effective frequency band into the[0,0.001]Hz band of lowfrequency signals and the[0.001,0.050]Hz band of low-frequency noise,and subdivides the lowfrequency noise into the[0.001,0.010]Hz band of metal pad abnormal rolling and the[0.01,0.05]Hz band of sub-low-frequency noise.Compared with the instantaneous energy spectrum based on empirical mode decomposition,the SIEP more finely represents the law of energy change with time in any designated frequency band within the effective frequency band of the cell voltage.The proposed frequency segmentation method is more sensitive to cell condition changes and can obtain more elaborate details of online cell condition information,thus providing a more reliable and accurate online basis for cell condition monitoring and control decisions.

Attention-based novel neural network for mixed frequency data

It is a common fact that data(features,characteristics or variables)are collected at different sampling frequencies in some fields such as economic and industry.The existing methods usually either ignore the difference from the different sampling frequencies or hardly take notice of the inherent temporal characteristics in mixed frequency data.The authors propose an innovative dual attention-based neural network for mixed frequency data(MID-DualAtt),in order to utilize the inherent temporal characteristics and select the input characteristics reasonably without losing information.According to the authors’knowledge,this is the first study to use the attention mechanism to process mixed fre-quency data.The MID-DualAtt model uses the frequency alignment method to trans-form the high--frequency variables into observation vectors at low frequency,and more critical input characteristics are selected for the current prediction index by attention mechanism.The temporal characteristics are explored by the encoder-decoder with attention based on long-short-term memory networks(LSTM).The proposed MID-DualAtt has been tested in practical application,and the experimental results show that it has better prediction ability than the compared models.

DECENTRALIZED H_∞ SUBOPTIMAL DESIGN:AN LMI APPROACH

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知识驱动的流程工业智能制造

智能制造是实现我国流程工业高效化、绿色化、高质量发展的必由之路.知识是流程工业智能制造的核心要素,知识驱动的流程工业智能制造是流程制造业发展的新模式.论文从流程制造业中知识的重要性和特点出发,综述了知识研究及应用现状.提出了知识驱动的流程工业智能制造系统框架,探讨了深度知识获取、知识注入和工业知识图谱等关键技术.通过铝电解企业智能决策过程应用案例阐明了以上关键技术在流程工业智能制造系统中的重要作用.最后给出了知识驱动的流程工业智能制造面临的挑战性问题和未来展望.

Double-groove rectangular gratings for high-efficiency wideband vertical coupling in planar-integrated optical systems

A planar-integrated optical system(PIOS)represents powerful optical imaging and information processing techniques and is a potential candidate for the realization of a three-dimensional(3D)integrated optoelectronic intelligent system.Coupling the optical wave carrying information into a planar transparent substrate(typically fused silica)is an essential prerequisite for the realization of such a PIOS.Unlike conventional grating couplers for nano-waveguides on the silicon-on-insulator platform,the grating couplers for PIOS enable to obtain a higher design freedom and to achieve much higher coupling efficiency.By combining the rigorous coupled wave algorithm and simulated annealing optimization algorithm,a highefficiency asymmetric double-groove grating coupler is designed for PIOS.It is indicated that,under the condition of the normal incidence of TE polarization,the diffraction efficiency of the-1st order is over 95%,and its average value is 97.3%and 92.8%in the C and C+L bands.The simulation results indicate that this type of grating coupler has good tolerance and is expected to be applied in optical interconnections,waveguide-based augmented reality glasses,and planar-integrated 3D interconnection optical computing systems.

Visual Perception-Based Fault Diagnosis in Froth Flotation Using Statistical Approaches

Froth flotation is an important mineral concentration technique.Faulty conditions in flotation processes may cause the huge waste of mineral resources and reagents,and consequently,may lead to deterioration in terms of benefits of flotation plants.In this paper,we propose a computer vision-aided fault detection and diagnosis approach for froth flotation.Specifically,a joint Gabor texture feature based on the Copula model is designed to describe froth images;a rejection sampling technique is developed to generate training sets from the quality distribution of real flotation products,and then an isolation forest-based fault detector is learned;and a fault diagnosis model based on spline regression is developed for root cause identification.Simulation experiments conducted on the historical industry data show that the proposed strategy has better performance than the alternative methods.Thereafter,the entire framework has been tested on a lead-zinc flotation plant in China.Experimental results have demonstrated the effectiveness of the proposed method.