Plant-wide Process Operating Performance Assessment and Non-optimal Cause Identification Based on Hierarchical Multi-block Structure
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摘要: 过程运行状态评价是指在安全生产的前提下,对过程运行性能优劣程度做出评判,并对非优运行状态追溯原因,以指导操作人员进行生产调整.针对含不确定性的流程工业过程运行状态评价问题,本文提出分层分块评价结构.同时,考虑到实际生产过程中大量存在的不确定性信息,采用粗糙集对每个子模型进行建模,建立过程变量、工艺指标与综合评价指标间的关系.最后,将所提方法应用于一个金湿法冶金过程中,验证所提方法有效性.Abstract: Process operating performance assessment may determine the operating optimality degree and identify the cause of non-optimal operating performance, thus providing guidance for production adjustment. For the plant-wide process uncertainty, a novel hierarchical multi-block assessment framework is proposed in this paper. Due to the widely existing uncertainties in the plant-wide processes, the rough set is utilized to build an assessment model of each sub-block. The relations between process variables, technical indices and the comprehensive assessment index are extracted. Finally, the proposed method is applied to a gold hydrometallurgy process to illustrate its validity and feasibility.1) 本文责任编委 苏宏业
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表 1 各层评价指标列表
Table 1 The assessment indices for each level
序号 指标名称 位置 1 一次浸出率 一次浸出单元层 2 一浸能耗 一次浸出单元层 3 一浸物耗 一次浸出单元层 4 二次浸出率 二次浸出单元层 5 二浸能耗 二次浸出单元层 6 二浸物耗 二次浸出单元层 7 一次洗涤率 一次洗涤单元层 8 二次洗涤率 二次洗涤单元层 9 总浸出率 浸出功能区层 10 总浸出能耗 浸出功能区层 11 总浸出物耗 浸出功能区层 12 总洗涤率 总洗涤率 13 置换率 置换功能区层 14 置换能耗 置换功能区层 15 置换物耗 置换功能区层 16 CEI 全流程层 表 2 湿法冶金过程变量表
Table 2 The variables of the gold
序号 指标名称 位置 1 矿石来料量 生产条件 2 初始金品位 生产条件 3 矿石平均粒径 生产条件 4 调浆后矿浆浓度 一次浸出单元 5 调浆后矿浆流量 一次浸出单元 6 一浸前调浆水量 一次浸出单元 7 一浸NaCN添加量 一次浸出单元 8 一浸后金氰离子浓度 一次浸出单元 9 一浸空气流量 一次浸出单元 10 一浸溶氧量 一次浸出单元 11 一浸矿浆密度 一次浸出单元 12 一次浸出单元 二次浸出单元 13 二浸前矿浆流量 二次浸出单元 14 二浸前调浆水量 二次浸出单元 15 二浸NaCN添加量 二次浸出单元 16 二浸后金氰离子浓度 二次浸出单元 17 二浸空气流量 二次浸出单元 18 二浸溶氧量 二次浸出单元 19 二浸矿浆密度 二次浸出单元 20 一洗前矿浆浓度 一次压滤洗涤单元 21 一洗后金氰离子浓度 一次压滤洗涤单元 22 一洗后滤液流量 一次压滤洗涤单元 23 一洗后滤液流量 一次压滤洗涤单元 24 二洗前矿浆浓度 二次压滤洗涤单元 25 二洗后金氰离子浓度 二次压滤洗涤单元 26 二洗后滤液流量 二次压滤洗涤单元 27 二洗后滤饼流量 二次压滤洗涤单元 28 脱氧塔1压力 置换功能区 29 流入置换压滤机贵液流量 置换功能区 30 流入置换压滤机贵液金氰离子浓度 置换功能区 31 锌粉添加量 置换功能区 32 锌粉平均粒径 置换功能区 33 贫液流量 置换功能区 34 贫液金氰离子浓度 置换功能区 表 3 RSHMM和RS评价正确率对比(%)
Table 3 The assessment accuracy rate comparison of RSHMM and RS (%)
建模数据总量 RSHMM的评价正确率 RS的评价正确率 1 500 68.0 32.5 3 000 81.7 58.7 6 000 92.3 76.1 12 000 94.1 87.3 15 000 95.3 95.2 -
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