专利详细信息

基于独立元相似度的高含硫天然气净化脱硫过程检测方法

文献类型：专利

专利类型：发明专利

是否失效：否

是否授权：否

申请号：CN201410827060.0

申请日：20141225

发明人：邱奎李景哲苏盈盈张莉娅辜小花李太福

申请人：重庆科技学院

申请人地址：401331 重庆市沙坪坝区虎溪大学城重庆科技学院

公开日：20150408

公开号：CN104504271A

代理人：王玉芝

代理机构：11327 北京鸿元知识产权代理有限公司

语　　种：中文

摘　　要：本发明公开了一种基于独立元相似度的高含硫天然气净化脱硫过程检测方法，该方法按如下步骤进行：约简原始特征，确定表征高含硫天然气净化脱硫生产过程工况特征的根本影响因素：初选M个表征高含硫天然气净化脱硫生产过程工况的原始特征组成原变量组X，筛选出在主元方向投影最大的m个独立元，剔除贡献度较小的变量；将所述原变量组X的样本数据重新组合后，形成新样本数据；从新样本数据中选取样本数据作为训练样本，建立高含硫天然气净化脱硫生产过程工况分类模型，模型输出值对应的高含硫天然气净化脱硫生产过程工况类型即为诊断结果。它能够降低模型复杂度，降低维度，提高模型精度，找出影响高含硫天然气净化异常工况的根本原因。

主权项：1.一种基于独立元相似度的高含硫天然气净化脱硫过程检测方法，其特征在于该方法按如下步骤进行：步骤1：约简原始特征，确定表征高含硫天然气净化脱硫生产过程工况特征的根本影响因素：初步选择M个表征高含硫天然气净化脱硫生产过程工况的原始特征组成原变量组X，X＝(x₁,x₂…,x_i,…,x_M)，其中，x₁,x₂,…,x_i,…,x_M为工艺过程参数，采集n组样本，得到X_M×n样本矩阵，利用核独立分量分析计算所述原始变量组X的独立元，将所有独立元按独立元在主元空间特征值由大到小排列，筛选出在主元方向投影最大的m个独立元，各独立元在主元空间特征值须大于或等于预设的某一阈值c，筛选出的m个独立元对应了所有原始特征的最少独立元Bj，j＝1,2,…,m；步骤2：按i＝1，2，…，M的顺序，依次考察原变量组X中每个变量对高含硫天然气净化脱硫生产过程工况的贡献度：2.1将原变量组X中的变量x_i置零，得到一个新的变量组，即待测邻点 $<math> <mrow> <mover> <mi>X</mi> <mo>~</mo> </mover> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> <mo>=</mo> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>x</mi> <mn>2</mn> </msub> <mo>,</mo> <mo>·</mo> <mo>·</mo> <mo>·</mo> <mo>,</mo> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>,</mo> <mn>0</mn> <mo>,</mo> <msub> <mi>x</mi> <mrow> <</p><p class='subject'><strong>关键词：</strong><b class='type_ico_id'></b>天然气净化 <b class='type_ico_id'></b>含硫工况样本数据 <b class='type_ico_id'></b>脱硫原始特征独立元方向投影分类模型模型精度 <b class='type_ico_id'></b>脱硫过程影响因素诊断结果复杂度 <b class='type_ico_id'></b>贡献度筛选出 <b class='type_ico_id'></b>相似度样本检测训练 </p><p class='class'><strong>IPC专利分类号：</strong>G06F19/00(20110101)</p>
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