安全、健康和环境

2020, v.20(09) 20-23

[打印本页] [关闭]
本期目录(Current Issue) | 过刊浏览(Past Issue) | 高级检索(Advanced Search)

LDAR数据统计分析方法研究及应用
Research on LDAR Data Statistical Analysis Method and its Application

丁德武;
Ding Dewu;The Key Laboratory of Safety and Control for Chemicals,SINOPEC Research Institute of Safety Engineering;

摘要(Abstract):

研究了适用于泄漏检测与修复(LDAR)密封点台账、检测数据、泄漏数据、VOCs排放量等不同数据类型和分析目标的LDAR数据统计分析方法。基于分类和聚类方法,对某企业2015-2018年5 088 480个检测值的区间分布进行统计分析,分别对比阀门、法兰、连接件等10种密封类型检测值区间分布情况,同时对泄漏率和修复率进行分析。结果表明,除搅拌器密封无泄漏点外,阀门、法兰、连接件等密封类型的泄漏点检测值主要分布在500μmol/mol≤SV<2 000μmol/mol和2 000μmol/mol≤SV <5 000μmol/mol区间;泄漏率较高的密封类型分别为泵1.81%、采样口0.97%、开口管线0.79%,其次是阀门0.37%,压缩机密封0.31%;泄漏点修复率逐年提高,维修效果显著。
Leak detection and repair(LDAR) has various types of data such as seal point ledger,detection data,leakage data and VOCs emissions. Data statistical analysis method was studied for above data types and different analysis targets. Based on the classification and clustering method,the interval distribution of 5088480 detection values of an enterprise from 2015 to 2018 was statistically analyzed. The interval distribution of detection values of 10 sealing types,such as valves,flanges and connectors,were compared. The leakage rate and repair rate were analyzed. The results showed that the detection values of leakage points of valves,flanges and connectors were mainly distributed in the range of 500 μ mol/mol ≤SV < 2 000 μ mol/mol and 2 000 μ mol/mol ≤SV < 5 000. The sealing types with higher leakage rate were pump(1. 81%),sampling port(0. 97%)and open pipeline(0. 79%),following by valve(0. 37%) and compressor seal(0. 31%). The repair rate of leakage point was improved year by year and the maintenance effect was remarkable.

关键词(KeyWords): 泄漏检测与修复;LDAR数据;数据挖掘;统计分析;区间分布
leak detection and repair;LDAR data;data mining;statistical analysis;interval distribution

Abstract:

Keywords:

基金项目(Foundation):

作者(Author): 丁德武;
Ding Dewu;The Key Laboratory of Safety and Control for Chemicals,SINOPEC Research Institute of Safety Engineering;

Email:

DOI:

扩展功能
本文信息
服务与反馈
本文关键词相关文章
本文作者相关文章
中国知网
分享