水利学报
水利學報
수리학보
2014年
6期
735-741
,共7页
江思珉%张亚力%周念清%赵姗
江思珉%張亞力%週唸清%趙姍
강사민%장아력%주념청%조산
污染源识别%模糊对比%单纯形法%卡尔曼滤波
汙染源識彆%模糊對比%單純形法%卡爾曼濾波
오염원식별%모호대비%단순형법%잡이만려파
contaminant plume identification%fuzzy comparison%simplex method%Kalman filter
地下水污染源位置与强度的确定有助于提高地下水污染治理和修复的效果。本文在场地信息不确定的前提下,基于卡尔曼滤波技术与单纯形法提出一种地下水污染源识别的新方法。该方法利用卡尔曼滤波技术连续作用采样点来估计复合污染羽与误差协方差矩阵,进而利用误差协方差矩阵进行新采样点的选择;模糊集被用来进行污染羽的表示,通过复合污染羽与单个污染羽的形态对比以确定污染源位置;在进行污染源位置反演时,嵌入单纯形法以进行污染源强度的同步反演。算例研究表明,该方法在判断污染源位置时考虑了污染羽的整体形态,从而降低了场地局部信息不确定对于污染源识别结果的影响,并能够通过合理的采样点的选择,正确地识别出污染源位置与强度,反演结果具有较高的可靠性。
地下水汙染源位置與彊度的確定有助于提高地下水汙染治理和脩複的效果。本文在場地信息不確定的前提下,基于卡爾曼濾波技術與單純形法提齣一種地下水汙染源識彆的新方法。該方法利用卡爾曼濾波技術連續作用採樣點來估計複閤汙染羽與誤差協方差矩陣,進而利用誤差協方差矩陣進行新採樣點的選擇;模糊集被用來進行汙染羽的錶示,通過複閤汙染羽與單箇汙染羽的形態對比以確定汙染源位置;在進行汙染源位置反縯時,嵌入單純形法以進行汙染源彊度的同步反縯。算例研究錶明,該方法在判斷汙染源位置時攷慮瞭汙染羽的整體形態,從而降低瞭場地跼部信息不確定對于汙染源識彆結果的影響,併能夠通過閤理的採樣點的選擇,正確地識彆齣汙染源位置與彊度,反縯結果具有較高的可靠性。
지하수오염원위치여강도적학정유조우제고지하수오염치리화수복적효과。본문재장지신식불학정적전제하,기우잡이만려파기술여단순형법제출일충지하수오염원식별적신방법。해방법이용잡이만려파기술련속작용채양점래고계복합오염우여오차협방차구진,진이이용오차협방차구진진행신채양점적선택;모호집피용래진행오염우적표시,통과복합오염우여단개오염우적형태대비이학정오염원위치;재진행오염원위치반연시,감입단순형법이진행오염원강도적동보반연。산례연구표명,해방법재판단오염원위치시고필료오염우적정체형태,종이강저료장지국부신식불학정대우오염원식별결과적영향,병능구통과합리적채양점적선택,정학지식별출오염원위치여강도,반연결과구유교고적가고성。
Identification of the location and intensity of groundwater pollution source is contributive to the effect of pollution remediation. In this study, a new approach to identify the groundwater pollution source is proposed based on the Kalman filtering and simplex method with the uncertainty of fields. The general pollution plume and covariance matrix of error are predicted through continuous sampling with Kalman filter?ing. Afterwards, the sampling points are selected in combination with the covariance matrix, to reduce the uncertainty as far as possible. The pollution plume is represented by fuzzy set, and the pollution location is identified by the comparison of general and single plume. The simplex method is embedded in the inver?sion of source location to reverse source intensity. The case study shows that this approach give sufficient consideration to the overall shape of pollutants in order to reduce the influence of the uncertainty of local information on the recognition results, and the approach is an effective way to identify the location and in?tensity of pollution source through the reasonable sampling points, providing the inversion with higher reli?ability.