Settlement Monitoring and Analysis Method for Building Based on Statistical Process Control

WANG Yichen; ZHANG Mingju; LI Liyun; LU Xinyue

doi:10.11936/bjutxb2021060007

Journal of Beijing University of Technology > 2022 > 48(9): 952-960. > DOI: 10.11936/bjutxb2021060007

WANG Yichen, ZHANG Mingju, LI Liyun, LU Xinyue. Settlement Monitoring and Analysis Method for Building Based on Statistical Process Control[J]. Journal of Beijing University of Technology, 2022, 48(9): 952-960. DOI: 10.11936/bjutxb2021060007

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Settlement Monitoring and Analysis Method for Building Based on Statistical Process Control

Key Laboratory of Urban Security and Disaster Engineering, Ministry of Education, Beijing University of Technology, Beijing 100124, China

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Received Date: June 07, 2021
Revised Date: July 17, 2021
Available Online: September 13, 2022

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Abstract

To improve the deficiencies for the current analysis based on the double-control indices, an optimized analysis method for the settlement monitoring of a building was proposed in this study by introducing statistical process control. Whether the settlement variation is controlled stably by employing $\bar{X}-R$ statistical control chart was identified by the method. $\bar{X}-R$ control chart contains R chart was employed to identify the variation of the differential settlement and the $\bar X$ chart was employed to identify the total settlement. Moreover, whether the capacity of settlement control satisfies the corresponding threshold was evaluated by employing process capacity index. On the basis of these, the necessary engineering measures were ascertained. The practical case study of an ancient building adjacent to Beijing Metro Line 8 was introduced to verify the rationality of the method. It demonstrates that introducing SPC can analyze the dynamic randomness of the settlement evolution, and the method can define the reasonable engineering measures as well as verify the efficiency of the measures implemented.

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Settlement Monitoring and Analysis Method for Building Based on Statistical Process Control

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