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Foundation pit slope support stability detection method, medium and system
The invention provides a foundation pit slope supporting stability detection method, medium and system, and belongs to the technical field of foundation pit slope supporting, and the method comprises the steps: continuously collecting vibration signals on a foundation pit slope and a supporting structure, carrying out the preprocessing, time-frequency feature extraction and clustering analysis, obtaining a feature group matched with a pre-training model, and obtaining a feature group matched with the pre-training model; and inputting a pre-trained foundation pit slope support stability evaluation model, and outputting a stability evaluation vector. And calculating an overall stability index, determining a stable state of the foundation pit slope, and marking a potential unstable area. According to the method, a vibration sensor is adopted to continuously monitor a foundation pit slope and a supporting structure, vibration signals covering time domain, frequency domain and time-frequency domain characteristics are obtained, and detection of the stability of the foundation pit slope supporting structure is achieved through a deep learning model. The technical problems that existing detection depends on experience of professionals and is easily influenced by subjective factors, and stress changes in the side slope cannot be effectively monitored are solved.
本发明提供了一种基坑边坡支护稳定性检测方法、介质及系统，属于基坑边坡支护技术领域，包括：通过连续采集基坑边坡和支护结构上的振动信号,经预处理、时频特征提取和聚类分析,获得与预训练模型相匹配的特征组,输入预训练的基坑边坡支护稳定性评估模型,输出稳定性评估向量。进而计算整体稳定性指数,确定基坑边坡的稳定状态,标注潜在的不稳定区域。该方法采用振动传感器对基坑边坡和支护结构进行连续监测,获取涵盖时域、频域和时频域特征的振动信号，利用深度学习模型,实现了对基坑边坡支护结构稳定性的检测。解决了现有检测依赖于专业人员的经验,易受主观因素的影响,且无法对边坡内部的应力变化进行有效监测的技术问题。
Foundation pit slope support stability detection method, medium and system
The invention provides a foundation pit slope supporting stability detection method, medium and system, and belongs to the technical field of foundation pit slope supporting, and the method comprises the steps: continuously collecting vibration signals on a foundation pit slope and a supporting structure, carrying out the preprocessing, time-frequency feature extraction and clustering analysis, obtaining a feature group matched with a pre-training model, and obtaining a feature group matched with the pre-training model; and inputting a pre-trained foundation pit slope support stability evaluation model, and outputting a stability evaluation vector. And calculating an overall stability index, determining a stable state of the foundation pit slope, and marking a potential unstable area. According to the method, a vibration sensor is adopted to continuously monitor a foundation pit slope and a supporting structure, vibration signals covering time domain, frequency domain and time-frequency domain characteristics are obtained, and detection of the stability of the foundation pit slope supporting structure is achieved through a deep learning model. The technical problems that existing detection depends on experience of professionals and is easily influenced by subjective factors, and stress changes in the side slope cannot be effectively monitored are solved.
本发明提供了一种基坑边坡支护稳定性检测方法、介质及系统，属于基坑边坡支护技术领域，包括：通过连续采集基坑边坡和支护结构上的振动信号,经预处理、时频特征提取和聚类分析,获得与预训练模型相匹配的特征组,输入预训练的基坑边坡支护稳定性评估模型,输出稳定性评估向量。进而计算整体稳定性指数,确定基坑边坡的稳定状态,标注潜在的不稳定区域。该方法采用振动传感器对基坑边坡和支护结构进行连续监测,获取涵盖时域、频域和时频域特征的振动信号，利用深度学习模型,实现了对基坑边坡支护结构稳定性的检测。解决了现有检测依赖于专业人员的经验,易受主观因素的影响,且无法对边坡内部的应力变化进行有效监测的技术问题。
Foundation pit slope support stability detection method, medium and system
一种基坑边坡支护稳定性检测方法、介质及系统
SUN TIANZHI (author) / WANG BAODONG (author) / HAN HONGPENG (author) / LIN YANG (author) / WAN YONGMING (author) / ZHANG SHUAISHUAI (author) / WANG CHEN (author) / QIN HONGCHANG (author) / JIA PENG (author) / MU YUQIANG (author)
2024-09-24
Patent
Electronic Resource
Chinese
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