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Side slope pre-stressed anchor rod intelligent monitoring and early warning system and method based on cloud platform
The invention discloses a side slope pre-stressed anchor rod intelligent monitoring and early warning system and method based on a cloud platform. The side slope pre-stressed anchor rod intelligent monitoring and early warning method based on the cloud platform comprises the steps that S1, strain values of all point locations on an anchor rod are collected in real time; S2, an anchor rod average shear stress prediction model is constructed; S3, a gap stress function relationship between the anchor rod and an anchor hole is calculated; S4, the anchor rod average shear stress prediction model iscorrected to obtain an anchor rod shear stress prediction model; S5, the absolute value D of the difference between an anchor rod shear stress value output by the prediction model and an anchor rod shear stress value actually measured by a magnetic flux sensor is measured; S6, the absolute value D is divided; and S7, a neural network model of accident early warning is constructed. According to the side slope pre-stressed anchor rod intelligent monitoring and early warning method based on the cloud platform, the neural network model of accident early warning is constructed by adopting an intelligent algorithm, the stress bearing condition of the current anchor rod is predicted through the stress data acquired in real time, and when the stress bearing capacity of the anchor rod exceeds a preset value, the fault type is judged.
本发明公开了基于云平台的边坡预应力锚杆智能化监测预警系统及方法，包括S1、实时采集锚杆上各个点位的应变值；S2、构建锚杆平均剪应力预测模型；S3、计算锚杆与锚孔之间的空隙应力函数关系；S4、修正锚杆平均剪应力预测模型，得到锚杆剪应力预测模型；S5、衡量预测模型输出的锚杆剪应力值与磁通量传感器实测得到的锚杆剪应力值之间的差的绝对值D；S6、对绝对值D进划分；S7、构建事故预警的神经网络模型。本发明采用智能算法构建事故预警的神经网络模型，通过实时采集的应力数据预测当前锚杆的应力承受情况，当锚杆应力承受超过预设值时，对故障类型进行判断。
Side slope pre-stressed anchor rod intelligent monitoring and early warning system and method based on cloud platform
The invention discloses a side slope pre-stressed anchor rod intelligent monitoring and early warning system and method based on a cloud platform. The side slope pre-stressed anchor rod intelligent monitoring and early warning method based on the cloud platform comprises the steps that S1, strain values of all point locations on an anchor rod are collected in real time; S2, an anchor rod average shear stress prediction model is constructed; S3, a gap stress function relationship between the anchor rod and an anchor hole is calculated; S4, the anchor rod average shear stress prediction model iscorrected to obtain an anchor rod shear stress prediction model; S5, the absolute value D of the difference between an anchor rod shear stress value output by the prediction model and an anchor rod shear stress value actually measured by a magnetic flux sensor is measured; S6, the absolute value D is divided; and S7, a neural network model of accident early warning is constructed. According to the side slope pre-stressed anchor rod intelligent monitoring and early warning method based on the cloud platform, the neural network model of accident early warning is constructed by adopting an intelligent algorithm, the stress bearing condition of the current anchor rod is predicted through the stress data acquired in real time, and when the stress bearing capacity of the anchor rod exceeds a preset value, the fault type is judged.
本发明公开了基于云平台的边坡预应力锚杆智能化监测预警系统及方法，包括S1、实时采集锚杆上各个点位的应变值；S2、构建锚杆平均剪应力预测模型；S3、计算锚杆与锚孔之间的空隙应力函数关系；S4、修正锚杆平均剪应力预测模型，得到锚杆剪应力预测模型；S5、衡量预测模型输出的锚杆剪应力值与磁通量传感器实测得到的锚杆剪应力值之间的差的绝对值D；S6、对绝对值D进划分；S7、构建事故预警的神经网络模型。本发明采用智能算法构建事故预警的神经网络模型，通过实时采集的应力数据预测当前锚杆的应力承受情况，当锚杆应力承受超过预设值时，对故障类型进行判断。
Side slope pre-stressed anchor rod intelligent monitoring and early warning system and method based on cloud platform
基于云平台的边坡预应力锚杆智能化监测预警系统及方法
QU HONGLUE (author) / LIAO YU (author) / TANG WENRUI (author) / WANG WEI (author) / TANG TAIKE (author)
2020-12-18
Patent
Electronic Resource
Chinese
IPC:
E02D
FOUNDATIONS
,
Gründungen
/
G01D
MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE
,
Anzeigen oder Aufzeichnen in Verbindung mit Messen allgemein
/
G01L
Messen von Kraft, mechanischer Spannung, Drehmoment, Arbeit, mechanischer Leistung, mechanischem Wirkungsgrad oder des Drucks von Fluiden
,
MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
/
G06F
ELECTRIC DIGITAL DATA PROCESSING
,
Elektrische digitale Datenverarbeitung
/
G08B
SIGNALLING OR CALLING SYSTEMS
,
Signalisier- oder Rufsysteme
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