Wireless intelligent alarming system for automatically monitoring multivariate information of tunnel

Abstract

The invention discloses a wireless intelligent alarming system for automatically monitoring multivariate information of a tunnel. The wireless intelligent alarming system is characterized by being realized by the following steps of: firstly, identifying surrounding rock multivariate parameters based on a differential evolution algorithm and a support vector machine; secondly, predicating a surrounding rock multivariate information time sequence based on the differential evolution algorithm and the support vector machine; and thirdly, carrying out judgment and alarm on the safety of the surrounding rock according to filed monitoring information and an information predication result obtained in the second step. According to the system, the requirements on a field communication cable and the field processing capability are reduced, and thus an acquisition-transmission instrument of a filed part is integrated on a circuit board; a wireless data transmission technology is adopted on site and field monitoring data is comprehensively and smoothly transmitted to a data processing system for an ultra-long distance; and an analytic result alarms through short messages, emails and qq, so that the pertinence, the flexibility and the reliability of alarm are improved. The direct contact between relevant persons and complex and danger surrounding rock field can be avoided and status information of the surrounding rock can be safely and remotely acquired.

Description

technical field [0001] The invention relates to a multi-information intelligent alarm system for remote automatic monitoring of tunnels. Background technique [0002] With the progress of tunnel engineering construction in our country, more and more tunnels in water-rich areas have emerged, such as coastal area tunnels, submarine tunnels, cross-river tunnels, river bottom tunnels, and karst area tunnels. These tunnels are built under groundwater, and there is a complex seepage-stress coupling effect in the surrounding rock, and their stability states are represented by various comprehensive characterization information such as displacement, stress, and flow. During the tunnel construction period, ordinary manual monitoring and general single-information online monitoring instruments are often difficult to obtain effective surrounding rock state prediction information. Therefore, safety accidents such as landslides and water inrush in tunnels in water-rich areas have occurred...

AI Technical Summary

Problems solved by technology

During the tunnel construction period, ordinary manual monitoring and general single-information online monitoring instruments are often difficult to obtain effective surrounding rock state prediction information. Therefore, safety accidents such as landslides and water inrush in tunnels in water-rich areas have occurred frequently, bringing serious economic and economic losses. social hazard

[0003] The current tunnel monitoring technology has considerable limitations in judging the surrounding rock state of tunnels in water-rich areas, mainly in the following aspects: 1. The information of general online monitoring instruments is single, while tunnels in water-rich areas have typical multi-field coupling, parameter many features

A single monitoring information cannot fully reflect the stability of tunnel engineering

2. If a variety of sensors are deployed on site, it will involve the transmission and processing of complex multi-information data

3. The environment of the tunnel site is poor and the space is limited, so it is not allowed to install a bulky computer system, and the complex multi-information processing tasks are beyond the capabilities of embedded systems such as single-chip computers

The size and layout space of tunnel monitoring instruments are limited, and it is not allowed to lay too long data cables. Generally, only single-chip microprocessors and short cables can be used, and it is difficult to realize complex fusion processing of complex and multivariate information. Analytical computing and long-distance data transmission

The software and hardware systems of traditional tunnel monitoring are difficult to meet the requirements of multi-information automatic prediction system for tunnels in water-rich areas

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