To acquire the accurate tunnel environment information
and comprehensively evaluate the tunnel air quality, a series of highway tunnel
environment perception system (TEPS) based on the Internet of Things and cloud
computing is designed and developed. Highprecision sensors measuring
pollutant concentration, temperature and pressure, visibility, and wind speed
and direction are arranged and integrated in a tunnel. An STM32 microprocessor
is adopted for realtime monitoring of environmental
data, and a 4G mobile communication network is used for remote data
transmission, realizing the cloud storage and realtime
display of the tunnel environment monitoring data. Compared with various
special detectors, the mean absolute percentage errors of CO and NO2 concentrations, visibility, and wind speed of the proposed system
are 3.36% and 1.73%, 5.43%, and 2.06%, respectively. Results demonstrate that
the TEPS is highly integrated, can be easily deployed, and provide stable
operation. These performance characteristics overcome the shortcomings of
portable monitoring devices, such as single collection content and insufficient
data accuracy, and those of the traditional fixed tunnel monitoring systems,
such as complex structure and scattered layout. By operating the TEPS online
for a long time, suitable data can be measured to support the exploration of
the variations in air quality in the tunnel caused by traffic and dynamical
adjustment of the ventilation systems.
QIAN Chao
,
DENG Musheng
,
LI Huxiong
,
CHEN Jianxun
,
WANG Chenyao
.
Design and Implementation of an Environment Perception System
for Highway Tunnels
[J]. Tunnel Construction, 2021
, 41(9)
: 1502
-1508
.
DOI: 10.3973/j.issn.2096-4498.2021.09.008
