CN109405729A - Wireless sensor, method for sensing and the system of bridge defect crack long term monitoring - Google Patents
Wireless sensor, method for sensing and the system of bridge defect crack long term monitoring Download PDFInfo
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- CN109405729A CN109405729A CN201811065150.5A CN201811065150A CN109405729A CN 109405729 A CN109405729 A CN 109405729A CN 201811065150 A CN201811065150 A CN 201811065150A CN 109405729 A CN109405729 A CN 109405729A
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- strain
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- signal amplification
- long term
- bridge
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
- G01B7/16—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge
- G01B7/18—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge using change in resistance
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- General Physics & Mathematics (AREA)
- Arrangements For Transmission Of Measured Signals (AREA)
Abstract
The invention discloses the wireless sensors of bridge defect crack long term monitoring, including tool-type surface strain sensor, tool-type surface strain sensor measurement Bridge Crack bring strain resistor changes and measurement result is sent to strain signal amplification module, strain signal amplification module carries out signal amplification and A/D conversion, and the digital signal obtained after conversion is sent to core board, core board sends instructions to NB-IoT module.The present invention solves the problems such as wired strain acquirement equipment cost height, difficult wiring, big in-site installation difficulty, have the characteristics that low cost, low-power consumption, high-precision, effectively realizes that the strain data in bridge defect crack area change procedure is long-term, real-time monitoring process.
Description
Technical field
The present invention relates to wireless sensor technologies, more particularly to wireless sensor, method for sensing and system.
Background technique
Most current strain data is based on wire transmission, and wherein resistance-type, that is, strain bridge principle accounts for the overwhelming majority,
It has the characteristics that high-precision, high sensitivity, but transmission range is limited, live displacement sensor difficult wiring, prior
It is to carry out long term monitoring if straining to the infrastructure cluster such as bridge, building, each bridge or building should all be placed accordingly
Acquisition equipment, high installation cost and later maintenance cost will be brought.It is wired under the environment of the conditions of power supply such as bridge deficiency
Acquisition equipment is even more to be difficult to maintain to work normally.
Cluster is conducive to using wireless technology, lays displacement sensor on a large scale, and data is facilitated to manage concentratedly.Current nothing
Line technology multiplicity, but there is high power consumption in major part, and the infrastructure such as bridge site environment is complicated, and power supply is difficult, high power consumption
Radio Transmission Technology such as WiFi, ZigBee, 4G etc. are difficult to meet long-time service requirement.
Summary of the invention
Goal of the invention: the object of the present invention is to provide a kind of inexpensive, low-power consumption bridge defect crack long term monitorings
Wireless sensor, method for sensing and system.
Technical solution: to reach this purpose, the invention adopts the following technical scheme:
The wireless sensor of bridge defect crack of the present invention long term monitoring, including tool-type surface strain sensing
Measurement result is simultaneously sent to strain letter by device, the variation of tool-type surface strain sensor measurement Bridge Crack bring strain resistor
Number amplification module, strain signal amplification module carries out signal amplification and A/D conversion, and the digital signal obtained after conversion is sent
To core board, core board sends instructions to NB-IoT module.
It further, further include power module, power module is that core board and strain signal amplification module are powered.
Further, the power module includes lithium battery.
Further, the core board includes MSP430F5438A low power processor chip.
Using the method for sensing of the wireless sensor of bridge defect crack of the present invention long term monitoring, including following step
It is rapid:
S1: tool-type surface strain sensor measurement Bridge Crack bring strain resistor changes and sends measurement result
Give strain signal amplification module；
S2: strain signal amplification module carries out signal amplification and A/D conversion, and the digital signal obtained after conversion is sent
To core board；
S3: core board transmission AT, which is instructed, gives NB-IoT module；
S4:NB-IoT module establishes the connection with cloud data management module by udp protocol.
Using the system of the wireless sensor of bridge defect crack of the present invention long term monitoring, including multiple wireless biographies
Sensor and a cloud data management module, multiple wireless sensors are led to by udp protocol and cloud data management module
Letter.
The utility model has the advantages that the invention discloses a kind of wireless sensor of bridge defect crack long term monitoring, method for sensing and
System establishes wireless strain sensor for measuring the Developing Condition in bridge defect crack by NB-IoT module, passes through crack
The situation of change in the resistance change reflection crack during development solves wired strain acquirement equipment cost height, wiring is stranded
Difficult, the problems such as in-site installation difficulty is big, have the characteristics that low cost, low-power consumption, high-precision, effective realization bridge defect crack area
Strain data in change procedure is long-term, real-time monitoring process.
Detailed description of the invention
Fig. 1 is the schematic diagram of sensor in the specific embodiment of the invention；
Fig. 2 is the flow chart of method for sensing in the specific embodiment of the invention；
Fig. 3 is the schematic diagram of system in the specific embodiment of the invention.
Specific embodiment
Technical solution of the present invention is further introduced with attached drawing With reference to embodiment.
Present embodiment discloses a kind of wireless sensor of bridge defect crack long term monitoring, as shown in Figure 1, packet
Tool-type surface strain sensor is included, tool-type surface strain sensor measurement Bridge Crack bring strain resistor changes and incites somebody to action
Measurement result is sent to strain signal amplification module, and strain signal amplification module carries out signal amplification and A/D conversion, and will conversion
The digital signal obtained afterwards is sent to core board, and core board sends instructions to NB-IoT module.Further include power module, energizes mould
Block is that core board and strain signal amplification module are powered.
Each section is described below:
(1) power module
It uses lithium battery to provide 3.7V normal voltage to power for core board and strain signal amplification module.
(2) tool-type surface strain sensor
Including elastomer, strain ga(u)ge, extraction wire, connection terminal, fixed screw.By fixing sensor both ends,
It is set to be across crack two sides, the increase of crack progressing bring strain value can be converted into the increased resistance value of the sensor.It is led
Want technical indicator are as follows: gauge length 100mm, variable quantity are ± 1mm, and output sensitivity is ± 10000 microstrains/mm.
(3) core board
Including MSP430F5438A low power processor chip, there are three 16 bit timing devices, one high-performance 12 for tool
The common serial communication interface of ADC, up to four (USCI), a hardware multiplier, DMA, the RTC block with warning function and
87 I/O pins.Core board includes power switch, DC12V input, serial communication.Expansion interface supports I2C, guarantees core board
With NB-IoT module normal communication.The core board mainly realizes that low power consumption data stores, and controls tool-type surface strain sensor
Frequency acquisition, AT command communication and AccessPort function.By compiling C language SCM program, setting receives tool-type surface
Strain transducer data frequency determines whether to receive tool-type surface strain sensing data by single-chip microcontroller internal clocking；It compiles
C programmer generation AT is translated to instruct and be sent to NB-IoT module.
(4) NB-IoT module
Use BC95-B20 frequency range for 850MHz module, number of pin 94, supply voltage 3.1V~4.2V, representative value
3.8V, operating temperature are -40 DEG C~+85 DEG C, are instructed and are controlled using AT, transmit data with udp protocol.The module receives core board
After AT instruction, executes network and find and register, establish udp protocol connection, transmission sensing data to specified IP, port.The module
Main AT instruction includes: " AT+CFUN=1 " setting operating mode, " AT+CGDCONT=1, " IP ", " APN " " setting networking side
Formula, " AT+CGATT=1 " adhere to network, and " AT+CSQ " inquires signal strength, " AT+CEREG? " registered network state is inquired, is led to
It crosses " AT+NSOCR " Xiang Zhiding public network IP and sends 16 binary datas.
Present embodiment also discloses the method for sensing using wireless sensor, as shown in Fig. 2, including following step
It is rapid:
S1: tool-type surface strain sensor measurement Bridge Crack bring strain resistor changes and sends measurement result
Give strain signal amplification module；
S2: strain signal amplification module carries out signal amplification and A/D conversion, and the digital signal obtained after conversion is sent
To core board；
S3: core board transmission AT, which is instructed, gives NB-IoT module；
S4:NB-IoT module establishes the connection with cloud data management module by udp protocol.
Cloud data management module uses serial ports program, and port numbers 8082 write udp protocol interface journey using Python
Sequence establishes 8082 ports using the library socket and receives program, receives wireless data, according to ID identification (RNC-ID) analytic data, uses
MangoDB real-time storage data are into specified database table.
In addition, present embodiment also discloses the system using wireless sensor, as shown in figure 3, including multiple nothings
Line sensor and a cloud data management module, multiple wireless sensors by udp protocol and cloud data management module into
Row communication.Different sensors can require to be configured according to the frequency acquisition of corresponding disease, and all monitoring data can be beyond the clouds
It is stored and is read.
Claims (6)
1. the wireless sensor of bridge defect crack long term monitoring, it is characterised in that: including tool-type surface strain sensor, work
Tool formula surface strain sensor measurement Bridge Crack bring strain resistor, which changes and measurement result is sent to strain signal, to be put
Big module, strain signal amplification module carries out signal amplification and A/D conversion, and the digital signal obtained after conversion is sent to core
Core, core board send instructions to NB-IoT module.
2. the wireless sensor of bridge defect crack according to claim 1 long term monitoring, it is characterised in that: further include supplying
Energy module, power module are that core board and strain signal amplification module are powered.
3. the wireless sensor of bridge defect crack according to claim 2 long term monitoring, it is characterised in that: the energy supply
Module includes lithium battery.
4. the wireless sensor of bridge defect crack according to claim 1 long term monitoring, it is characterised in that: the core
Plate includes MSP430F5438A low power processor chip.
5. the method for sensing of the wireless sensor using bridge defect crack according to claim 1 long term monitoring, special
Sign is: the following steps are included:
S1: tool-type surface strain sensor measurement Bridge Crack bring strain resistor, which changes and is sent to measurement result, answers
Varying signal amplification module；
S2: strain signal amplification module carries out signal amplification and A/D conversion, and the digital signal obtained after conversion is sent to core
Core；
S3: core board transmission AT, which is instructed, gives NB-IoT module；
S4:NB-IoT module establishes the connection with cloud data management module by udp protocol.
6. the system of the wireless sensor using bridge defect crack according to claim 1 long term monitoring, feature exist
In: including multiple wireless sensors and a cloud data management module, multiple wireless sensors pass through udp protocol and cloud number
It is communicated according to management module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811065150.5A CN109405729A (en) | 2018-09-13 | 2018-09-13 | Wireless sensor, method for sensing and the system of bridge defect crack long term monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811065150.5A CN109405729A (en) | 2018-09-13 | 2018-09-13 | Wireless sensor, method for sensing and the system of bridge defect crack long term monitoring |
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| Publication Number | Publication Date |
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| CN109405729A true CN109405729A (en) | 2019-03-01 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201811065150.5A Pending CN109405729A (en) | 2018-09-13 | 2018-09-13 | Wireless sensor, method for sensing and the system of bridge defect crack long term monitoring |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111473722A (en) * | 2020-04-10 | 2020-07-31 | 东南大学 | Flexible deformation sensor with double-crack structure and preparation method thereof |
| CN113188436A (en) * | 2021-05-18 | 2021-07-30 | 吉林大学 | Bridge strain and crack monitoring method and device based on bionic sensing element |
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| CN201803691U (en) * | 2010-03-02 | 2011-04-20 | 赵启林 | Inside embedded type seam monitoring device based on flexible conductive paint |
| CN103067941A (en) * | 2012-12-26 | 2013-04-24 | 武汉大学 | Multivariable distributed type online monitoring system based on wireless sensor network |
| CN206450196U (en) * | 2017-02-23 | 2017-08-29 | 安徽感知土木科技有限公司 | A kind of bridge displacement monitoring device communicated based on NB IoT |
| CN107491575A (en) * | 2016-12-30 | 2017-12-19 | 河南省交通规划设计研究院股份有限公司 | The vector representation mode and data processing method of Bridge Crack disease |
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2018
- 2018-09-13 CN CN201811065150.5A patent/CN109405729A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201803691U (en) * | 2010-03-02 | 2011-04-20 | 赵启林 | Inside embedded type seam monitoring device based on flexible conductive paint |
| CN103067941A (en) * | 2012-12-26 | 2013-04-24 | 武汉大学 | Multivariable distributed type online monitoring system based on wireless sensor network |
| CN107491575A (en) * | 2016-12-30 | 2017-12-19 | 河南省交通规划设计研究院股份有限公司 | The vector representation mode and data processing method of Bridge Crack disease |
| CN206450196U (en) * | 2017-02-23 | 2017-08-29 | 安徽感知土木科技有限公司 | A kind of bridge displacement monitoring device communicated based on NB IoT |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111473722A (en) * | 2020-04-10 | 2020-07-31 | 东南大学 | Flexible deformation sensor with double-crack structure and preparation method thereof |
| CN111473722B (en) * | 2020-04-10 | 2021-05-11 | 东南大学 | Flexible deformation sensor with double-crack structure and preparation method thereof |
| CN113188436A (en) * | 2021-05-18 | 2021-07-30 | 吉林大学 | Bridge strain and crack monitoring method and device based on bionic sensing element |
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Application publication date: 20190301 |
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