CN109218420A - Wireless displacement sensor and system based on NB-IoT - Google Patents
Wireless displacement sensor and system based on NB-IoT Download PDFInfo
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- CN109218420A CN109218420A CN201811044401.1A CN201811044401A CN109218420A CN 109218420 A CN109218420 A CN 109218420A CN 201811044401 A CN201811044401 A CN 201811044401A CN 109218420 A CN109218420 A CN 109218420A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a kind of wireless displacement sensors based on NB-IoT, including displacement meter, it send after displacement meter acquisition displacement data to low level signal amplification module, low level signal amplification module amplifies displacement data, then amplified displacement data is sent to MCU core board, MCU core board carries out control for being stored to displacement data, to the frequency acquisition of displacement meter and communicates with NB-IoT module.The invention also discloses the systems using the sensor.Low-power consumption of the present invention, low cost, high-precision.
Description
Technical field
The present invention relates to wireless displacement sensors and system based on NB-IoT.
Background technique
Traditional displacement sensor is based on wire transmission, and wherein resistance-type, that is, strain bridge principle accounts for the overwhelming majority.Its
Have the characteristics that high-precision, high sensitivity, but transmission range is limited, live displacement sensor difficult wiring, need to be equipped with corresponding
Demodulated equipment and later maintenance difficulty, are difficult to maintain to work normally under the environment of condition of power supply deficiency.Meanwhile if to bridge or
Other infrastructure change in displacement carry out cluster monitoring, will face huge on-site installation work amount and high cost requirement.It adopts
Be conducive to cluster with wireless technology, lay displacement sensor on a large scale, and data is facilitated to manage concentratedly.Current wireless technology is more
Sample, 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 wireless 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 low-power consumption, low cost, high-precision based on the wireless of NB-IoT
Displacement sensor and system.
Technical solution: to reach this purpose, the invention adopts the following technical scheme:
Wireless displacement sensor of the present invention based on NB-IoT, including displacement meter, displacement meter acquire displacement data
After send to low level signal amplification module, low level signal amplification module amplifies displacement data, then by amplified displacement data
Be sent to MCU core board, MCU core board for being stored to displacement data, to the frequency acquisition of displacement meter controlled with
And it is communicated with NB-IoT module.
Further, the displacement meter includes post rod type displacement sensing module.
It further include data management module using the system of the wireless displacement sensor of the present invention based on NB-IoT,
NB-IoT module is communicated with data management module.
Further, the data management module carries out real-time reception to the displacement data that NB-IoT module is sent and deposits
Storage, establishes data recovering algorithms to the event of data loss being likely to occur；By the detection of fixed data length, to current data
Data count and time point in length are detected: being jumped if it find that data count exists less than regular length or time point
The case where jump, missing, then determines that the segment data in the presence of losing, according to data random loss and continuous loss both of these case, is led to
Overcompression perception theory is indicated displacement data by sparse transformation vector.
Further, the data management module carries out recovery and rebuilding to missing data using following methods:
S1: construction calculation matrix φ:
φ∈RM×N (1)
In formula (1), the diagonal entry of calculation matrix φ is 1, other elements 0；M is missing data quantity, and N is complete
Data bulk；
S2: by data with existing sample, constructing complete dictionary, so that each segment data of data sample can be realized formula (2)
Expression:
Y=Dx (2)
In formula (2), y is certain segment data of data sample, and D was complete dictionary, and x is the rarefaction representation vector to y；
S3: estimated by the partial data that the following formula solves quasi- prediction, complete missing data recovery and rebuilding:
In formula (3),Estimate for the quasi- partial data predicted,To solve to obtain by orthogonal matching algorithm progressive alternate
Estimated value.
Further, in the step S2, excessively complete dictionary is constructed by following steps:
S2.1: dictionary D is initialized as to the matrix of data with existing sample composition；
S2.2: the corresponding rarefaction representation vector x of certain segment data of data sample is solved；
s.b.||x||0≤T0 (5)
Wherein, T0For the maximum value of nonzero element sum in rarefaction representation vector x；
S2.3: dictionary D is updated by formula (6):
In formula (6), Y is the set of each data sample, and X is the set of each rarefaction representation vector, vector dkIndicate to
Update the kth column of dictionary D, vector djIndicate the jth column of dictionary D to be updated, xTIndicate vector dkRow k vector in corresponding X,
Matrix EkTo remove dkError matrix afterwards.
It further, further include visualization interface, data management module shows data by visualization interface.
It further, further include power management module, power management module is that MCU core board and low level signal amplification module supply
Electricity.
The utility model has the advantages that the invention discloses a kind of wireless displacement sensor and system based on NB-IoT, with the prior art
Compare, have it is following the utility model has the advantages that
(1) present invention establishes wireless top displacement sensor by NB-IoT wireless communication module, solve wired sensor at
The problems such as this height, difficult wiring, in-site installation difficulty is big, and existing wireless sensor transmissions are solved apart from limited, power consumption is big etc.
Problem effectively solves the problems such as scene power supply is difficult, can be realized low cost, low-power consumption, the long-life, extensively covers purpose, be conducive to
Realize that the infrastructure displacement data such as bridge is long-term, real-time monitoring.
(2) wireless sensor of the invention can report and submit requirement according to field data, provide corresponding acquisition and send mould
Formula transfers data to cloud server by udp protocol, can be realized large-scale cluster displacement monitoring purpose, realizes data
Centralized management.
(3) data management module realizes data loss detection, data recovery and rebuilding and real-time visual.Module high-precision
Data recovery procedure can make up for it because the factors such as environment, equipment cause wireless data loss bring data discontinuous and analysis sample
The problems such as this deficiency.
Detailed description of the invention
Fig. 1 is the block diagram of system in the specific embodiment of the invention；
Fig. 2 is the procedure chart of data transmission in the specific embodiment of the invention；
Fig. 3 is that data recovering algorithms flow chart is lost in the specific embodiment of the invention；
Fig. 4 is the schematic diagram of loss of data and recovery in the specific embodiment of the invention；
Fig. 4 (a) is total data sample tendency chart in the specific embodiment of the invention；
Fig. 4 (b) is the schematic diagram of random loss in the specific embodiment of the invention；
Fig. 4 (c) is that data estimated value and practical partial data compare Error Graph in the specific embodiment of the invention.
Specific embodiment
Present embodiment discloses a kind of wireless displacement sensor based on NB-IoT, as shown in Figure 1, including displacement
Meter, displacement meter are sent after acquiring displacement data to low level signal amplification module, and low level signal amplification module amplifies displacement data, so
Amplified displacement data is sent to MCU core board afterwards, MCU core board is for storing displacement data, to displacement meter
Frequency acquisition carry out control and communicated with NB-IoT module.
(1) displacement meter
Including post rod type displacement sensing module, displacement data is acquired using YHD type displacement sensor, mainly by machine driving
Mechanism, instruction device and electric wiring composition.Basic functional principle uses strain bridge principle, using half-bridge or full-bridge mode,
Resistance variations are converted into change in displacement analog signal, error range has that output sensitivity is high less than 5 microstrains, good linearity,
It is small in size, from heavy and light, drift about the features such as small.
(2) MCU 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, command displacement meter frequency acquisition, AT instruction
Communication and AccessPort function.By compiling C language SCM program, setting receives displacement and counts frequency, passes through single-chip microcontroller
Internal clocking determines whether that receiving displacement counts；Compiling C programmer generates AT and instructs and be sent to NB-IoT module.
(3) 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 " and sends 16 binary datas to specified public network IP.
Present embodiment also discloses the system using the wireless displacement sensor based on NB-IoT, as shown in Figure 1,
Including data management module, NB-IoT module is communicated with data management module.System further includes visualization interface, data pipe
Reason module shows data by visualization interface.In addition, system further includes power management module, power management module is
MCU core board and low level signal amplification module for power supply Fig. 2 are the procedure chart of data transmission in the specific embodiment of the invention.
The displacement data that data management module sends NB-IoT module carries out real-time reception and storage, to being likely to occur
Event of data loss establish data recovering algorithms.By writing the Socket program of Python, UDP connection is established, is supervised in real time
UDP designated port (such as 8080) are listened, by separators such as " " or " | | " by Interval data are bridge if there are data to enter
ID, sensor number, data, the data fields such as time, and according to bridge ID and sensor number, it stores to the data of specified ID
In library.By the detection of fixed data length, in current data length data count and time point detect: if hair
There is the case where jump, missing less than regular length or time point in existing data count, then determine that the segment data exists and lose, according to
According to data random loss and it is continuous lose both of these case, by compressive sensing theory, to displacement data by sparse transformation to
Amount is indicated.
As shown in figure 3, data management module carries out recovery and rebuilding to missing data using following methods:
S1: construction calculation matrix φ:
φ∈RM×N (1)
In formula (1), the diagonal entry of calculation matrix φ is 1, other elements 0；M is missing data quantity, and N is complete
Data bulk；
S2: by data with existing sample, constructing complete dictionary, so that each segment data of data sample can be realized formula (2)
Expression:
Y=Dx (2)
In formula (2), y is certain segment data of data sample, and D was complete dictionary, and x is the rarefaction representation vector to y；
S3: estimated by the partial data that the following formula solves quasi- prediction, complete missing data recovery and rebuilding:
In formula (3),Estimate for the quasi- partial data predicted,To solve to obtain by orthogonal matching algorithm progressive alternate
Estimated value.
In step S2, excessively complete dictionary is constructed by following steps:
S2.1: dictionary D is initialized as to the matrix of data with existing sample composition；
S2.2: the corresponding rarefaction representation vector x of certain segment data of data sample is solved；
s.b.||x||0≤T0 (5)
Wherein, T0For the maximum value of nonzero element sum in rarefaction representation vector x；
S2.3: dictionary D is updated by formula (6):
In formula (6), Y is the set of each data sample, and X is the set of each rarefaction representation vector, vector dkIndicate to
Update the kth column of dictionary D, vector djIndicate the jth column of dictionary D to be updated, xTIndicate vector dkRow k vector in corresponding X,
Matrix EkTo remove dkError matrix afterwards.
30 groups of total data samples are chosen, every data sample contains 1000 data, loses at random wherein every group of sample standard deviation exists
It loses or continuous loss situation, loss data is 400, set and lose data as 0.Fig. 4 (a) is total data sample tendency chart, Fig. 4
It (b) is random loss schematic diagram.
After the excessively complete dictionary of K-SVD algorithm construction, missing data sample is chosen, has been solved using orthogonal matching algorithm
Entire data estimated value, the value and practical partial data are to shown in ratio error such as Fig. 4 (c), and as seen from the figure, the error for reconstructing data exists
Within 0.2%, meet bridge monitoring in the accuracy requirement of practical application.
Claims (8)
1. the wireless displacement sensor based on NB-IoT, it is characterised in that: including displacement meter, sent after displacement meter acquisition displacement data
To low level signal amplification module, low level signal amplification module amplifies displacement data, then sends amplified displacement data
To MCU core board, MCU core board for displacement data is stored, to the frequency acquisition of displacement meter carry out control and with
NB-IoT module is communicated.
2. the wireless displacement sensor according to claim 1 based on NB-IoT, it is characterised in that: the displacement meter includes
Post rod type displacement sensing module.
3. using the system of the wireless displacement sensor according to claim 1 based on NB-IoT, it is characterised in that: also wrap
Data management module is included, NB-IoT module is communicated with data management module.
4. the system according to claim 3 using the wireless displacement sensor based on NB-IoT, it is characterised in that: described
Data management module carries out real-time reception and storage to the displacement data that NB-IoT module is sent, and loses to the data being likely to occur
It loses situation and establishes data recovering algorithms；By the detection of fixed data length, in current data length data count and when
Between point detected: if it find that data count has the case where jump, missing less than regular length or time point, then determine
The segment data, which exists, loses, and both of these case is lost with continuous according to data random loss, by compressive sensing theory, to displacement
Data are indicated by sparse transformation vector.
5. the system according to claim 3 using the wireless displacement sensor based on NB-IoT, it is characterised in that: described
Data management module carries out recovery and rebuilding to missing data using following methods:
S1: construction calculation matrix φ:
φ∈RM×N (1)
In formula (1), the diagonal entry of calculation matrix φ is 1, other elements 0；M is missing data quantity, and N is partial data
Quantity；
S2: by data with existing sample, constructing complete dictionary, so that each segment data of data sample can be realized the table of formula (2)
Show:
Y=Dx (2)
In formula (2), y is certain segment data of data sample, and D was complete dictionary, and x is the rarefaction representation vector to y；
S3: estimated by the partial data that the following formula solves quasi- prediction, complete missing data recovery and rebuilding:
In formula (3),Estimate for the quasi- partial data predicted,For the estimation solved by orthogonal matching algorithm progressive alternate
Value.
6. the system according to claim 5 using the wireless displacement sensor based on NB-IoT, it is characterised in that: described
In step S2, excessively complete dictionary is constructed by following steps:
S2.1: dictionary D is initialized as to the matrix of data with existing sample composition；
S2.2: the corresponding rarefaction representation vector x of certain segment data of data sample is solved；
s.b.||x||0≤T0 (5)
Wherein, T0For the maximum value of nonzero element sum in rarefaction representation vector x；
S2.3: dictionary D is updated by formula (6):
In formula (6), Y is the set of each data sample, and X is the set of each rarefaction representation vector, vector dkIndicate word to be updated
The kth of allusion quotation D arranges, vector djIndicate the jth column of dictionary D to be updated, xTIndicate vector dkRow k vector in corresponding X, matrix Ek
To remove dkError matrix afterwards.
7. the system according to claim 3 using the wireless displacement sensor based on NB-IoT, it is characterised in that: also wrap
Visualization interface is included, data management module shows data by visualization interface.
8. the system according to claim 3 using the wireless displacement sensor based on NB-IoT, it is characterised in that: also wrap
Power management module is included, power management module is MCU core board and low level signal amplification module for power supply.
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