CN106855787A - A kind of method of sampling of Internet of Things analog signal - Google Patents
A kind of method of sampling of Internet of Things analog signal Download PDFInfo
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- CN106855787A CN106855787A CN201611260495.7A CN201611260495A CN106855787A CN 106855787 A CN106855787 A CN 106855787A CN 201611260495 A CN201611260495 A CN 201611260495A CN 106855787 A CN106855787 A CN 106855787A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/05—Digital input using the sampling of an analogue quantity at regular intervals of time, input from a/d converter or output to d/a converter
Abstract
The invention discloses a kind of method of sampling of Internet of Things analog signal, it is adaptable to rotating machinery parameter (vibration, electric current) collection, including step：S01：The multiple operating cycle datas of sampling；S02：FFT treatment is done to upper step data, the frequency of its energy value maximum spectral line is calculated；S03：According to the frequency of energy value maximum spectral line, gathered data is calculated periodically；S04：Based on upper step data periodically, a cycle data are taken as reference data；S05：Sampling is periodically carried out by upper step data, and each cycle data judges with reference data similarity size, and similarity is big, into lower step；Similarity is small, improves sample frequency and return to step S02 proceeds after gathering multiple operating cycle datas；S06：Data are preserved and upload sample frequency and sampled data.The present invention uses the acquisition mode of variable sampling frequency, material time point data high frequency sampling, general data low-frequency sampling to embody the value of gathered data to greatest extent.
Description
Technical field
The present invention relates to Internet of Things field, more particularly to a kind of acquisition method of Internet of Things analog signal.
Background technology
During Internet of Things collection analogue data, in view of the limitation of the network bandwidth and server capacity, expects gathered data energy
Effectively embody value.During existing equipment remote collection data, sample frequency higher is generally used, so, greatly increase network
Burden and server storage burden.Under network abnormal situation, local datastore amount can be increased, loss is there is also for a long time
The situation of data, so as to increase remote maintenance cost.It is another to plant instrument, using relatively low sample frequency, in remote data exception
In the case of, the need for relatively low sample frequency can not meet Abnormality Analysis substantially, losing whole Internet of things system should have
Effect.
At present, remote analog data collecting instrument generally uses three kinds of methods：
1st, such as patent " CN102346959A ", a kind of remote gathering system of analog signal, the present invention relates to a kind of signal
A kind of acquisition system, and in particular to the collection in worksite distance transmission system of analog signal.The bus that it overcomes prior art is remote
The slow problem of journey data transmission bauds.For signal acquisition.It includes the collection of simulant signal device of measurand, A/D conversions
Circuit and remote computer, the analog signal output connection A/D change-over circuits of the collection of simulant signal device of measurand
Input end of analog signal, it also includes M-LVDS bus systems, and the digital signal output end connection M-LVDS of A/D change-over circuits is total
One end of linear system system, the other end connection remote computer of M-LVDS bus systems.
2nd, a kind of such as patent " CN201054708Y ", remote data collection radio applied in industrial control system is transmitted
Module, by analog data acquisition circuit, analogue data output circuit, four functional circuit structures of A/D converter circuit and GPRS module
Into.Wherein：The analog signal of analog data acquisition circuit collection detector output, is divided into two-way and is exported：Pass all the way
Analogue data output circuit is transported to, another road is transmitted to A/D converter circuit；Analogue data output circuit is electric by analog data acquisition
Analog signal that road collects is transparent to be exported to industrial control system；A/D converter circuit collects analog data acquisition circuit
Analog signal is converted into the data signal that can be compiled, and exports to GPRS module；GPRS module is by the number from A/D converter circuit
Word signal is transmitted on Internet Server, carries out long distance wireless data transfer.The present invention can with existing industrial control system without
Seam connection, makes the data of system carry out wireless remote transmission under conditions of existing system normal function is not influenceed, and data are uploaded
Onto specified server.
3rd, such as patent " CN102346453A ", the present invention is the Analog Data Acquistion Module based on EPA, by
Main control module, ethernet communication module, power module and AD data acquisition modules are constituted, and main control module is by Ethernet control
Device arm processor chip, standard jtag circuit and peripheral circuit are constituted, and standard jtag circuit is connected with arm processor, Ethernet
Communication module is made up of network transformer, the network chip of integrated PHY layer and RJ45 network interfaces, and power module is ether Netcom
News module and AD data acquisition modules provide power supply and reference voltage, AD data acquisition modules realize analog data collection and
Signal is changed, and the multiple analog signal of industry spot is converted to EPA signal by the present invention, constitutes EPA
The basic element of character, is easy to implement remote subscriber and data collecting card is conducted interviews and monitoring by Internet.
All there is irremediable shortcoming in existing three kinds of technologies.Three kinds of systems are when analogue data is gathered, it is impossible to intelligence
Sampling rate adjusting and reported data frequency, so, can cause loss or the delay of valid data, and failure is solved to produce necessarily
Hysteresis quality.
The content of the invention
It is an object of the invention to provide a kind of Internet of Things analog signal method of sampling energy adjustment sample frequency and on
Report data frequency, sampling precision is high, controllability is strong.
To achieve the above object, the present invention provides a kind of method of sampling of Internet of Things analog signal, including step：
S01：On slewing, the multiple operating cycle datas of sampling；
S02：FFT treatment is done to upper step data, the frequency of its energy value maximum spectral line is calculated；
S03：According to the frequency of energy value maximum spectral line, gathered data is calculated periodically；
S04：Based on upper step data periodically, a cycle data are taken as reference data；
S05：Sampling is periodically carried out by upper step data, and each cycle data judges with reference data similarity size, phase
It is big like spending, into lower step；Similarity is small, improves sample frequency and gathers return to step S02 continuation after multiple operating cycle datas
Carry out；
S06：Data are preserved and upload sample frequency and sampled data.
It is preferred that similarity judges to use Pearson correlation coefficient in step S05, the coefficient value is more than or equal to 0.72
Similarity is big, less than 0.72 for similarity is small.
It is preferred that each sample frequency sampling time is not less than 300s.
It is preferred that in step S04, if gathered data is periodically constant, reference data inconvenience, otherwise, reference data is replaced
It is new reference data.
It is preferred that in step S05, similarity hour provides sample frequency and at least samples 20 groups of data of service cycle.
It is preferred that data upload the upload in the form of protocol package in step S06.
Beneficial effects of the present invention：
(1), the present invention is based on to data with existing spectrum analysis, can draw the maximum dominant frequency of its energy value.It is big based on dominant frequency
It is small, to two kinds of data analysis its similitudes.If data are similar, and larger (close to +/- 1), its sample frequency and transmission frequency are with relatively low
Frequency is operated, if similarity is smaller, need to improve its sample frequency, also, with 20 groups of data in cycle of larger frequency collection；
(2), the present invention uses the acquisition mode of variable sampling frequency, the sampling of material time point data high frequency, general data
Low-frequency sampling, embodies the value of gathered data to greatest extent；
(3), the present invention can improve terminal intelligent level, so as to improve the effective percentage of unit data, save the network bandwidth.It is right
Online accident analysis provides effective data basis；
(4), using data collecting system of the present invention, in use, it is not necessary to manual intervention, intelligent acquisition significant figure
According to, and be transferred on Cloud Server.System in use, can be independently operated, and be used cooperatively without other equipment or instrument.
Brief description of the drawings
Fig. 1 is method of sampling flow chart of the invention.
Specific embodiment
Below in conjunction with the drawings and specific embodiments, invention is described in detail.
Shown in reference picture 1, the present invention provides a kind of method of sampling of Internet of Things analog signal, including step：
S01：The multiple operating cycle datas of sampling；
S02：FFT treatment is done to upper step data, the frequency of its energy value maximum spectral line is calculated；
S03：According to the frequency of energy value maximum spectral line, gathered data is calculated periodically；
S04：Based on upper step data periodically, a cycle data are taken as reference data；
S05：Sampling is periodically carried out by upper step data, and each cycle data judges with reference data similarity size, phase
It is big like spending, into lower step；Similarity is small, improves sample frequency and gathers return to step S02 continuation after multiple operating cycle datas
Carry out；
S06：Data are preserved and upload sample frequency and sampled data.
Wherein, similarity judges to use Pearson correlation coefficient in step S05, and the coefficient value is phase more than or equal to 0.72
It is big like spending, less than 0.72 for similarity is small.
Each sample frequency sampling time is not less than 300s.
In step S04, if gathered data is periodically constant, reference data inconvenience, otherwise, reference data replaces with new base
Quasi- data.
In step S05, similarity hour provides sample frequency and at least samples 20 groups of data of service cycle.
Data are uploaded and uploaded in the form of protocol package in step S06.
Based on the above method, its specific algorithm implementation process is as follows：
1st, discrete data is gathered, data space is defined as T；
2nd, FFT is made to data space T, calculates frequency space F：
F=FFT (T)；
Calculate the frequency MaxV of energy value maximum in the F of space：
MaxV=max (F)；
3rd, make sample frequency for V, data length is L, calculates mechanical basic frequency MainV：
MainV=MaxV × V/L；
Based on this frequency, primary period length MainL is calculated：
MainL=L/MaxV；
4th, a cycle data are chosen, as reference data space TLB (x1, x2 ... ..., Xn)；
5th, same, sampled newest data space TLN (y1, y2 ... ..., yn), and similarity-rough set is made with TLB：
If the 6, similarity is larger, continue to be gathered with existing sample rate；If similarity is smaller, sample frequency becomes big to MainV
8 to 10 times；Meanwhile, using newest data space TLN as reference data space.
If the 7, data are similar, the similar value for calculating two groups of data meets standardized normal distribution.Due to it is similar be in [0,1] area
It is interior, it is result to be distributed 80%, calculated based on standardized normal distribution formula：
X is interval for [0,0.28], i.e. similarity value calculation are more than 0.72.
The above-mentioned algorithm of implementation process of the present invention can reduce network data exchange, prevent loss of data；This algorithm can be gathered
Valid data, improve data user rate；This algorithm can be based on real data Intelligent adjustment, be situated between without Human disturbance and external data
Enter；Data upload information is complete, can guarantee that the integrality of the data in upload procedure.
In the present invention, in data upload process, can be using a kind of simple custom protocol such as table 1：
The Data Transport Protocol of table 1
| Skew | Value | Length | Remarks |
| 1 | 0x66 | 1byte | Data head |
| 2 | 8000 | 2byte | Sample frequency |
| 4 | 10000 | 2byte | Data length |
| 6 | N1, n2 ... nm | Value(4) | Data |
| T-2 | 0x1234 | 2byte | Check bit |
| T | 0x88 | 1 | Data tail |
The above, the only present invention preferably specific embodiment, but protection scope of the present invention is not limited thereto,
Any one skilled in the art in the technical scope of present disclosure, technology according to the present invention scheme and its
Inventive concept is subject to equivalent or change, should all be included within the scope of the present invention.
Claims (6)
1. a kind of method of sampling of Internet of Things analog signal, it is characterised in that including step：
S01：On slewing, the multiple operating cycle datas of sampling；
S02：FFT treatment is done to upper step data, the frequency of its energy value maximum spectral line is calculated；
S03：According to the frequency of energy value maximum spectral line, gathered data is calculated periodically；
S04：Based on upper step data periodically, a cycle data are taken as reference data；
S05：Sampling is periodically carried out by upper step data, and each cycle data judges with reference data similarity size, similarity
Greatly, into lower step；Similarity is small, improves sample frequency and return to step S02 proceeds after gathering multiple operating cycle datas；
S06：Data are preserved and upload sample frequency and sampled data.
2. the method for sampling according to claim 1, it is characterised in that similarity judges to use Pearson came phase in step S05
Relation number, the coefficient value is that similarity is big more than or equal to 0.72, less than 0.72 for similarity is small.
3. the method for sampling according to claim 1 and 2, it is characterised in that each sample frequency sampling time is not less than
300s。
4. the method for sampling according to claim 3, it is characterised in that in step S04, if gathered data is periodically constant,
Reference data inconvenience；Otherwise, reference data replaces with new reference data.
5. the method for sampling according to claim 3, it is characterised in that in step S05, similarity hour provides sample frequency
At least sample 20 groups of data of service cycle.
6. the method for sampling according to claim 4, it is characterised in that data are uploaded in the form of protocol package in step S06
Upload.
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Cited By (3)
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| CN110597145A (en) * | 2019-09-30 | 2019-12-20 | 鞍钢集团自动化有限公司 | Full life cycle management data acquisition system of electrical equipment |
| CN110597144A (en) * | 2019-09-30 | 2019-12-20 | 鞍钢集团自动化有限公司 | Motor sensor data acquisition unit and data acquisition method |
| CN111859307A (en) * | 2020-08-18 | 2020-10-30 | 久视数字科技(苏州)有限公司 | Data acquisition method and device capable of effectively improving data acquisition and transmission efficiency |
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Application publication date: 20170616 |
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