CN103364625A - Automatic online tracking method for sensor zero drift - Google Patents
Automatic online tracking method for sensor zero drift Download PDFInfo
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- CN103364625A CN103364625A CN2012101037983A CN201210103798A CN103364625A CN 103364625 A CN103364625 A CN 103364625A CN 2012101037983 A CN2012101037983 A CN 2012101037983A CN 201210103798 A CN201210103798 A CN 201210103798A CN 103364625 A CN103364625 A CN 103364625A
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Abstract
To solve problems of automatic online tracking and real-time compensation of sensor zero drift, an automatic online tracking method for the sensor zero drift is proposed. The sensor zero drift problem in a test and measurement process of the sensor is a big problem which is troubling people all the time. To weaken effects of the zero drift, people propose all kinds of methods: 1. according to implementation conditions, the methods include a hardware circuit compensation method and a software compensation method; 2. a neural network method; and 3. an automatic zero-setting circuit. The above-mentioned three methods enable zero drift of a specific kind to be dealt with greatly. However, zero tracking cannot be carried out greatly and automatic online tracking cannot be realized. But this method enables an automatic online tracking function to be realized and at the same time requires fewer registers for sample data storage at a previous moment and at a current moment and fewer calculations so that problems of big data storages and a large quantity of calculations are avoided and the function of automatic online tracking of the zero drift can be realized excellently.
Description
Technical field
The invention belongs to weak electric signal and detect and field of measuring technique, the zero point drift that can be used in the Wheatstone bridge class circuit is followed the tracks of and compensation.
Background technology
The application of sensor in detection and field of measuring technique is more and more extensive, and it is the primary link of realizing automatically detection and automatic control.But, the Zero drift in main amplifier of sensor but is puzzlement people's large problem always, it is larger that main cause is that zero point drift is affected by temperature and external environment, and it is the process of non-linear a, random variation, can't provide the function representation that can describe Drift Process, and then can't be to its fine compensation.
People have proposed the whole bag of tricks in order to weaken the impact of zero point drift.Can be divided into hardware circuit compensation and software compensation method according to the condition that realizes.
The hardware compensating method has: the appropriate constant resistance method of series and parallel on brachium pontis; Brachium pontis thermistor compensation method; Bridge guest performer, thermistor compensation method in parallel; Double bridge compensation technique etc.But proofread and correct with hardware circuit mostly have circuit complexity, debug difficulties, precision is low, versatility is poor, the high in cost of production shortcoming, is unfavorable for practical implementation.The more important thing is, in the sensor use procedure, if large environmental change occurs, these class methods then can not realize again compensating.
Software compensation method is that microprocessor and sensor are combined, and takes full advantage of programmable function, uses certain algorithm, and in conjunction with certain hardware circuit the additive error of sensor temperature is revised.The effect of software compensation is better than hardware compensating, and the precision that reaches is higher, and cost is lower.At present, the algorithm of software compensation has curve fitting method, schedule method, inverse function method, statistical method, neural net method etc.
In these methods, curve fitting method, schedule method, inverse function method, needs are preserved mass data, calculated amount is larger.
In " software is removed the discussion of zero point drift side " literary composition of delivering in 2004, provide this use statistical law and removed the method for drift, its basic thought is before gathering beginning and after finishing, carry out respectively data acquisition, then use the method for statistics, find out average and the variance of these two data sets, and then calculate zero point.
Neural net method needs great amount of samples, for particular sensor, trains, and makes it to form a zero point drift mapping network.These class methods are its keys to the training of network, the sensor zero point drift tracking that is not suitable for producing in enormous quantities.
In addition, also have a class automatic zero set (AZS) technology to be used for solving Zero drift in main amplifier, ultimate principle is zeroing circuit of design, is installed in the sensor amplifier circuit front end.Before each the measurement, to the Zero-drift Signal sampling that caused by sensor amplifier and various other factors and preserve, when formal the measurement, from amplify output signal, deduct Zero-drift Signal and obtain actual signal, thereby eliminate the impact of drift.
The automatic zero set (AZS) circuit generally can be divided into digital and analog two types.The principle of digital automatic zero set (AZS) circuit is: measure first Zero-drift Signal before detection, deliver to the drift memory and preserve after the A/D conversion, the signal (wherein comprising Zero-drift Signal) that handle obtains when formally measuring deducts the drift number in the register at zero point.Thereby eliminate the drift impact, obtain correct measurement result.The simulating signal zeroing circuit then is that Zero-drift Signal is stored in capacitor or the sampling holder circuit, deducts its Zero-drift Signal when formally measuring and eliminates the drift impact.These two class methods all only can be measured the zero point drift value in needs, can not realize automatic on-line tracking zero point drift.The more important thing is, in the zero point drift signal, contain much noise, only will be once or the several times measured value as believable zero point drift, also be coarse and not rigorous.
Above-mentioned these methods can be processed a certain class Zero drift in main amplifier well, but can not follow the tracks of zero point well, can not realize the automatic on-line tracking.
The present invention uses kalman filter method to be basic thought, realizes the automatic on-line following function.The present invention only needs less register-stored previous moment sampled data and current time sampled data, calculated amount few, has avoided large data-carrier store, intensive problem, and can realize well zero point drift automatic on-line following function.
Summary of the invention
The objective of the invention is to follow the tracks of and the real-Time Compensation problem for the automatic on-line that solves the sensor zero point drift, propose a kind of sensor zero point drift automatic on-line tracking.
The present invention is achieved through the following technical solutions.
(1) weak voltage signals is processed through amplifying circuit, signal intensity is increased to be suitable for the processing of A/D change-over circuit;
(2) the A/D change-over circuit transfers analog voltage signal to the digital signal that is suitable for using;
(3) designed a kind of improved Kalman filter digital signal has been carried out zero point from motion tracking.Concrete tracking formula is as follows
S
k＝P
k-1+R
K
k＝P
k-1/S
k
x
k＝x
k-1+K
k(z
k-x
k-1)
P
k＝(I-K
k)P
k-1
Wherein, z
kBe k moment voltage actual measured value; x
K-1, x
kBe respectively constantly Zero-tracking value of k-1 and k; P
K-1, P
kBe respectively the constantly error variance of Zero-tracking value of k-1 and k; R is for measuring noise variance; S
kError variance for measured value; K
kBe gain factor.
Description of drawings
Fig. 1 is that voltage signal of the present invention detects and the processing structural representation
Fig. 2 is Zero-tracking subroutine flow chart of the present invention
Fig. 3 is that circuit zero point drift of the present invention is from the motion tracking main program flow chart
Wherein: 1-signal amplification module; The 2-A/D modular converter; The 3-microprocessor module.
Embodiment
With embodiment the present invention is further specified by reference to the accompanying drawings.
Embodiment two
Follow the tracks of catalytic combustion type combustible gas sensor zero point and carry out automatic calibration.
Connect the sensor measuring circuit power supply, start automatic tracking function.At first allow the sensor complete machine in pure air, move 15 minutes.
Claims (4)
1. the method for an automatic tracking circuit zero point drift is characterized in that:
(a) weak voltage signals is processed through amplifying circuit, signal intensity is increased to be suitable for the processing of A/D change-over circuit;
(b) the A/D change-over circuit transfers analog voltage signal to the digital signal that is suitable for using;
(c) designed a kind of improved Kalman filter digital signal has been carried out zero point from motion tracking.Concrete tracking formula is as follows:
S
k＝P
k-1+R
K
k＝P
k-1/S
k
x
k＝x
k-1+K
k(z
k-x
k-1)
P
k＝(I-K
k)P
k-1
Wherein, z
kBe k moment voltage actual measured value; x
K-1, x
kBe respectively constantly Zero-tracking value of k-1 and k; P
K-1, P
kBe respectively the constantly error variance of Zero-tracking value of k-1 and k; R is for measuring noise variance; S
kError variance for measured value; K
kBe gain factor.
2. the method for a kind of automatic tracking circuit zero point drift according to claim 1, it is characterized in that: can automatically determine whether needs Zero-tracking: when voltage signal is operating voltage, stop to follow the tracks of; When voltage signal is inoperative voltage, start track algorithm.
3. the method for a kind of automatic tracking circuit zero point drift according to claim 1 is characterized in that: the A/D change-over circuit has the ability that bipolarity gathers, and realizes upper and lower drift bi-directional tracking at zero point.
4. the method for a kind of automatic tracking circuit zero point drift according to claim 1 is characterized in that: according to the numerical value at zero point that traces into, to carrying out real-time dynamic compensation zero point.
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|---|---|---|---|
| CN2012101037983A CN103364625A (en) | 2012-04-11 | 2012-04-11 | Automatic online tracking method for sensor zero drift |
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|---|---|---|---|
| CN2012101037983A CN103364625A (en) | 2012-04-11 | 2012-04-11 | Automatic online tracking method for sensor zero drift |
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| CN103364625A true CN103364625A (en) | 2013-10-23 |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104820151A (en) * | 2015-05-08 | 2015-08-05 | 天津百利机械装备集团有限公司中央研究院 | Signal calibration method for 100A full-digitalized active power filter |
| CN106662559A (en) * | 2014-02-19 | 2017-05-10 | 马林克罗特医疗产品知识产权公司 | Methods for compensating long term sensitivity drift of electrochemical gas sensors exposed to nitric oxide |
| CN107290391A (en) * | 2017-07-25 | 2017-10-24 | 中国石油化工股份有限公司 | A kind of hydrocarbon exploration device and detection method based on linear semiconductor |
| CN109631975A (en) * | 2018-12-30 | 2019-04-16 | 郑州衡量科技股份有限公司 | A kind of automatic zero point track algorithm for inhibiting sensor zero to float |
| CN110798593A (en) * | 2019-10-24 | 2020-02-14 | 深圳市视特易智能科技有限公司 | Industrial camera temperature drift elimination method |
| CN111006691A (en) * | 2019-11-22 | 2020-04-14 | 普宙飞行器科技（深圳）有限公司 | Sensor drift correction method and device, readable storage medium, electronic device and unmanned aerial vehicle |
| CN112858980A (en) * | 2021-01-13 | 2021-05-28 | 国家电网有限公司华东分部 | Gateway metering abnormity diagnosis method combining sampling and big data |
| CN113125837A (en) * | 2021-04-16 | 2021-07-16 | 奇瑞商用车（安徽）有限公司 | Current sampling zero drift processing method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1580816A (en) * | 2004-05-21 | 2005-02-16 | 清华大学 | Vehicle forward target detecting method |
| JP2008215897A (en) * | 2007-03-01 | 2008-09-18 | Yokogawa Electric Corp | Average current measurement circuit |
| US20080269963A1 (en) * | 2004-06-02 | 2008-10-30 | David William Vos | Systems and Methods for Estimating Position, Attitude, and/or Heading of a Vehicle |
| US20090212995A1 (en) * | 2007-12-20 | 2009-08-27 | Shunguang Wu | Distributed iterative multimodal sensor fusion method for improved collaborative localization and navigation |
| CN102016604A (en) * | 2008-04-21 | 2011-04-13 | 丰田自动车株式会社 | Sensor drift amount estimating device |
| CN102323602A (en) * | 2011-05-30 | 2012-01-18 | 哈尔滨工程大学 | Carrier tracking loop based on self-adaptive second-order Kalman filter and filtering method of carrier tracking loop |
-
2012
- 2012-04-11 CN CN2012101037983A patent/CN103364625A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1580816A (en) * | 2004-05-21 | 2005-02-16 | 清华大学 | Vehicle forward target detecting method |
| US20080269963A1 (en) * | 2004-06-02 | 2008-10-30 | David William Vos | Systems and Methods for Estimating Position, Attitude, and/or Heading of a Vehicle |
| JP2008215897A (en) * | 2007-03-01 | 2008-09-18 | Yokogawa Electric Corp | Average current measurement circuit |
| US20090212995A1 (en) * | 2007-12-20 | 2009-08-27 | Shunguang Wu | Distributed iterative multimodal sensor fusion method for improved collaborative localization and navigation |
| CN102016604A (en) * | 2008-04-21 | 2011-04-13 | 丰田自动车株式会社 | Sensor drift amount estimating device |
| CN102323602A (en) * | 2011-05-30 | 2012-01-18 | 哈尔滨工程大学 | Carrier tracking loop based on self-adaptive second-order Kalman filter and filtering method of carrier tracking loop |
Non-Patent Citations (3)
| Title |
|---|
| 崔伟 等: "基于自适应卡尔曼滤波器的MEMS陀螺零点漂移的研究", 《传感器世界》, vol. 17, no. 01, 31 January 2011 (2011-01-31) * |
| 王雪平 等: "基于时间序列分析方法的FOG随机漂移建模与辨识", 《鱼雷技术》, vol. 15, no. 4, 31 August 2007 (2007-08-31), pages 34 - 37 * |
| 陆芳: "MIMU中陀螺随机漂移建模及Kalman滤波技术研究", 《中国优秀硕士学位论文全文数据库·信息科技辑》, no. 05, 15 November 2007 (2007-11-15) * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11141549B2 (en) | 2014-02-19 | 2021-10-12 | Mallinckrodt Pharmaceuticals Ireland Limited | Systems and methods for compensating long term sensitivity drift of electrochemical gas sensors exposed to nitric oxide |
| CN106662559A (en) * | 2014-02-19 | 2017-05-10 | 马林克罗特医疗产品知识产权公司 | Methods for compensating long term sensitivity drift of electrochemical gas sensors exposed to nitric oxide |
| CN106662559B (en) * | 2014-02-19 | 2019-09-27 | 马林克罗特医疗产品知识产权公司 | For compensating the method for being exposed to the long-term sensitivity drift of nitric oxide production electrochemical gas sensor |
| CN104820151B (en) * | 2015-05-08 | 2017-11-14 | 天津百利机械装备集团有限公司中央研究院 | A kind of signal calibrating method of 100A total digitalizations Active Power Filter-APF |
| CN104820151A (en) * | 2015-05-08 | 2015-08-05 | 天津百利机械装备集团有限公司中央研究院 | Signal calibration method for 100A full-digitalized active power filter |
| CN107290391A (en) * | 2017-07-25 | 2017-10-24 | 中国石油化工股份有限公司 | A kind of hydrocarbon exploration device and detection method based on linear semiconductor |
| CN107290391B (en) * | 2017-07-25 | 2023-03-28 | 中国石油化工股份有限公司 | Oil-gas detector based on linear semiconductor and detection method |
| CN109631975A (en) * | 2018-12-30 | 2019-04-16 | 郑州衡量科技股份有限公司 | A kind of automatic zero point track algorithm for inhibiting sensor zero to float |
| CN110798593A (en) * | 2019-10-24 | 2020-02-14 | 深圳市视特易智能科技有限公司 | Industrial camera temperature drift elimination method |
| CN111006691B (en) * | 2019-11-22 | 2021-06-01 | 普宙飞行器科技（深圳）有限公司 | Sensor drift correction method and device, readable storage medium, electronic device and unmanned aerial vehicle |
| CN111006691A (en) * | 2019-11-22 | 2020-04-14 | 普宙飞行器科技（深圳）有限公司 | Sensor drift correction method and device, readable storage medium, electronic device and unmanned aerial vehicle |
| CN112858980B (en) * | 2021-01-13 | 2021-09-24 | 国家电网有限公司华东分部 | Gateway metering abnormity diagnosis method combining sampling and big data |
| CN112858980A (en) * | 2021-01-13 | 2021-05-28 | 国家电网有限公司华东分部 | Gateway metering abnormity diagnosis method combining sampling and big data |
| CN113125837A (en) * | 2021-04-16 | 2021-07-16 | 奇瑞商用车（安徽）有限公司 | Current sampling zero drift processing method and system |
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Application publication date: 20131023 |