CN101344471A - Calibration method for moisture instrument - Google Patents

Calibration method for moisture instrument Download PDF

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CN101344471A
CN101344471A CNA2008100303973A CN200810030397A CN101344471A CN 101344471 A CN101344471 A CN 101344471A CN A2008100303973 A CNA2008100303973 A CN A2008100303973A CN 200810030397 A CN200810030397 A CN 200810030397A CN 101344471 A CN101344471 A CN 101344471A
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calibration
grouping
error
moisture meter
day
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CN101344471B (en
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田志雄
吴桂周
冯志斌
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China Tobacco Guangdong Industrial Co Ltd
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China Tobacco Guangdong Industrial Co Ltd
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Abstract

The invention relates to the field of calibration methods of measuring equipment, aims at solving the technique problem and overcoming the disadvantage that existing water content calibrating methods are not applicable in the processing technic of cigarette grouping, and provides a method that can quickly and accurately calibrate water content gauges in the working process. The improved calibration method of the invention adds a Beta variable, and consequently builds the connection between mutually independent calibration curves, can finish the revision of all curves in daily dynamic calibration only by adjusting the Beta variable, greatly lowers the sample amount in the sampling, raises calibration efficiency and precision and realizes the real-time calibration of linear water content gauges in the processing technic of grouping.

Description

A kind of calibration steps of Moisture Meter
Technical field
The present invention relates to the calibration steps field of measuring equipment, a kind of calibration steps that utilizes historical data measurement of water ratio equipment to be carried out the online Moisture Meter of real time calibration of saying so more specifically.
Background technology
Grouping Processing is the technology of a kind of development of novel or converted products, how to obtain or the parameter of monitoring each process point particularly crucial.Be meant raw material as tobacco grouping Processing technology at different qualities, dissimilar, different qualities, prove the result according to the operation evaluation, require and single grade raw material sensory evaluation result in conjunction with product design, formulate suitable working process parameter, process route, processing mode targetedly, promote the Chinese style cigarette characteristic technology of the level of online processing technology.The primary processing line grouping process technology mainly comprises being mixed of the grouping Processing of grouping Processing, leaf silk of blade and Ye Si etc.
Tobacco manufacturing enterprise usually uses online Moisture Meter to measure the material water ratio of different process point, and modal have two kinds of infrared moisture meter and microwave moisture instruments.Owing to have quick and precisely, range ability is big, can realize online contactless continuous coverage, and can be connected the realization closed-loop control with automatic control system, online Moisture Meter seems more and more important in the technology controlling and process of fiber tow production and quality monitoring, rationally use Moisture Meter simultaneously, the accuracy and reliability that improves its detection control is the emphasis during Moisture Meter is used always.Although the measuring principle difference, online Moisture Meter (to call Moisture Meter in the following text) algorithm in use is roughly similar with the use flow process.
At first utilize the process point material to make the balance sample, then with the Moisture Meter static measurement and write down displayed value x 1, x 2... x i, detect corresponding sample water percentage y with Oven Method simultaneously 1, y 2... y i, utilize least square method that Moisture Meter displayed value and baking oven standard value are done matched curve, determine calibration curve:
Y i＝a iX+b i (i＝1...n)
The then corresponding calibration curve of each grouping, i is a grouping serial number.This is the static demarcating process.
Moisture Meter also needs dynamic calibration through behind the static demarcating in use.In the practical application of Moisture Meter, in the dynamic calibration with reference to quality inspection personnel to sampling moisture check data at goods, according to group classifying with baking oven standard value and corresponding on-the-spot Moisture Meter displayed value contrast, the mean value of getting difference is as foundation, do the corresponding dynamic correction on zero-bit, its data volume is generally about 5.
But tobacco grouping Processing technology is in single process point, mix to have formed in joining such as loosening and gaining moisture, reinforced, leaf silk drying and pipe tobacco and Duoed different materials than full formula cooked mode in the past, the form and the characteristics of material are different, more personalized, the characteristic curve of Moisture Meter also will be done independent demarcation, along with the variation in the external world,, also to need Moisture Meter is carried out dynamic calibration such as temperature, humidity.And dynamic calibration relies on the validity of sampling and the sample size of statistics, and the big more operation element amount of sample size is big.As seen the workload of dynamic calibration is very big in grouping process technology, also obviously have hysteresis quality simultaneously, and the same day, unproductive grouping can not get calibration data, can not check the calibration curve that it is corresponding, exists easily to measure risk.Along with the increase of leaf group storage cabinet and prewired cabinet, there is intermittently feature in the processing of single grouping, and the dynamic calibration of Moisture Meter will lose the data foundation of calibration like this.
In sum, the maintenance independence and the hysteresis quality of each passage of dynamic calibration on the traditional algorithm, such as the degree of accuracy that can't after changing passage, guarantee Moisture Meter to the calibration of No. 1 passage, so just greatly reduce the reliability of Moisture Meter, the complicacy of the instrument dynamic calibration that moisturizes; Though it is that reasonable engineering is used that in actual use that zero-bit is approaching material merges a shared calibration curve, but must sacrifice the precision of a part of grouping like this, even so a process point still keeps five to ten passage, the workload of dynamic calibration remains huge, and the independence of passage causes being difficult to put in order main threads in calibration management, and management is difficulty very.The cooperation of applying more advanced, the more accurate and Moisture Meter calibration steps that can carry out in real time of urgent need of grouping process technology technology.
Summary of the invention
Technical matters to be solved by this invention is the shortcoming that overcomes the existing inapplicable grouping process technology of moisture calibration steps, and providing a kind of can quick and precisely carry out Calibration Method to Moisture Meter in the course of the work.
This patent is realized the foregoing invention purpose by the following technical solutions.
Concrete scheme may further comprise the steps:
1. utilize the process point of measuring in the technology to make many groups calibration sample of different nature;
2. organize calibration samples with the static measurement of Moisture Meter difference is above-mentioned more, and the record displayed value, detect corresponding sample water percentage with Oven Method simultaneously, calculate calibration curve Y by least square method i=κ X+b iParameter κ and b i, Y wherein iBe the calibration value of each grouping, X is the Moisture Meter measured value, and slope κ is the processing characteristics of process point, b iBe the individual character that measure grouping every day of process point, i is a grouping serial number;
3. carry out many days testabilities and measure, and sampling in each grouping, the b that adopts Oven Method to measure iError, and get the mean value correction b of error i
4. write down the b of each grouping of every day i, form historical data base;
It is characterized in that further comprising the steps of:
5. carry out consistency maintenance, one day b in the selection historical data base iBe b Ij, calculate same grouping different time b iWith b IjError and get AME β, with same grouping b iAll unified is b Ij, calibration curve changes to Y i=κ X+b Ij+ β wherein is b IjThe individual character of the grouping of process point, β is the combined influence of external condition to Moisture Meter, j is the number of times of consistency maintenance;
6. move Moisture Meter and carry out actual measurement;
7. do not divide into groups to sample, the β error that adopts Oven Method to measure, and get the mean value correction β of error.
In use need to demarcate calibration curve from the visible online Moisture Meter of said method, corresponding calibration of a grouping of each process point, independent toward each other, when dynamic calibration, revise one by one as required, need to add more passage in the grouping Processing, just calibration method is difficult to effectively use in new model in the past.Calibration steps after the present invention's improvement has increased the β variable, thereby will be separately independently calibration curve connect, when daily dynamic calibration, can finish modification to all curves as long as regulate the β variable, greatly reduce the sample size of sampling, improve calibration efficiency and precision, realized the real time calibration of line Moisture Meter in grouping process technology.
After calibration, in the general daily use, only need to move in the process that Moisture Meter measures in every day, do not divide into groups in real time to sample, the β error that adopts Oven Method to measure, and get the mean value correction β of error, step is 8..Very simple and convenient in the use, workload significantly reduces.
Above-mentioned consistency maintenance need not to carry out every day, carries out once every a period of time, and its reason is b IjNeed not to safeguard every day, and safeguard every day improving having little significance of calibration accuracy.Generally be to be separated by several days, just carry out property maintenance again and again after the certain data volume of accumulative total, can further improve the precision of calibration like this, mainly may further comprise the steps:
9. after measuring every day, in each grouping, sample the b that adopts Oven Method to measure IjError, and get the mean value correction b of error Ij, in historical data base, write down b Ij
10. be separated by in the Moisture Meter operation and carried out one time consistency maintenance in 5 to 30 days, select one day b in the historical data base IjThe b of unified same grouping Ij
In order well to utilize historical data, in the general work process above-mentioned steps 3., 9. in each grouping 4 to 20 data of sampling.Because the quantity that extracts is bigger, adopt Oven Method not carry out real time calibration to Moisture Meter timely, but these data to non real-time calibration play important effect, the consistency maintenance that carries out in 9. as step just is based on these data.
The β that is worth in the daily use of Moisture Meter revises and need not to carry out packet samples, thus step 7., 4 to 20 data of only need not dividing into groups to sample in 8. get final product, and can carry out real-time correction to Moisture Meter by Oven Method.
Step 3. in the fate measured of testability be 5 to 15 days, can guarantee accuracy.
The inventive method with all calibration curves of same process point by original relatively independent become interrelated, present intermittent grouping of producing relatively less for processing capacity and no matter produce, can guarantee the degree of accuracy identical and the reliability of work with other groupings when.Make the baking oven data of each grouping just can reach the effect of data multiplex, be equivalent to increase sample size, strengthen the effective utilization of data and the reliability of dynamic calibration, made each calibration curve can guarantee identical degree of accuracy, thereby improved the measuring accuracy of Moisture Meter.The dynamic calibration of providing convenience, daily servicing is unique parameter with value, simplifies workload.
Description of drawings
Fig. 1 is the grouping process technology process flow diagram in the cigarette manufacturing process;
Fig. 2 is the calibration process flow diagram of the inventive method.
Embodiment
Below be example with the cigarette packet processing technique, the present invention is done describing in further detail in conjunction with the accompanying drawings.
The grouping Processing technology of cigarette is meant the raw material at different qualities, dissimilar, different qualities, prove the result according to the operation evaluation, require and single grade raw material sensory evaluation result in conjunction with product design, formulate suitable working process parameter, process route, processing mode targetedly, promote the Chinese style cigarette characteristic technology of the level of online processing technology.The primary processing line grouping process technology mainly comprises being mixed of the grouping Processing of grouping Processing, leaf silk of blade and Ye Si etc.
As shown in Figure 1, have a plurality of single process point, mix such as loosening and gaining moisture, reinforced, leaf silk drying and pipe tobacco and to join, formed than full formula cooked mode in the past and Duoed many different materials, the form and the characteristics of material are different, more personalized at first will be carried out static demarcating separately to the characteristic curve of Moisture Meter, according to the corresponding respectively grouping prescription of each calibration curve that detects the principle Moisture Meter.
Analyze theoretically, in a process point, the corresponding calibration curve of each grouping prescription has:
Y 1 = a 1 X + b 1 Y 2 = a 2 X + b 2 · · · Y i = a i X + b i The coefficient of correspondence matrix is a 1 b 1 a 2 b 2 · · · a i b i
Make b 1=b 11+ b 12, b 2=b 21+ b 22..., b i=b I1+ b I2Then
Y 1 = a 1 X + b 11 + b 12 Y 2 = a 2 X + b 21 + b 22 · · · Y i = a i X + b i 1 + b i 2 The coefficient of correspondence matrix is a 1 b 11 b 12 a 2 b 21 b 22 · · · a i b i 1 b i 2
Because under the very little situation of moisture fluctuation range, each passage keeps identical slope still can guarantee the detection degree of accuracy of water percentage, in the practical application of Moisture Meter, the different groupings corresponding calibration curve of filling a prescription often adopts identical slope in the same process point, simultaneously coefficient is integrated by following requirement:
Order β = b 12 = b 22 = · · · = b i 2 ; κ = a 1 = a 2 = · · · = a i ;
Y 1 = κX + b 11 + β Y 2 = κX + b 21 + β · · · Y i = κX + b i 1 + β The coefficient of correspondence matrix is κ b 11 β κ b 21 β · · · κ b i 1 β
Can see from matrix of coefficients to draw that originally independent separately irrelevant passage characterizes out tangible individual character and general character, this is the theoretical and Moisture Meter measuring principle of coincidence measurement instrument error also, and the meaning of calibration curve matrix of coefficients is respectively: Y i=κ X+b I1Characterized the characteristic curve of Moisture Meter to the process point material, slope κ is the processing characteristics of process point, b I1Be the individual character of the grouping material of process point, β has characterized the combined influence of external condition to Moisture Meter, is the stochastic error of measuring system, to the unanimity of each grouping.b i=b I1The corresponding traditional zero-bit of+β.After the Moisture Meter algorithm changed, it was unique to see that from matrix of coefficients parameter β becomes, as long as β is revised, it is convenient that dynamic calibration becomes.
Because existing Moisture Meter is not supported algorithm like this, but existing computer system finishes and can realize, as long as the matrix of coefficients of Moisture Meter calibration curve correspondence is based upon host computer, when prescription discharges with slope κ and zero-bit b i=b I1+ β uploads to corresponding Moisture Meter and gets final product.
New algorithm has changed traditional Moisture Meter calibration and has been divided into static demarcating and the two-part flow process of dynamic calibration, and the static state calibrating (is determined slope κ and b I1) and dynamically adjust that (each curve is determined b under the same terms I1) being merged into the self study process of Moisture Meter, daily servicing changes the dynamic calibration process that β is adjusted into.
As shown in Figure 2, illustrate the aforementioned calculation process below.
At first Moisture Meter is carried out static demarcating, promptly use least square method to determine κ, b parameter.In same process point the different grouping material is made into the balance sample, then with the Moisture Meter static measurement and write down displayed value x 1, x 2... x i, detect corresponding sample water percentage y with Oven Method simultaneously 1, y 2Y i, utilize least square method that Moisture Meter displayed value and baking oven standard value are done match: Y i=κ X+b i(i=1...n) wherein i is a grouping serial number, and the then corresponding calibration curve of each grouping (trade mark) carries out static demarcating by the matched curve equation to Moisture Meter.
Moisture Meter also needs dynamic calibration through behind the static demarcating in use.In the practical application of Moisture Meter, quality inspection personnel carries out pick test moisture data to grouping material goods in process of production, with baking oven standard value and corresponding on-the-spot Moisture Meter displayed value contrast, the mean value of getting difference is done the corresponding dynamic correction as foundation on zero-bit according to grouping.As in the first grouping course of work, select four groups of material goods and test, b 1The dynamic calibration process as shown in the table:
Dynamic calibration b 1=b 1-error mean, i.e. b 1=b 1+ 0.52.
As mentioned above, respectively to each the grouping material b 1Carry out dynamically, and with every day calibration process note the formation historical data base, more than be computation process of the prior art, the dynamic calibration of other groupings and record no longer tire out at this and to state.
Next the historical data that has write down is carried out consistency maintenance, the data of below choosing six days describe, as following table (error refers to above-mentioned dynamic calibration error mean in the table):
Figure A20081003039700092
Figure A20081003039700101
On first day basis (following table overstriking display part), make that the β value is zero, error is zero, calculates b iValue, b i=b i-error, as following table:
Figure A20081003039700102
Carry out the consistency maintenance first time, with b in the historical data base iUnification be first day b i(following table overstriking display part), the b during promptly above-mentioned theory is analyzed I1, and the error of calculation again is 0.15-0.47+0.52=0.20 as the error of grouping in second day 1, the error of grouping in the 3rd day 1 is 0.33-0.47+0.52=0.38, and the like:
Figure A20081003039700103
Extract b I1And error, the arrangement above table is following form:
Figure A20081003039700111
Make the β value=-error mean, and error revised: error=former error-β value, revised Error List is as follows:
Figure A20081003039700112
From contrasting first form and last form as seen, after employing β revises, dwindled error amount greatly, in the measurement of follow-up every day, brand is not added up, and the error of calculation obtains average error as the β modified value.Parameter β becomes unique, as long as β is revised, it is convenient that dynamic calibration becomes.The existing computer system of above-mentioned calibration process is finished and can be realized, as long as the matrix of coefficients of Moisture Meter calibration curve correspondence is based upon host computer, when prescription discharges with slope κ and zero-bit b i=b I1+ β uploads to corresponding Moisture Meter and gets final product, i.e. Y i=κ X+b I1+ β.Calculating the β value in the measurement of every day calibrates as shown in the table:
Figure A20081003039700113
Figure A20081003039700121
The calibration steps of the present invention's design has changed traditional Moisture Meter calibration and has been divided into static demarcating and the two-part flow process of dynamic calibration, and the static state calibrating (is determined slope κ and b i) and dynamically adjust that (each curve is determined b under the same terms I1) being merged into the self study process of Moisture Meter, daily servicing changes the dynamic calibration process that β is adjusted into.
b IjNeed not to safeguard every day, and safeguard every day improving having little significance of calibration accuracy.Generally be to be separated by several days, just carry out property maintenance again and again after the certain data volume of accumulative total, can further improve the precision of calibration like this.After measuring every day, sampling in each grouping, the b that adopts Oven Method to measure IjError, and get the mean value correction b of error Ij, in historical data base, write down b Ij4 to 20 data of sampling in each grouping.Because the quantity that extracts is bigger, adopt Oven Method not carry out real time calibration to Moisture Meter timely, these data are calibrated the important effect of playing to non real-time, generally are separated by in the Moisture Meter operation and carry out one time consistency maintenance in 5 to 30 days, select one day b in the historical data base IjThe b of unified same grouping IjEach calibration j increases by 1, the line item of going forward side by side.

Claims (6)

1. the calibration steps of a Moisture Meter may further comprise the steps:
1. utilize the process point of measuring in the technology to make many groups calibration sample of different nature;
2. organize calibration samples with the static measurement of Moisture Meter difference is above-mentioned more, and the record displayed value, detect corresponding sample water percentage with Oven Method simultaneously, calculate calibration curve Y by least square method i=κ X+b iParameter κ and b i, Y wherein iBe the calibration value of each grouping, X is the Moisture Meter measured value, and slope κ is the processing characteristics of process point, b iBe the individual character that measure grouping every day of process point, i is a grouping serial number;
3. carry out many days testabilities and measure, and sampling in each grouping, the b that adopts Oven Method to measure iError, and get the mean value correction b of error i
4. write down the b of each grouping of every day i, form historical data base;
It is characterized in that further comprising the steps of:
5. carry out consistency maintenance, one day b in the selection historical data base iBe b Ij, calculate same grouping different time b iWith b IjError and get AME β, with same grouping b iAll unified is b Ij, calibration curve changes to Y i=κ X+b Ij+ β wherein is b IjThe individual character of the grouping of process point, β is the combined influence of external condition to Moisture Meter, j is the number of times of consistency maintenance;
6. move Moisture Meter and carry out actual measurement;
7. do not divide into groups to sample, the β error that adopts Oven Method to measure, and get the mean value correction β of error.
2. calibration steps according to claim 1 is characterized in that after calibration further comprising the steps of:
8. move in the process that Moisture Meter measures in every day, do not divide into groups in real time to sample, the β error that adopts Oven Method to measure, and get the mean value correction β of error.
3. calibration steps according to claim 2 is characterized in that further comprising the steps of:
9. after measuring every day, in each grouping, sample the b that adopts Oven Method to measure IjError, and get the mean value correction b of error Ij, in historical data base, write down b Ij
10. be separated by in the Moisture Meter operation and carried out one time consistency maintenance in 5 to 30 days, select one day b in the historical data base IjThe b of unified same grouping Ij
4. calibration steps according to claim 3, it is characterized in that step 3., 9. in each the grouping in the sampling 4 to 20 data.
5. calibration steps according to claim 3, it is characterized in that step 7., 4 to 20 data of not dividing into groups to sample in 8..
6. calibration steps according to claim 1, it is characterized in that step 3. in the fate measured of testability be 5 to 15 days.
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Cited By (12)

* Cited by examiner, † Cited by third party
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CN101806683A (en) * 2010-04-01 2010-08-18 云南省烟草烟叶公司 Manufacturing of tobacco water content detection standard sample and oven calibration method
CN101408492B (en) * 2008-08-26 2010-12-08 广东中烟工业有限责任公司 Method for calibrating on-line moisture instrument in cigarette packet processing technique
CN102095831A (en) * 2010-06-24 2011-06-15 龙岩烟草工业有限责任公司 Moisture meter management method and system
CN102183474A (en) * 2011-02-15 2011-09-14 北京首钢自动化信息技术有限公司 Calibration method of infrared moisture meter
CN102323277A (en) * 2011-08-04 2012-01-18 中国电子科技集团公司第四十一研究所 Algorithm for eliminating influence of metal exterior decoration on tobacco rod moisture density measurement
CN103336015A (en) * 2013-07-18 2013-10-02 北京紫东科技有限公司 Method for detecting moisture content of crude tobacco bales by using microwave moisture meter on line
CN105842191A (en) * 2016-06-16 2016-08-10 泉州装备制造研究所 On-line spreading rate and uniformity detecting device and method for reconstituted tobacco
CN109960817A (en) * 2017-12-22 2019-07-02 中核核电运行管理有限公司 A method of based on the online survey tritium for sequentially measuring dynamic error calculating method
CN112255189A (en) * 2020-10-12 2021-01-22 河南中烟工业有限责任公司 Tobacco material online moisture meter adjusting method and device
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CN101408492B (en) * 2008-08-26 2010-12-08 广东中烟工业有限责任公司 Method for calibrating on-line moisture instrument in cigarette packet processing technique
CN101806683A (en) * 2010-04-01 2010-08-18 云南省烟草烟叶公司 Manufacturing of tobacco water content detection standard sample and oven calibration method
CN101806683B (en) * 2010-04-01 2013-03-20 云南省烟草烟叶公司 Manufacturing of tobacco water content detection standard sample and oven calibration method
CN102095831A (en) * 2010-06-24 2011-06-15 龙岩烟草工业有限责任公司 Moisture meter management method and system
CN102183474A (en) * 2011-02-15 2011-09-14 北京首钢自动化信息技术有限公司 Calibration method of infrared moisture meter
CN102323277A (en) * 2011-08-04 2012-01-18 中国电子科技集团公司第四十一研究所 Algorithm for eliminating influence of metal exterior decoration on tobacco rod moisture density measurement
CN103336015A (en) * 2013-07-18 2013-10-02 北京紫东科技有限公司 Method for detecting moisture content of crude tobacco bales by using microwave moisture meter on line
CN105842191A (en) * 2016-06-16 2016-08-10 泉州装备制造研究所 On-line spreading rate and uniformity detecting device and method for reconstituted tobacco
CN109960817A (en) * 2017-12-22 2019-07-02 中核核电运行管理有限公司 A method of based on the online survey tritium for sequentially measuring dynamic error calculating method
CN109960817B (en) * 2017-12-22 2023-08-15 中核核电运行管理有限公司 Online tritium measurement method based on sequential measurement dynamic error calculation method
CN112255189A (en) * 2020-10-12 2021-01-22 河南中烟工业有限责任公司 Tobacco material online moisture meter adjusting method and device
CN112946188A (en) * 2021-01-26 2021-06-11 天地（常州）自动化股份有限公司 Downhole sensor calibration method, device, equipment and medium
CN113466405A (en) * 2021-06-07 2021-10-01 湖北中烟工业有限责任公司 Correction method and correction device for online moisture meter
CN113960256A (en) * 2021-10-21 2022-01-21 上海朝辉压力仪器有限公司 Temperature compensation method for water content instrument
CN113960256B (en) * 2021-10-21 2023-11-21 上海朝辉压力仪器有限公司 Temperature compensation method of water meter

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