CN105953841A - Humiture detection system based on LabVIEW platform - Google Patents

Abstract

The invention discloses a humiture detection system based on a LabVIEW platform. The system comprises a data acquisition module (1) used for acquiring temperature/humidity data of an environment and creating an original temperature/humidity data array for the temperature/humidity data; an invalid data deletion module (2) used for deleting invalid data from the temperature/humidity data in the original temperature/humidity data array, and forming a valid temperature/humidity data array out of residual temperature/humidity data after the invalid data is deleted; a data fusion module (3) used for performing fusion calculation on the valid temperature/humidity data array so as to obtain temperature/humidity data after fusion; and a data recording module (4) used for storing the temperature/humidity data after the fusion at a specific position of the data recording module (4). The humiture detection system based on the LabVIEW platform has the advantages of higher reliability and accuracy, fewer temperature/humidity measurement errors, flexible development and short period.

Description

A kind of temperature/humiditydetection detection system based on LabVIEW platform

Technical field

The present invention relates to the system of a kind of temperature/Humidity Detection, a kind of temperature based on LabVIEW platform Dust humidity detection system.

Background technology

Temperature/humidity is the fields such as storehouse management, the manufacturing, meteorological observation, scientific research and daily life An important parameter, therefore, temperature/dust humidity detection system experienced by and grows out of nothing, and sends out from simple to complicated Exhibition course, its intelligence degree is more and more higher.But, in current temperature/dust humidity detection system, generally adopt As the detection data in this moment, there is degree of accuracy in the single data gathered in certain moment with temperature/humidity sensor Problem that low, bigger error, poor reliability etc. are not enough.In order to improve the precision of temperature/Humidity Detection, traditional side Method is to use arithmetic mean of instantaneous value method to go to process the data message that sensor obtains, though having certain anti-interference Ability, but this method cannot eliminate the invalid data measuring changing suddenly of environment and produce to measurement error Impact.

Summary of the invention

It is an object of the invention to, it is provided that a kind of temperature/humiditydetection detection system based on LabVIEW platform.This Bright have raising reliability and degree of accuracy, reduction temperature/moisture measurement error and develop feature flexible, that the cycle is short.

Technical scheme: a kind of temperature/humiditydetection detection system based on LabVIEW platform, including:

Data acquisition module, effect is the temperature/humidity data gathering environment, and creates this temperature/humidity data Original temperature/humidity data array；

Invalid data removing module, effect is to the temperature/humidity number in above-mentioned original temperature/humidity data array According to carrying out invalid data deletion, remaining temperature/humidity data is constituted effective temperature/humidity after deleting by invalid data Array of data；

Data fusion module, effect is that effective temperature/humidity data array is carried out fusion calculation, after being merged Temperature/humidity data；

Data recordin module, effect is temperature/humidity data after fusion to be stored in data recordin module specify position.

In aforesaid temperature/humiditydetection detection system based on LabVIEW platform, described invalid data is deleted concrete For: invalid data removing module is to original temperature/humidity data array Z₁=x₁, x₂..., x_n, by following public affairs Formula carries out the meansigma methods of original temperature/humidity data respectivelyResidual delta x_iCalculating with standard deviation sigma:

$\stackrel{\‾}{x}=\frac{1}{n}\underset{i=1}{\overset{n}{\Σ}}{x}_i;$

${\mathrm{\Δx}}_i=x_i-\stackrel{\‾}{x};$

$\mathrm{\σ}=\sqrt{\frac{1}{n-1}\underset{n-1}{\overset{n}{\Σ}}{\mathrm{\Δx}}_i^2};$

After calculating, | Δ x_i| the temperature/humidity data of ＞ 3 σ is invalid data, is deleted.

In aforesaid temperature/humiditydetection detection system based on LabVIEW platform, described fusion calculation specifically, Data fusion module is by effective temperature/humidity data array Z₂=x₁, x₂..., x_m, x_m+1, x_m+2..., x_nIt is divided into y₁And y₂Two groups, and calculate temperature/humidity meansigma methods respectively by following formula With standard deviation δ₁, δ₂:

$\stackrel{\‾}{y_1}=\frac{1}{m}\underset{i=1}{\overset{m}{\Σ}}{x}_i;$

$\stackrel{\‾}{y_2}=\frac{1}{n-m}\underset{i=m+1}{\overset{m}{\Σ}}{x}_i;$

${\mathrm{\δ}}_1=\sqrt{\frac{1}{m-1}\underset{i=1}{\overset{m}{\Σ}}{\mathrm{\Δx}}_i^2};$

${\mathrm{\δ}}_2=\sqrt{\frac{1}{n-m-1}\underset{i=m+1}{\overset{n}{\Σ}}{\mathrm{\Δx}}_i^2};$

Afterwards, then by above-mentionedAnd δ₁, δ₂Substitute in following formula and calculate temperature/humidity number after fusion According to data

In aforesaid temperature/humiditydetection detection system based on LabVIEW platform, described data recordin module will merge Rear temperature/humidity data is converted to character string and creates into array, by this array structure together with time character string dimension Become a two-dimensional array, finally by write spreadsheet functions node, this two-dimensional array is stored in data record Module specifies position.

In aforesaid temperature/humiditydetection detection system based on LabVIEW platform, described data acquisition module includes Temperature/humidity sensor and data collecting card；The effect of described temperature/humidity sensor is by the temperature of environment/wet Degree signal is converted to analog voltage signal, and this analog voltage signal is passed to data collecting card；Described number It is to be amplified above-mentioned analog voltage signal processing and being converted into calculating function according to the effect of capture card Enough digital voltage signals identified, realize in LabVIEW platform the most again voltage signal be converted to environment temperature/ Humidity data, and create original temperature/humidity data array.

In aforesaid temperature/humiditydetection detection system based on LabVIEW platform, when described invalid data increases, logical Crossing batch and delete invalid temperature/humidity data, its method is as follows:

One array R containing only 0,1 element of structure according to the following formula:

$r_{ij}=\left\{\begin{array}{c}0,\left|\mathrm{\&Delta;}{x}_i\right|>3\mathrm{\&sigma;}\\ 1,\left|\mathrm{\&Delta;}{x}_i\right|<3\mathrm{\&sigma;}\end{array}\right.$

Seek temperature/humidity array Y=R*Z₁, and delete 0 element, remaining array element constitutes effective temperature/humidity Array of data Z₂。

Beneficial effect: compared with prior art, detection, on platform based on LabVIEW, is by the present invention System is divided into data acquisition module, invalid data removing module, data fusion module and the mould of data recordin module Massing designs；By this structure, data acquisition module gathers temperature/humidity data continuously and passes to invalid data Removing module carries out data process；By this structure, instead of tradition temperature/humidity sensor and gather in certain moment Single data as the detection data in this moment, be effectively increased accuracy of detection and reduce measurement error, Improve Measurement reliability；And owing to front panel and the test function of LabVIEW platform can be made by oneself by user Justice, then makes to develop more flexible, further shorten the R&D cycle.The present invention collects in process During temperature/humidity data, by original meansigma methods in invalid data removing moduleResidual delta x_iAnd primary standard The calculating of difference σ, will | Δ x_i| the invalid data of ＞ 3 σ is deleted；By which, effectively specify that because of detection environment Sudden change or sensor failure and the invalid data that exists, after deleting this invalid data, effectively prevent it to survey The impact of amount result so that the anti-interference of the present invention is higher, further increases the certainty of measurement of the present invention. In addition, the process of temperature/humidity data is sought arithmetic mean of instantaneous value by the present invention the most simply, but by original temperature After invalid data in/humidity data array is deleted, utilize remaining original temperature/humidity data set up effectively temperature/ Humidity data array, then finally give temperature/humidity data after fusion after this array is carried out grouped data fusion(i.e. measuring temperature data or the humidity data in moment)；With it, temperature/humidity number after the fusion obtained According toMore accurate, error is less, and then further increases the certainty of measurement of the present invention so that the present invention's Reliability is higher.

In order to prove beneficial effect of the present invention, applicant tests as follows:

Experiment 1.12:06 on April 11st, 2016 divides collection one group of original temperature experiments of measuring data, As shown in table 1:

Table 1 original temperature experiments of measuring data

As shown in Table 1, according toCalculate temperature-averaging before merging respectively ValueBe 19.43 DEG C, standard deviation sigma be 0.2065 DEG C.

Before merging, temperature averages and standard deviation substitute intoCalculate and work as T_i＜ 18.811 DEG C or T_iDuring ＞ 20.050 DEG C, these data are invalid data.18.57 DEG C of ＜ 18.811 DEG C in table 1, Therefore these data are invalid data.After deleting this invalid no data, effective temperature data are divided into two groups: each For: 19.53 DEG C, 19.32 DEG C, 19.48 DEG C, 19.38 DEG C, 19.44 DEG C, 19.46 DEG C, 19.57 DEG C, 19.61 DEG C, 19.55 DEG C, 19.32 DEG C, 19.59 DEG C, 19.36 DEG C, 19.28 DEG C, 19.36 DEG C, 19.50 DEG C and 19.57℃,19.32℃,19.34℃,19.50℃,19.59℃,19.59℃,19.57℃,19.53℃,19.1 9℃,19.25℃,19.26℃,19.53℃,19.65℃,19.57℃.Substituted into It is calculated, temperature data after fusionIt is 19.45 DEG C, standard deviationIt it is 0.0080 DEG C.

Experiment conclusion: be capable of judgement and the deletion of invalid data by the calculating of invalid data removing module； And standard deviation after merging front standard deviation sigma by contrast and mergeUnderstand, the temperature data after fusion calculation Precision is higher.

Experiment 2.Table 2 is system temperature/moisture measurement experimental data.

Table 2 system temperature/moisture measurement experimental data

Fig. 2, Fig. 3 are before table 2 temperature and humidity merges and the standard deviation comparison diagram of effective integration respectively, by scheming Understanding, before merging, temperature, the standard deviation of humidity change greatly, and respectively more than 0.10 DEG C with 0.15%RH, After effective integration, standard deviation change is the mildest；From table 2 temperature/moisture measurement experimental data it can be seen that effectively melt After conjunction the maximum error of temperature be 0.0135 DEG C, the maximum error of humidity be 0.0228%RH.

Conclusion: the temperature/humiditydetection detection system of the present invention, reliability and degree of accuracy are greatly improved, Reduce measurement error.

Accompanying drawing explanation

Fig. 1 is the system structure schematic diagram of the present invention；

Fig. 2 is before Temperature fusion and effective integration standard deviation comparison diagram；

Fig. 3 is before humidity merges and effective integration standard deviation comparison diagram.

Reference: 1-data acquisition module, 2-invalid data removing module, 3-data fusion module, 4- Data recordin module, 5-temperature/humidity sensor, 6-data collecting card.

Detailed description of the invention

The present invention is further illustrated with embodiment below in conjunction with the accompanying drawings, but is not intended as limiting the present invention The foundation of system.

Embodiment 1.A kind of temperature/humiditydetection detection system based on LabVIEW platform, its constitute as it is shown in figure 1, Including:

Data acquisition module 1, effect is the temperature/humidity data gathering environment, and creates this temperature/humidity data Original temperature/humidity data array；

Invalid data removing module 2, effect is to the temperature/humidity number in above-mentioned original temperature/humidity data array Carrying out invalid data deletion according to (array element), remaining temperature/humidity data composition is had after deleting by invalid data Effect temperature/humidity data array；

Data fusion module 3, effect is that effective temperature/humidity data array is carried out fusion calculation, is merged Rear temperature/humidity data；

Data recordin module 4, effect is that temperature/humidity data after fusion is stored in data recordin module 4 specific bit Put.

Aforesaid invalid data is deleted particularly as follows: invalid data removing module 2 is to original temperature/humidity data array Z₁=x₁, x₂..., x_n, the meansigma methods of original temperature/humidity data is carried out respectively by following formulaResidual delta x_i Calculating with standard deviation sigma:

$\stackrel{\&OverBar;}{x}=\frac{1}{n}\underset{i=1}{\overset{n}{\&Sigma;}}{x}_i;$

${\mathrm{\&Delta;x}}_i=x_i-\stackrel{\&OverBar;}{x};$

$\mathrm{\&sigma;}=\sqrt{\frac{1}{n-1}\underset{n-1}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i^2};$

After calculating, | Δ x_i| the temperature/humidity data of ＞ 3 σ is invalid data, is deleted.

Aforesaid invalid data delete in LabVIEW platform to realize process as follows:

1. data acquisition module 1 exports raw temperature data array and original wet degrees of data array respectively；

2. " array element addition " function node is utilized to calculate original temperature/humidity data array element sum；

3. " array size " function node is utilized to calculate temperature/several numbers of humidity data array unit；

4. " division " function node is utilized to calculate temperature/humidity data array meansigma methods

5. " subtraction " function node is utilized to calculate temperature/humidity data residual delta x_i；

6. " square ", " array element addition ", " subtracting 1 ", " division ", " square root " letter are utilized Several sections of calculating original temperature/humidity data standard deviation sigma.

Specifically, described fusion calculation is, data fusion module 3 is by effective temperature/humidity data array Z₂=x₁, x₂..., x_m, x_m+1, x_m+2..., x_nIt is divided into y₁And y₂Two groups, and calculate temperature respectively by following formula / humidity meansigma methods With standard deviation δ₁, δ₂:

$\stackrel{\&OverBar;}{y_1}=\frac{1}{m}\underset{i=1}{\overset{m}{\&Sigma;}}{x}_i;$

$\stackrel{\&OverBar;}{y_2}=\frac{1}{n-m}\underset{i=m+1}{\overset{m}{\&Sigma;}}{x}_i;$

${\mathrm{\&delta;}}_1=\sqrt{\frac{1}{m-1}\underset{i=1}{\overset{m}{\&Sigma;}}{\mathrm{\&Delta;x}}_i^2};$

${\mathrm{\&delta;}}_2=\sqrt{\frac{1}{n-m-1}\underset{i=m+1}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i^2};$

Afterwards, then by above-mentioned And δ₁, δ₂Substitute in following formula and calculate temperature/humidity number after fusion According to data(temperature/humidity data after fusionIt is exactly temperature data or the humidity data measuring the moment) and standard deviation(standard deviationThe least certainty of measurement is the highest):

It is as follows that aforesaid fusion calculation realizes process in LabVIEW platform:

1. utilize " fractionation one-dimension array " function node that effective temperature array of data is divided into two groups of data of before and after；

2. before utilizing " array unit number is added ", " array size ", " division " function node to calculate respectively The meansigma methods of rear two groups of temperature datas

3. " subtraction ", " subtracting 1 ", " array element addition ", " square ", " division " function are utilized Node calculate respectively the standard deviation of two groups of data of before and after square

4. " addition ", " multiplication ", " division " function node is utilized to calculate temperature data after fusion

5. after merging, 1.～4. humidity data is in like manner calculated by above-mentioned.

Temperature/humidity data after fusion is converted to character string and creates into array by aforesaid data recordin module 4, This array is constituted together with time character string dimension a two-dimensional array, finally by write electrical form letter This two-dimensional array is stored in data recordin module 4 and specifies position by several sections of points, it is simple to user carries out historical data and looks into Ask or carry out other analysis and research.

Aforesaid data acquisition module 1 includes temperature/humidity sensor 5 and data collecting card 6；Described temperature/ The effect of humidity sensor 5 is that the temperature/moisture signal of environment is converted to analog voltage signal, and by this simulation Voltage signal passes to data collecting card 6；The effect of described data collecting card 6 is by above-mentioned analog voltage letter Number it is amplified processing and being converted into the digital voltage signal that computer is capable of identify that, exists the most again LabVIEW platform realizes voltage signal and is converted to environment temperature/humidity data, and create original temperature/humidity data Array.

When aforesaid invalid data increases, being deleted by batch, its step is as follows:

First, original temperature/humidity data array Z is created₁；

Secondly, original meansigma methods is calculatedResidual delta x_iσ poor with primary standard；

Again, array R containing only 0,1 element is built according to the following formula:

$r_{ij}=\left\{\begin{array}{c}0,\left|\mathrm{\&Delta;}{x}_i\right|>3\mathrm{\&sigma;}\\ 1,\left|\mathrm{\&Delta;}{x}_i\right|<3\mathrm{\&sigma;}\end{array}\right.$

Finally, temperature/humidity array Y=R*Z is sought₁, and delete 0 element, remaining array element constitutes effectively temperature / humidity data array Z₂.In measurement data, along with increasing of independent pendulous frequency, the quantity of invalid data Also can increase therewith, delete invalid data by batch so that the operational efficiency of system is higher.

The batch of above-mentioned invalid data delete in LabVIEW platform to realize process as follows:

1. " multiplication " function node is utilized to calculate 3 σ of temperature data array；

2. " absolute value " function node is utilized to calculate the absolute value of temperature residual error | Δ x_i|；

3. " being less than ", " Boolean to (0,1) is changed " function node is utilized to build containing only 0,1 element Array R；

4. utilize " multiplication " function node by raw temperature data array Z₁Being multiplied with R, invalid data is corresponding Element becomes 0, obtains new array Y；

5. utilization " construction of condition ", " being equal to " function node judge whether the element of array Y is 0, works as unit Delete neutral element when element is 0, otherwise create array；

6. " For " loop structure, " deletion array element " function node is utilized to create effective temperature data number Group；

7. delete invalid humidity data and create effective humidity data array and in like manner 1.～5. carry out by above-mentioned.

Aforesaid LabVIEW Chinese is virtual instrument graphical programming software.

Claims (6)

1. a temperature/humiditydetection detection system based on LabVIEW platform, it is characterised in that including:

Data acquisition module (1), effect is the temperature/humidity data gathering environment, and to this temperature/humidity data Create original temperature/humidity data array；

Invalid data removing module (2), effect is to the temperature in above-mentioned original temperature/humidity data array/wet Degrees of data carries out invalid data deletion, invalid data after deleting remaining temperature/humidity data constituted effectively temperature/ Humidity data array；

Data fusion module (3), effect is that effective temperature/humidity data array is carried out fusion calculation, obtains Temperature/humidity data after fusion；

Data recordin module (4), effect is that temperature/humidity data after fusion is stored in data recordin module (4) Specify position.

2. temperature/humiditydetection detection system based on LabVIEW platform as claimed in claim 1, it is characterised in that Described invalid data is deleted particularly as follows: invalid data removing module (2) is to original temperature/humidity data array Z₁=x₁, x₂..., x_n, the meansigma methods of original temperature/humidity data is carried out respectively by following formulaResidual delta x_i Calculating with standard deviation sigma:

$\stackrel{\&OverBar;}{x}=\frac{1}{n}\underset{i=1}{\overset{n}{\&Sigma;}}{x}_i;$

${\mathrm{\&Delta;x}}_i=x_i-\stackrel{\&OverBar;}{x};$

$\mathrm{\&sigma;}=\sqrt{\frac{1}{n-1}\underset{n-1}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i^2};$

After calculating, | Δ x_i| the temperature/humidity data of ＞ 3 σ is invalid data, is deleted.

3. temperature/humiditydetection detection system based on LabVIEW platform as claimed in claim 1 or 2, its feature Being, described fusion calculation is specifically, data fusion module (3) is by effective temperature/humidity data array Z₂=x₁, x₂..., x_m, x_m+1, x_m+2..., x_nIt is divided into y₁And y₂Two groups, and calculate temperature respectively by following formula / humidity meansigma methodsWith standard deviation δ₁, δ₂:

$\stackrel{\&OverBar;}{y_1}=\frac{1}{m}\underset{i=1}{\overset{m}{\&Sigma;}}{x}_i;$

$\stackrel{\&OverBar;}{y_2}=\frac{1}{n-m}\underset{i=m+1}{\overset{m}{\&Sigma;}}{x}_i;$

${\mathrm{\&delta;}}_1=\sqrt{\frac{1}{m-1}\underset{i=1}{\overset{m}{\&Sigma;}}{\mathrm{\&Delta;x}}_i^2};$

${\mathrm{\&delta;}}_2=\sqrt{\frac{1}{n-m-1}\underset{i-m+1}{\overset{n}{\&Sigma;}}{\mathrm{\&Delta;x}}_i^2};$

Afterwards, then by above-mentionedAnd δ₁, δ₂Substitute in following formula and calculate temperature/humidity number after fusion According to data

4. temperature/humiditydetection detection system based on LabVIEW platform as claimed in claim 1 or 2, its feature It is: temperature/humidity data after fusion is converted to character string and creates into by described data recordin module (4) Array, constitutes a two-dimensional array together with time character string dimension by this array, finally by write electronics This two-dimensional array is stored in data recordin module (4) and specifies position by table function node.

5. temperature/humiditydetection detection system based on LabVIEW platform as claimed in claim 1 or 2, its feature It is: described data acquisition module (1) includes temperature/humidity sensor (5) and data collecting card (6)； The effect of described temperature/humidity sensor (5) is that the temperature/humidity signal of environment is converted to analog voltage letter Number, and this analog voltage signal is passed to data collecting card (6)；The work of described data collecting card (6) Be above-mentioned analog voltage signal is amplified process and be converted into the numeral that computer is capable of identify that Voltage signal, realizes voltage signal the most again in LabVIEW platform and is converted to environment temperature/humidity data, and Create original temperature/humidity data array.

6. temperature/humiditydetection detection system based on LabVIEW platform as claimed in claim 2, it is characterised in that: When described invalid data increases, deleting invalid temperature/humidity data by batch, its method is as follows:

One array R containing only 0,1 element of structure according to the following formula:

$r_{ij}=\left\{\begin{array}{c}0,\left|\mathrm{\&Delta;}{x}_i\right|>3\mathrm{\&sigma;}\\ 1,\left|\mathrm{\&Delta;}{x}_i\right|<3\mathrm{\&sigma;}\end{array}\right.$

Seek temperature/humidity array Y=R*Z₁, and delete 0 element, remaining array element constitutes effective temperature/humidity Array of data Z₂。