CN105352860A - Data processing method of infrared dust sensor - Google Patents
Data processing method of infrared dust sensor Download PDFInfo
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
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Abstract
The invention discloses a data processing method of an infrared dust sensor. The method at least comprises the following steps: 1) changing dust concentration in experimental environment air in a moisture-proof box and stabilizing the dust concentration for a while; 2) collecting a voltage value of the infrared dust sensor under different stable dust concentration and a value shown by a high-precision dust detector under same environment; 3) performing a fitting analysis on the collected values in the step 2) by software to obtain a function expression; and 4) verifying an experiment result. According to the invention, by optimizing an algorithm, precision of the infrared dust sensor is increased, so that the infrared dust sensor can reach the basically approximate functions of the dust detector, the infrared sensor can substitute for the dust detector, so that cost is reduced.
Description
Technical field
The present invention relates to the voltage characteristic value acquisition technique field of infrared dust sensor, particularly relate to a kind of data processing method of infrared dust sensor.
Background technology
The technology of existing high precision dust detector is use light to irradiate in air suspended particulate substance produces scattering substantially, collect scattered light at a certain special angle simultaneously, obtain the time dependent curve of scattered light intensity, and then microprocessor utilizes related algorithm, draw the particle quantity of different-grain diameter in the equivalent grain size of particle and unit volume thus obtain the concentration value of dust.And the principle of the infrared dust sensor of p also with dust detector be similar to, but due to the infrared ray depth of parallelism not high, energy concentrate etc. shortcoming, so precision and reaction velocity are all weak than dust detector.But simultaneously the cost of dust detector is also high than infrared sensor, and infrared sensor due to not careful its degree of accuracy that result in of self defect itself and algorithm can be poorer than dust sensor.
Summary of the invention
Object of the present invention: the data processing method that a kind of infrared dust sensor is provided, the inaccurate technical matters of precision that prior art causes because of algorithm imperfection in infrared dust sensor detection system can be solved, thus reach and under the requirement of certain precision, replace high precision dust detector to reduce the object of cost with infrared sensor in related application product.
To achieve these goals, technical scheme of the present invention is:
A data processing method for infrared dust sensor, the method at least comprises the steps:
Step 1: change the dust concentration in experimental situation air and make concentration stabilize a period of time of dust in proof cabinet.
Step 2: gather the infrared dust sensor under different stable dust concentrations magnitude of voltage and with the high precision dust detector institute indicating value under environment.
Step 3: collection value software step 2 obtained carries out Fitting Analysis, obtains function expression.
Step 4: confirmatory experiment result.
The data processing method of above-mentioned infrared dust sensor, wherein, described step 1 comprises as follows step by step:
Step 1.1: in proof cabinet, puts into dust detector, infrared dust sensor and air purifier simultaneously, obtaining dust and entering in proof cabinet, closing proof cabinet by burning facial tissue.
Step 1.2: open air purifier, until allow the registration of dust detector be stabilized near nominative testing value, then closes air purifier and waits for 5 minutes and allow that numerical value is stable near nominative testing value.
The data processing method of above-mentioned infrared dust sensor, wherein, in described step 1.2, refers to nominative testing value ± 10ug/l near described nominative testing value.
The data processing method of above-mentioned infrared dust sensor, wherein, described step 2 comprises as follows step by step:
Step 2.1: at numerical stability after about 5 minutes, when 5th ~ 6min, records in next minute, 0.22ms in the cycle each time of all infrared dust sensors, 0.24ms, 0.26ms, the output voltage group of 0.28ms, 0.30ms, 0.32ms and 0.34ms;
Step 2.2: ask the mean value X1_ave of output voltage group within this minute in step 2.1, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, and preserve with text mode.
The data processing method of above-mentioned infrared dust sensor, wherein, in described step 3, described function expression is:
①、X4_ave≤660mv
Y=1.25*X7_ave-0.092*X1_ave-655.899；
②、660mv≤X4_ave≤938mv
Y=0.26*X7_ave+0.221*X1_ave-265.485；
③、938mv≤X4_ave≤1200mv
Y=0.665*X7_ave-0.297*X1_ave-150.579；
④、1200mv≤X4_ave≤1655mv
Y=0.247X7_ave-37.821；
⑤、1655mv≤X4_ave≤2000mv
Y=0.165*X7_ave+192.35；
⑥、X4_ave≥2000mv
Y=0.792*X1_ave-0.692*X7_ave+225.071；
Wherein, Y is dust concentration actual value, X1_ave, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave are the 0.22ms in each cycle in one minute, 0.24ms, the average output voltage class value of 0.26ms, 0.28ms, 0.30ms, 0.32ms and 0.34ms.
The data processing method of above-mentioned infrared dust sensor, wherein, described step 4 comprises as follows step by step:
Step 4.1: by the function expression write single-chip microcomputer in step 3, the dust value shown by dust numerical value and the high precision dust detector of infrared dust sensor display under experiment obtains equivalent environment is again compared.
Step 4.2: the actual deviation value obtained if compare not in allowed band, then re-starts test data of experiment.
Step 4.3: the actual deviation value obtained if compare is in allowed band, then the result being considered as obtaining is reasonable; By repeatedly test and validation, obtain final function expression.
The data processing method of above-mentioned infrared dust sensor, wherein, in described step 4.2 and step 4.3, the allowed band of the actual deviation value that described comparison obtains is ± 20ug/l.
The precision that the present invention improves infrared dust sensor by the optimization of algorithm makes it reach the function be substantially similar to dust detector, and by allowing infrared sensor replace the method for dust detector thus to reduce cost in product.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the data processing method of a kind of infrared dust sensor of the present invention.
Fig. 2 is the predicted data cumulative probability of dust concentration and the graph of a relation of observation data cumulative probability of the data processing method of a kind of infrared dust sensor of the present invention, and wherein, transverse axis is observation data cumulative probability, and the longitudinal axis is predicted data cumulative probability.
Embodiment
Embodiments of the invention are further illustrated below in conjunction with accompanying drawing.
Refer to shown in accompanying drawing 1 and accompanying drawing 2, a kind of data processing method of infrared dust sensor, the method at least comprises the steps:
Step 1: change the dust concentration in experimental situation air and make concentration stabilize a period of time of dust in proof cabinet.
Step 2: gather the infrared dust sensor under different stable dust concentrations magnitude of voltage and with the high precision dust detector institute indicating value under environment.
Step 3: collection value software step 2 obtained carries out Fitting Analysis, obtains function expression.
Step 4: confirmatory experiment result.
Described step 1 comprises as follows step by step:
Step 1.1: in proof cabinet, puts into dust detector, infrared dust sensor and air purifier simultaneously, obtaining dust and entering in proof cabinet, closing proof cabinet by burning the methods such as facial tissue.
Step 1.2: open air purifier, until allow the registration of dust detector be stabilized near nominative testing value, then closedown air purifier is waited for and within about 5 minutes, is allowed numerical value stable near nominative testing value.
In described step 1.2, near described nominative testing value, refer to nominative testing value ± 10ug/l.
Described step 2 comprises as follows step by step:
Step 2.1: at numerical stability after about 5 minutes, when 5th ~ 6min, records in next minute, 0.22ms in the cycle each time of all infrared dust sensors, 0.24ms, 0.26ms, the output voltage group of 0.28ms, 0.30ms, 0.32ms and 0.34ms.
Step 2.2: ask the mean value X1_ave of output voltage group within this minute in step 2.1, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, and preserve with text mode.
In described step 3, described function expression is:
①、X4_ave≤660mv
Y=1.25*X7_ave-0.092*X1_ave-655.899；
②、660mv≤X4_ave≤938mv
Y=0.26*X7_ave+0.221*X1_ave-265.485；
③、938mv≤X4_ave≤1200mv
Y=0.665*X7_ave-0.297*X1_ave-150.579；
④、1200mv≤X4_ave≤1655mv
Y=0.247X7_ave-37.821；
⑤、1655mv≤X4_ave≤2000mv
Y=0.165*X7_ave+192.35；
⑥、X4_ave≥2000mv
Y=0.792*X1_ave-0.692*X7_ave+225.071；
Wherein, Y is dust concentration actual value, X1_ave, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave are the 0.22ms in each cycle in one minute, 0.24ms, the average output voltage class value of 0.26ms, 0.28ms, 0.30ms, 0.32ms and 0.34ms.
Described step 4 comprises as follows step by step:
Step 4.1: by the function expression write single-chip microcomputer in step 3, the dust value shown by dust numerical value and the high precision dust detector of infrared dust sensor display under experiment obtains equivalent environment is again compared.
Step 4.2: the actual deviation value obtained if compare not in allowed band, then re-starts test data of experiment.
Step 4.3: the actual deviation value obtained if compare is in allowed band, then the result being considered as obtaining is reasonable.Carry out continuous test and validation, final function expression can be obtained.
In described step 4.2 and step 4.3, the allowed band of the actual deviation value that described comparison obtains is ± 20ug/l.
When air-borne dust concentration stabilize, connect infrared dust sensor by single-chip microcomputer STM-8 and gather 30 A/D values every 0.02ms in a cycle (0.1s), and converting corresponding magnitude of voltage to by software, the numerical value that setting dust detector shows under same environment is simultaneously that the actual value of prevailing circumstances dust is to be used for demarcating.Because each dust concentration value is to there being 30 A/D values i.e. 30 groups of voltages, but it is too large for single-chip microcomputer internal memory burden to process 30 groups of data, based on the principle of infrared dust sensor, the 0.28ms of every subpulse is its voltage when reaching maximal value, therefore selects to form corresponding relation with actual dust concentration value first three and rear three (the comprising 0.28ms) of the 0.28th millisecond altogether 7 magnitudes of voltage to be one group.In order to reduce error, every 160 data are carried out the mean value that moving window gets these 7 magnitudes of voltage, slip stepping is 0.1 second.By changing dust concentration, the corresponding relation of the voltage group of many group dust concentration numerical value and infrared dust sensor can be obtained, because the voltage swing of this infrared dust sensor and dust concentration are approximately linear correlation substantially.So test data is input to software to carry out linear fit thus the quantitative relational expression obtaining dust concentration size and voltage.
By in gained expression formula write single-chip microcomputer, the dust value shown by dust numerical value and the high precision dust detector of infrared dust sensor display under experiment obtains equivalent environment is again compared, if difference in allowed limits, is considered as successfully, if gap is comparatively large, met the demands by correction factor.
Embodiment 1:
Because the congenital precision of transient response infrared sensor is just not high, therefore the present invention is main it is considered that equilibrium transport answers the approximate of aspect.And the selection of environment is in workable airtight subenvironment (moisture-resistant cabinet), the convenient dust concentration value that changes is measured.For 2 gatherer processes, the concentration of the PM2.5 of 2 times is respectively 500ug/l, 480ug/l.
Step 1: in proof cabinet, put into dust detector and infrared dust sensor and air purifier simultaneously, by burn facial tissue obtain smog and enter in proof cabinet, close proof cabinet, open air purifier, until allow the registration of dust detector be stabilized near nominative testing value 500ug/l (± 10ug/l), close air purifier, then allow numerical value stablize about 5 minutes near this value.When 5th ~ 6min, record in next minute, then all infrared output voltage groups ask the mean value X1_ave of one group of voltage in this minute, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, and preserve with text mode.
Open air purifier, until allow the registration of dust detector be stabilized near nominative testing value 480ug/l (± 10ug/l), close air purifier, then allow numerical value stablize about 5 minutes near this value.When 5th ~ 6min, record in next minute, then all infrared output voltage groups ask the mean value X1_ave of one group of voltage in this minute, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, and preserve with text mode.
Step 2: by that analogy, records the corresponding relation of dust concentration value from 500ug/l to 0ug/l and voltage every the gradient of about about 20ug/l.Owing to having illustrated that concentration value is into linear approximate relationship with voltage in the instructions of this infrared dust sensor, thus, suppose that dust concentration value is Y, voltage array X is X1_ave, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, namely expression formula is:
Y=A*X1_ave+B*X2_ave+C*X3_ave+D*X4_ave+E*X5_ave+F*X6_ave+G*X7_ave+Z
Wherein, A, B, C, D, E, F, G are respectively voltage array X1_ave, the scale-up factor before X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, and Z is constant coefficient.
By the linear analogue of SPSS software to data, A can be obtained, the value of B, C, D, E, F, G and Z thus obtain equation expression formula.
Through the continuous training to data and checking, and in conjunction with the feature of infrared dust sensor self character curve, function is divided into 6 sections to construct, the standard of segmentation is average voltage level and the X4_ave at the 0.28th millisecond of place, constructed fuction is following, and (X1 ~ X7 is one group of magnitude of voltage, Y is the dust concentration value actual value that this group voltage is corresponding, and PRE_1 is the dust concentration predicted value after utility function):
①、X4_ave≤660mv
Y=1.25*X7_ave-0.092*X1_ave-655.899；
②、660mv≤X4_ave≤938mv
Y=0.26*X7_ave+0.221*X1_ave-265.485；
③、938mv≤X4_ave≤1200mv
Y=0.665*X7_ave-0.297*X1_ave-150.579；
④、1200mv≤X4_ave≤1655mv
Y=0.247X7_ave-37.821；
⑤、1655mv≤X4_ave≤2000mv
Y=0.165*X7_ave+192.35；
⑥、X4_ave≥2000mv
Y=0.792*X1_ave-0.692*X7_ave+225.071。
Subordinate list 1 be experiment the result of survey data and software simulation, X1 ~ X7 is one group of magnitude of voltage, and Y is the dust concentration value actual value that this group voltage is corresponding, and PRE_1 is the dust concentration simulation and forecast value after utility function.
Subordinate list 1:
| X1_ave | X2_ave | X3_ave | X4_ave | X5_ave | X6_ave | X7_ave | Actual concentrations value | Simulation and forecast value |
| 2872.13 | 3015.57 | 3088.47 | 3098.29 | 3057.31 | 2976.11 | 2857.83 | 499 | 499.5 |
| 2491.00 | 2617.92 | 2682.41 | 2692.50 | 2654.52 | 2584.38 | 2483.53 | 460 | 458.4 |
| 2388.15 | 2508.19 | 2571.68 | 2581.98 | 2547.94 | 2480.57 | 2383.91 | 447 | 446.3 |
| 2294.50 | 2411.49 | 2474.46 | 2484.18 | 2451.09 | 2386.19 | 2293.47 | 433 | 435.1 |
| 2190.64 | 2303.61 | 2365.14 | 2375.85 | 2346.64 | 2285.68 | 2200.34 | 418 | 417.8 |
| 2074.83 | 2183.80 | 2241.19 | 2253.79 | 2226.71 | 2172.15 | 2090.14 | 403 | 402.8 |
| 1786.33 | 1880.04 | 1931.58 | 1942.36 | 1919.99 | 1873.1 | 1805.66 | 390 | 389.5 |
| 1742.72 | 1834.69 | 1886.11 | 1897.14 | 1876.22 | 1829.76 | 1762.76 | 382 | 382.5 |
| 1668.13 | 1757.04 | 1806.13 | 1816.50 | 1796.20 | 1752.84 | 1687.81 | 370 | 370.1 |
| 1516.61 | 1598.18 | 1643.89 | 1655.45 | 1637.87 | 1598.51 | 1540.22 | 346 | 341.5 |
| 1449.50 | 1526.88 | 1571.14 | 1582.15 | 1566.13 | 1530.86 | 1474.81 | 325 | 325.6 |
| 1405.77 | 1481.99 | 1524.23 | 1535.84 | 1521.25 | 1485.52 | 1432.89 | 310 | 315.4 |
| 1330.85 | 1404.46 | 1446.46 | 1457.43 | 1444.23 | 1410.56 | 1359.73 | 298 | 297.6 |
| 1272.30 | 1341.36 | 1381.89 | 1392.85 | 1380.15 | 1348.91 | 1302.68 | 283 | 283.8 |
| 1179.49 | 1243.69 | 1282.58 | 1292.44 | 1280.29 | 1252.16 | 1209.50 | 262 | 261.1 |
| 1135.9 | 1199.30 | 1235.82 | 1247.11 | 1236.98 | 1208.72 | 1168.01 | 251 | 251.1 |
| 1095.89 | 1155.07 | 1190.84 | 1200.49 | 1191.05 | 1164.44 | 1125.85 | 242 | 242.1 |
| 1061.37 | 1121.06 | 1154.72 | 1165.25 | 1156.21 | 1132.01 | 1094.23 | 228 | 228.5 |
| 1020.26 | 1078.14 | 1111.7 | 1121.92 | 1113.29 | 1089.51 | 1052.90 | 214 | 213.4 |
| 901.315 | 953.364 | 982.471 | 992.327 | 985.623 | 964.976 | 932.260 | 170 | 170.1 |
| 867.996 | 918.465 | 946.739 | 956.254 | 948.732 | 929.342 | 898.940 | 159 | 157.8 |
| 852.722 | 900.545 | 930.242 | 938.78 | 932.603 | 913.527 | 883.764 | 151 | 152.9 |
| 828.644 | 875.456 | 903.162 | 911.970 | 905.636 | 886.108 | 859.104 | 142 | 141.2 |
| 803.830 | 850.169 | 877.132 | 885.617 | 879.466 | 860.950 | 832.756 | 130 | 128.9 |
| 785.850 | 831.302 | 857.872 | 864.721 | 858.677 | 841.335 | 814.579 | 121 | 120.2 |
| 764.730 | 807.995 | 834.606 | 842.157 | 836.595 | 818.193 | 791.011 | 110 | 109.3 |
| 745.322 | 789.907 | 814.541 | 822.604 | 816.441 | 799.957 | 774.384 | 100 | 100.9 |
| 727.288 | 769.655 | 793.481 | 801.951 | 796.810 | 778.984 | 754.508 | 91 | 91.6 |
| 691.269 | 733.054 | 757.721 | 764.632 | 760.664 | 745.809 | 722.028 | 77 | 75.6 |
| 672.433 | 712.115 | 734.500 | 743.595 | 738.412 | 722.679 | 700.325 | 65 | 65.6 |
| 653.181 | 689.197 | 711.492 | 719.182 | 713.669 | 698.592 | 676.706 | 55 | 54.9 |
| 631.994 | 668.570 | 690.008 | 698.111 | 693.249 | 678.906 | 659 | 45 | 46.1 |
| 608.239 | 644.144 | 665.101 | 671.513 | 668.347 | 655.652 | 635.027 | 35 | 34.5 |
| 590.234 | 622.765 | 643.300 | 649.172 | 643.477 | 630.549 | 609.974 | 24 | 24.1 |
| 579.679 | 613.171 | 632.993 | 639.411 | 635.747 | 622.879 | 602.531 | 16 | 16.3 |
| 571.640 | 605.035 | 624.470 | 630.221 | 624.861 | 611.508 | 592.791 | 5 | 4.9 |
As can be seen from subordinate list 1, the absolute value of the knot simulated and actual value difference is basic≤10ug/l, namely thinks that the funtcional relationship obtained is correct effective.
Subordinate list 2 is after SPSS software simulation, the analog result that different function segment is corresponding.
Subordinate list 2:
| Function segment | After adjustment | Standard error | Residual sum of squares (RSS) | Significance test | |
| ① | 1.000 | / | / | 0.000 | 0.000 |
| ② | 0.999 | 0.999 | 1.140 | 11.702 | 0.000 |
| ③ | 1.000 | 0.999 | 1.057 | 3.351 | 0.000 |
| ④ | 0.997 | 0.993 | 2.969 | 52.885 | 0.000 |
| ⑤ | 1.000 | 0.999 | 0.507 | 0.514 | 0.000 |
| ⑥ | 0.999 | 0.999 | 1.637 | 8.038 | 0.000 |
From subordinate list 2, the significance test of 6 sections of functions is all 0.000≤0.05, can think that 6 set up regression equations are all effective.
represent the related coefficient between the independent variable of measured data and dependent variable, more represent that correlativity is better close to 1, as can be seen from table, 6 sections of functions
all be in close proximity to 1, illustrate that the correlativity of measurement data is all well and good.After adjustment
then be through the relation of the predicted value after functional simulation and independent variable, it is also illustrate that the predicted value after simulation is also accurately close to 1 that subordinate list 2 shows.
Then by gained expression formula write single-chip microcomputer, the dust value shown by dust numerical value and the high precision dust detector of infrared dust sensor display under experiment obtains equivalent environment is again compared, through continuous test and validation, find that the displayed value of infrared dust sensor steady-state value and high precision dust measurement is substantially approximate under same environment, percentage error error_percentage≤10%, therefore can think that function is rationally available, realistic.
In sum, the precision that the present invention improves infrared dust sensor by the optimization of algorithm makes it reach the function be substantially similar to dust detector, and by allowing infrared sensor replace the method for dust detector thus to reduce cost in product.
The foregoing is only the preferred embodiments of the present invention; not thereby the scope of the claims of the present invention is limited; every equivalent structure transformation utilizing description of the present invention to do; or directly or indirectly use the technical field being attached to other Related products, be all in like manner included in scope of patent protection of the present invention.
Claims (7)
1. a data processing method for infrared dust sensor, is characterized in that: the method at least comprises the steps:
Step 1: change the dust concentration in experimental situation air and make concentration stabilize a period of time of dust in proof cabinet;
Step 2: gather the infrared dust sensor under different stable dust concentrations magnitude of voltage and with the high precision dust detector institute indicating value under environment;
Step 3: collection value software step 2 obtained carries out Fitting Analysis, obtains function expression;
Step 4: confirmatory experiment result.
2. the data processing method of infrared dust sensor according to claim 1, is characterized in that: described step 1 comprises as follows step by step:
Step 1.1: in proof cabinet, puts into dust detector, infrared dust sensor and air purifier simultaneously, obtaining dust and entering in proof cabinet, closing proof cabinet by burning facial tissue;
Step 1.2: open air purifier, until allow the registration of dust detector be stabilized near nominative testing value, then closes air purifier and waits for 5 minutes and allow that numerical value is stable near nominative testing value.
3. the data processing method of infrared dust sensor according to claim 2, is characterized in that: in described step 1.2, refers to nominative testing value ± 10ug/l near described nominative testing value.
4. the data processing method of infrared dust sensor according to claim 1, is characterized in that: described step 2 comprises as follows step by step:
Step 2.1: at numerical stability after about 5 minutes, when 5th ~ 6min, records in next minute, 0.22ms in the cycle each time of all infrared dust sensors, 0.24ms, 0.26ms, the output voltage group of 0.28ms, 0.30ms, 0.32ms and 0.34ms;
Step 2.2: ask the mean value X1_ave of output voltage group within this minute in step 2.1, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave, and preserve with text mode.
5. the data processing method of infrared dust sensor according to claim 1, is characterized in that: in described step 3, and described function expression is:
①、X4_ave≤660mv
Y＝1.25*X7_ave-0.092*X1_ave-655.899；
②、660mv≤X4_ave≤938mv
Y＝0.26*X7_ave+0.221*X1_ave-265.485；
③、938mv≤X4_ave≤1200mv
Y＝0.665*X7_ave-0.297*X1_ave-150.579；
④、1200mv≤X4_ave≤1655mv
Y＝0.247X7_ave-37.821；
⑤、1655mv≤X4_ave≤2000mv
Y＝0.165*X7_ave+192.35；
⑥、X4_ave≥2000mv
Y＝0.792*X1_ave-0.692*X7_ave+225.071；
Wherein, Y is dust concentration actual value, X1_ave, X2_ave, X3_ave, X4_ave, X5_ave, X6_ave, X7_ave are the 0.22ms in each cycle in one minute, 0.24ms, the average output voltage class value of 0.26ms, 0.28ms, 0.30ms, 0.32ms and 0.34ms.
6. the data processing method of infrared dust sensor according to claim 1, is characterized in that: described step 4 comprises as follows step by step:
Step 4.1: by the function expression write single-chip microcomputer in step 3, the dust value shown by dust numerical value and the high precision dust detector of infrared dust sensor display under experiment obtains equivalent environment is again compared;
Step 4.2: the actual deviation value obtained if compare not in allowed band, then re-starts test data of experiment;
Step 4.3: the actual deviation value obtained if compare is in allowed band, then the result being considered as obtaining is reasonable; By repeatedly test and validation, obtain final function expression.
7. the data processing method of infrared dust sensor according to claim 6, is characterized in that: in described step 4.2 and step 4.3, and the allowed band of the actual deviation value that described comparison obtains is ± 20ug/l.
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