CN105203439A - Air purification control method and device - Google Patents
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- CN105203439A CN105203439A CN201510579638.XA CN201510579638A CN105203439A CN 105203439 A CN105203439 A CN 105203439A CN 201510579638 A CN201510579638 A CN 201510579638A CN 105203439 A CN105203439 A CN 105203439A
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- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000004887 air purification Methods 0.000 title abstract description 10
- 238000005259 measurement Methods 0.000 claims abstract description 49
- 239000013618 particulate matter Substances 0.000 claims abstract description 43
- 238000004140 cleaning Methods 0.000 claims abstract description 21
- 238000005070 sampling Methods 0.000 claims abstract description 11
- 238000012512 characterization method Methods 0.000 claims description 45
- 239000002245 particle Substances 0.000 claims description 34
- 238000000746 purification Methods 0.000 claims description 17
- 230000003287 optical effect Effects 0.000 claims description 13
- 238000001514 detection method Methods 0.000 claims description 11
- 238000013481 data capture Methods 0.000 claims description 7
- 230000001932 seasonal effect Effects 0.000 claims description 2
- 230000008859 change Effects 0.000 abstract description 6
- 230000008569 process Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000001914 filtration Methods 0.000 description 8
- 241001269238 Data Species 0.000 description 2
- 239000003463 adsorbent Substances 0.000 description 1
- 230000003750 conditioning effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 239000010419 fine particle Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003071 parasitic effect Effects 0.000 description 1
- 231100000614 poison Toxicity 0.000 description 1
- 230000007096 poisonous effect Effects 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
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Abstract
An air purification control method and device are disclosed. The air purification control method includes: acquiring sampling data of a particulate matter sensor; forming a time series of measurements from the sampled data; calculating a time-series average value of a predetermined number of items as a characteristic value of the measured value according to the time-series item-by-item progression; and starting/stopping the air cleaning device according to the characteristic value of the measured value. The air purification control method and the device eliminate the violent fluctuation of the measured data and accurately reflect the actual content and the change of the particulate matters.
Description
Technical field
The present invention relates to purification of air control field, more specifically, relate to purification of air control method and device.
Background technology
Along with people more and more pay close attention to quality of life, detection and the forecast of air quality also enter daily life.An importance of air quality is size and the content thereof of particle.Fine particle in air comprises the particle that diameter is less than or equal to 2.5 microns, is called PM2.5.Because PM2.5 can be suspended in air for a long time, and surface area is large, active strong, easily carries poisonous and harmful substance, therefore larger on the impact of health and air quality.
Particulate matter sensors is adopted to measure size and the content thereof of the particle in air.Particulate matter sensors, such as based on optical principle, obtains the information of particle through scattering during air by detection light.But often there is violent fluctuation in the measurement data of particulate matter sensors.The big ups and downs of measurement data may derive from many aspects, such as the thermonoise of the light activated element of sensor self, for the treatment of the filtering performance defect of the micro-control unit MCU of detection signal, and/or the dust concentration complex distribution etc. of sensor environment for use.
Due to the aerial distribution character of particle, the diffusion of particle is roughly mild process.The big ups and downs of the measurement data of particulate matter sensors cause being difficult to obtain reliable measured value.Such as, the numerical value at the crest place of measurement data may also exist larger deviation with the particle concentration of reality.
Therefore, the accuracy improving particulate matter sensors measurement result is further expected in the application.
Summary of the invention
In view of this, the invention provides a kind of filtering method can eliminating the unusual fluctuations of measurement data, for particulate matter sensors to improve the accuracy of measurement result.
According to a first aspect of the invention, provide a kind of purification of air control method, it is characterized in that, the method comprises: the sampled data obtaining particulate matter sensors; The time series of measured value is formed according to described sampled data; Mean value when passing according to time series the sequence calculating predetermined item number item by item, as the characterization value of measured value; And according to the characterization value start/stop air cleaning unit of measured value.
Preferably, the step obtaining the sampled data of particulate matter sensors comprises: with the measurement data of very first time interval sampling particulate matter sensors, to obtain multiple sampled data; And form the seasonal effect in time series step of measured value and comprise: the first mean value calculating multiple sampled data with second time interval, second interval greater than very first time interval, and wherein, the sequence of the first mean value is as the time series of measured value.
Preferably, the step calculating mean value during the sequence of predetermined item number comprises: the mean value during sequence of the predetermined item number formed together with multinomial before by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or mean value during the sequence of the predetermined item number formed together with multinomial afterwards by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or mean value during the sequence of the predetermined item number formed together with currentitem and front and back are multinomial separately, as the characterization value of the measured value in the currentitem corresponding time period.
Preferably, when calculating the sequence of predetermined item number mean value step after, also comprise: the measurement result adopting standard detection instrument, by the characterization value of measured value adjustment data gain, thus obtain the calibration value of measurement data.
Preferably, described particulate matter sensors comprises optical transmitting set and photoelectric detector, detects the particle content in air according to optical principle.
Preferably, the particle that described particulate matter sensors detects is the PM2.5 in air.
According to a second aspect of the invention, provide a kind of device for purification of air, it is characterized in that, this device comprises: data capture unit, for obtaining the sampled data of particulate matter sensors; First computing unit, for forming the time series of measured value according to described sampled data; Second computing unit, mean value during for passing the sequence calculating predetermined item number item by item according to time series, as the characterization value of measured value; Control module: according to the characterization value start/stop air cleaning unit of measured value.
Preferably, described data capture unit also for: with the measurement data of very first time interval sampling particulate matter sensors, to obtain multiple sampled data; Described first computing unit is also for the first mean value calculating multiple sampled data with second time interval, and second interval greater than very first time interval, and wherein, the sequence of the first mean value is as the time series of measured value.
Preferably, described second computing unit is used for: the mean value during sequence of the predetermined item number formed together with multinomial before by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or mean value during the sequence of the predetermined item number formed together with multinomial afterwards by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or mean value during the sequence of the predetermined item number formed together with currentitem and front and back are multinomial separately, as the characterization value of the measured value in the currentitem corresponding time period.
Preferably, described device also comprises alignment unit, for: the measurement result adopting standard detection instrument, by the characterization value of measured value adjustment data gain, thus obtains the calibration value of measurement data.
Preferably, described particulate matter sensors comprises optical transmitting set and photoelectric detector, detects the particle content in air according to optical principle.
Preferably, the particle that described particulate matter sensors detects is the PM2.5 in air.
According to embodiments of the invention, mean value when described purification of air control method passes according to the time series of sampled data the sequence calculating predetermined item number item by item, as the characterization value of measured value.Even if do not adopt conditioning sensor circuit, just can be solved the problem of the measurement result unusual fluctuations of particle content by filtering process, thus the accuracy of measurement result can be improved, and reflect the actual change of particle content exactly.
In a preferred embodiment, characterization value is multiplied by multiple, to adjust data gain, thus obtains the calibration value of measurement data.This preferred embodiment can reflect the actual content of particle exactly.
In the air cleaning system comprising particulate matter sensors and air purification control device, this purification of air control method can avoid the frequency of air cleaning unit to start and stop, and extends electrically and the serviceable life of mechanical part.
Accompanying drawing explanation
By referring to the description of accompanying drawing to the embodiment of the present invention, above-mentioned and other objects, features and advantages of the present invention will be more clear.
Fig. 1 illustrates the schematic diagram of particulate matter sensors;
Fig. 2 illustrates the schematic block diagram of the air cleaning system adopting particulate matter sensors;
Fig. 3 illustrates the measurement data time history plot of particulate matter sensors;
Fig. 4 illustrates the schematic block diagram of air purification control device according to an embodiment of the invention;
Fig. 5 illustrates the process flow diagram of purification of air control method according to an embodiment of the invention;
Fig. 6 illustrates the measurement data time history plot of purification of air control method acquisition according to an embodiment of the invention.
Embodiment
In hereafter details of the present invention being described, detailedly describe some specific detail sections.Do not have the description of these detail sections can understand the present invention completely for a person skilled in the art yet.In order to avoid obscuring essence of the present invention, known method, process, flow process, element and circuit do not describe in detail.It should be understood by one skilled in the art that the accompanying drawing provided at this is all for illustrative purposes, and accompanying drawing is not necessarily drawn in proportion.Unless the context clearly requires otherwise, similar words such as " comprising ", " comprising " otherwise in whole instructions and claims should be interpreted as the implication that comprises instead of exclusive or exhaustive implication; That is, be the implication of " including but not limited to ".
In describing the invention, it is to be appreciated that term " first ", " second " etc. are only for describing object, and instruction or hint relative importance can not be interpreted as.In addition, in describing the invention, except as otherwise noted, the implication of " multiple " is two or more.
Fig. 1 illustrates the schematic diagram of particulate matter sensors.Particulate matter sensors 100 comprise by outer wall 101 around sampler chamber.Well heater 102, optical transmitting set 104 and photoelectric detector 106 are set in sampler chamber.Sampler chamber has air intake and air out.Well heater 102 is such as resistance wire.When well heater 102 works, heating makes air-flow rise, and extraneous air enters sampler chamber.
Optical transmitting set 104 is such as LED, and can attach light shield 105, and to realize the orientation of light beam, and the pollutant reduced in air is to the pickup of optical transmitting set 104.Scattered light is produced after the particle scattering of the light that optical transmitting set 104 produces in air.Photoelectric detector 106 is such as photodiode.Photoelectric detector 106 receiving scattered light, according to diameter and the content of the intensity determination particle of scattered light.Such as, if do not comprise particle in air, then the detection signal of photoelectric detector 106 is high level.If the too high levels of particle, then all light all may by particulate adsorbent, and photoelectric detector 106 just can't detect scattered light, thus detection signal is low level.
Photoelectric detector 106 is arranged in light shield 107, to reduce the impact of the parasitic light in air.The front end of photoelectric detector 106 arranges lens 108, forms converging light, to improve detection sensitivity at the light-sensitive surface of photoelectric detector 106.
Particulate matter sensors is as shown in Figure 1 widely used in air cleaning system.Fig. 2 illustrates the schematic block diagram of the air cleaning system adopting particulate matter sensors.Particulate matter sensors 100 detects diameter and the content of the particle in air, produces measurement data.After this measurement data processes via air purification control device 200, obtain the measured value of particle, then measured value is provided to display 301 to show, or be provided to air cleaning unit 302, to control the startup of air cleaning unit 302, stopping and/or running parameter, thus effectively improve air quality.
Usually, if particle sensor detects that particle content is too high, then can start air cleaning unit 302, and on display 301 display alarm information.If particle sensor detects that particle content returns to normal level, then can stop air cleaning unit 302, and show particle content information on display 301.
But as mentioned above, often there is violent fluctuation in the measurement data of particulate matter sensors 100.Fig. 3 illustrates the measurement data time history plot of particulate matter sensors.Particulate matter sensors 100 being placed on average grain thing content is tens ug/m
3environment in, 10 minutes inner sensor data have and break through 25ug/m 2 times
3.
The big ups and downs of the measurement data of particulate matter sensors cause being difficult to obtain reliable measured value.Such as, the numerical value at the crest place of measurement data may also exist larger deviation with the particle content of reality.
If according to the measurement data start/stop air cleaning unit 302 of particulate matter sensors 100, then frequent starting and the stopping of air cleaning unit 302 may be caused, cause shorten the serviceable life of the electric of air cleaning unit 302 and mechanical part and even damage.
Fig. 4 illustrates the schematic block diagram of air purification control device 200 according to an embodiment of the invention.This air cleaning unit 200 comprises: data capture unit 201, first computing unit 202, second computing unit 203 and control module 204.
Data capture unit 201 is for obtaining the sampled data of particulate matter sensors.First computing unit 202 is for forming the time series of measured value according to described sampled data.Mean value second computing unit 203 is for passing the sequence calculating predetermined item number item by item during according to time series, as the characterization value of measured value.Control module 204 is according to the characterization value start/stop air cleaning unit of measured value.
Data capture unit 201 also for: with the measurement data of very first time interval sampling particulate matter sensors, to obtain multiple sampled data.First computing unit 202 is also for the first mean value calculating multiple sampled data with second time interval, and second interval greater than very first time interval, and wherein, the sequence of the first mean value is as the time series of measured value.
The mean value during sequence of the second computing unit 203 for: the predetermined item number formed together with multinomial before by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or mean value during the sequence of the predetermined item number formed together with multinomial afterwards by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or mean value during the sequence of the predetermined item number formed together with currentitem and front and back are multinomial separately, as the characterization value of the measured value in the currentitem corresponding time period.
In a preferred embodiment, this air cleaning unit 200 also comprises alignment unit 205, for: the measurement result adopting standard detection instrument, by the characterization value of measured value adjustment data gain, thus obtains the calibration value of measurement data.
Fig. 5 illustrates the process flow diagram of purification of air control method according to an embodiment of the invention.This purification of air control method comprises with the measurement data of very first time interval sampling particulate matter sensors, then to the measurement data that continuous print sampled result is carried out moving average to obtain after filtering.In this application, the method for moving average obtains the time series of measured value, and mean value when passing according to time series the sequence calculating certain item number item by item, as the method for the characterization value of currentitem.
Such as, in the air purification control device 200 shown in Fig. 2, perform each step of this purification of air control method.
In this embodiment, the filtration module of sensor internal to be averaged filtering process to the data obtained in the 1S time, and the data that namely 1S time inner sensor exports are the same, sampling should be carried out in 1S sensing data.Therefore, the time series of the measured value of this embodiment is the time series according to a data acquisition per second.
Hereafter be spaced apart 1S to illustrate for the very first time, this purification of air control method comprises following multiple step.
In step S01, with very first time interval sampling measurement data.The very first time is spaced apart 0.5-1S, is preferably 1S.
In step S02, with the first mean value of the second time interval calculating sampling data.Second time interval was 2.5-5S, was preferably 5S.Such as, in second time interval, calculate the mean value of continuous print 5 sampled datas, as the first mean value.The sequence of the first mean value is as the time series of measured value.
In step S03, in the time series of measured value, calculate the mean value that continuous print is multinomial, as the second mean value.Such as, described multinomial be 6-12 item, be preferably 6.Second mean value is as characterization value after filtering.Such as, by current 5S and the mean value of continuous 6 to form together with 5 before, as the characterization value of current 5S, or by current 5S and the mean value of continuous 6 to form together with 5 afterwards, as the characterization value of current 5S, or, by current 5S and front and back multinomial continuous 6 of forming together separately, as the characterization value of current 5S.
In step S04, according to the characterization value start/stop air cleaning unit of measured value.
The example of the method is as shown in table 1.35 sampled datas with the very first time interval sampling of 1S are shown in Table 1.Then, with the first mean value of second time interval computation and measurement data of 5S, the first mean value of every 5 measurement data is calculated.The sequence of the first mean value is as the time series of measured value.Such as, the first mean value illustrated in Table 1 is respectively 16,16,17,15,15,15,16.Then, in the time series of measured value, calculate the mean value of continuous print 6, as the second mean value in 5S.Such as, the second mean value illustrated in Table 1 is respectively 16,16.Result obtains 2 characterization values of measurement data, and within first 5S time period of sequence number 1 to 5, first characterization value is 16, and in second 5S time period of sequence number 6 to 10, second characterization value is 16.
Table 1 process sensor data sample signal table
As preferred step, can further to the characterization value adjustment data gain of measurement data.Wherein, the measurement numerical value of reference standard instrument, amplifies several times (such as 6 times), to obtain the calibration value of the actual content representing particle by the characterization value of measurement data.
Fig. 6 illustrates the measurement data time history plot of purification of air control method acquisition according to an embodiment of the invention.When testing, reducing the particle content in sampler chamber gradually, using the detector of standard and particulate matter sensors as shown in Figure 1 to measure simultaneously.
In air purification control device 200 as shown in Figure 2, perform each step of filtering method according to an embodiment of the invention, thus obtain the characterization value of measurement data.Then characterization value is multiplied by multiple, to adjust data gain, thus obtains the calibration value of measurement data.
In figure 6, the pick up calibration value that the measurement data of detector and method according to the present invention obtain is depicted as curve.Can see, the change that the data of the two reflect the particle content in sampler chamber all exactly warms up, and namely reduces gently in time.Purification of air control method eliminates the big ups and downs of measurement data according to an embodiment of the invention, reflects actual content and the change thereof of particle exactly.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, to those skilled in the art, the present invention can have various change and change.All do within spirit of the present invention and principle any amendment, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (12)
1. a purification of air control method, is characterized in that, the method comprises:
Obtain the sampled data of particulate matter sensors;
The time series of measured value is formed according to described sampled data; Mean value when passing according to time series the sequence calculating predetermined item number item by item, as the characterization value of measured value; And
According to the characterization value start/stop air cleaning unit of measured value.
2. method according to claim 1, is characterized in that, the step obtaining the sampled data of particulate matter sensors comprises: with the measurement data of very first time interval sampling particulate matter sensors, to obtain multiple sampled data; And the seasonal effect in time series step forming measured value comprises: the first mean value calculating multiple sampled data with second time interval, second interval greater than very first time interval,
Wherein, the sequence of the first mean value is as the time series of measured value.
3. method according to claim 1, is characterized in that, the step calculating mean value during the sequence of predetermined item number comprises:
The mean value during sequence of the predetermined item number formed together with multinomial before by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or
The mean value during sequence of the predetermined item number formed together with multinomial afterwards by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or
The mean value during sequence of the predetermined item number formed together with currentitem and front and back are multinomial separately, as the characterization value of the measured value in the currentitem corresponding time period.
4. method according to claim 1, is characterized in that, when calculating the sequence of predetermined item number mean value step after, also comprise:
Adopt the measurement result of standard detection instrument, by the characterization value of measured value adjustment data gain, thus obtain the calibration value of measurement data.
5. method according to claim 1, is characterized in that, described particulate matter sensors comprises optical transmitting set and photoelectric detector, detects the particle content in air according to optical principle.
6. method according to claim 1, is characterized in that, the particle that described particulate matter sensors detects is the PM2.5 in air.
7. for a device for purification of air, it is characterized in that, this device comprises:
Data capture unit, for obtaining the sampled data of particulate matter sensors;
First computing unit, for forming the time series of measured value according to described sampled data;
Second computing unit, mean value during for passing the sequence calculating predetermined item number item by item according to time series, as the characterization value of measured value;
Control module: according to the characterization value start/stop air cleaning unit of measured value.
8. device according to claim 7, is characterized in that, described data capture unit also for:
With the measurement data of very first time interval sampling particulate matter sensors, to obtain multiple sampled data;
Described first computing unit is also for the first mean value calculating multiple sampled data with second time interval, and second interval greater than very first time interval, and wherein, the sequence of the first mean value is as the time series of measured value.
9. device according to claim 7, is characterized in that, described second computing unit is used for:
The mean value during sequence of the predetermined item number formed together with multinomial before by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or
The mean value during sequence of the predetermined item number formed together with multinomial afterwards by currentitem, as the characterization value of the measured value in the currentitem corresponding time period; Or
The mean value during sequence of the predetermined item number formed together with currentitem and front and back are multinomial separately, as the characterization value of the measured value in the currentitem corresponding time period.
10. device according to claim 7, is characterized in that, described device also comprises alignment unit, for:
Adopt the measurement result of standard detection instrument, by the characterization value of measured value adjustment data gain, thus obtain the calibration value of measurement data.
11. devices according to claim 7, is characterized in that, described particulate matter sensors comprises optical transmitting set and photoelectric detector, detect the particle content in air according to optical principle.
12. devices according to claim 7, is characterized in that, the particle that described particulate matter sensors detects is the PM2.5 in air.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106802269A (en) * | 2017-03-24 | 2017-06-06 | 广东美的制冷设备有限公司 | Dust sensor adjusting zero method, device and purifier for purifier |
| CN113670785A (en) * | 2021-09-27 | 2021-11-19 | 北京伟瑞迪科技有限公司 | Particulate matter concentration monitoring method, device, equipment and storage medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11230887A (en) * | 1998-02-12 | 1999-08-27 | Kao Corp | Method for measuring particle size |
| CN101275896A (en) * | 2007-03-30 | 2008-10-01 | 北京亚都室内环保科技股份有限公司 | Coenobium concentration sensor, detecting system as well as method |
| US20110120096A1 (en) * | 2008-07-16 | 2011-05-26 | Horiba, Ltd. | Particulate matter measurement device |
| CN102087125A (en) * | 2010-11-29 | 2011-06-08 | 深圳市赛纳威环境仪器有限公司 | Air purification efficiency detection device |
| CN202522501U (en) * | 2012-05-02 | 2012-11-07 | 张远志 | Air particle matter monitoring system |
| CN102902203A (en) * | 2012-09-26 | 2013-01-30 | 北京工业大学 | Time series prediction and intelligent control combined online parameter adjustment method and system |
| CN103257097A (en) * | 2012-02-16 | 2013-08-21 | 株式会社堀场制作所 | Particle analytical device and method |
| CN103906893A (en) * | 2011-07-12 | 2014-07-02 | 因格瑞恩股份有限公司 | Method for simulating fractional multi-phase/multi-component flow through porous media |
| CN104458824A (en) * | 2014-12-23 | 2015-03-25 | 冠礼控制科技（上海）有限公司 | High-precision concentration meter and measuring method thereof |
-
2015
- 2015-09-11 CN CN201510579638.XA patent/CN105203439B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH11230887A (en) * | 1998-02-12 | 1999-08-27 | Kao Corp | Method for measuring particle size |
| CN101275896A (en) * | 2007-03-30 | 2008-10-01 | 北京亚都室内环保科技股份有限公司 | Coenobium concentration sensor, detecting system as well as method |
| US20110120096A1 (en) * | 2008-07-16 | 2011-05-26 | Horiba, Ltd. | Particulate matter measurement device |
| CN102087125A (en) * | 2010-11-29 | 2011-06-08 | 深圳市赛纳威环境仪器有限公司 | Air purification efficiency detection device |
| CN103906893A (en) * | 2011-07-12 | 2014-07-02 | 因格瑞恩股份有限公司 | Method for simulating fractional multi-phase/multi-component flow through porous media |
| CN103257097A (en) * | 2012-02-16 | 2013-08-21 | 株式会社堀场制作所 | Particle analytical device and method |
| CN202522501U (en) * | 2012-05-02 | 2012-11-07 | 张远志 | Air particle matter monitoring system |
| CN102902203A (en) * | 2012-09-26 | 2013-01-30 | 北京工业大学 | Time series prediction and intelligent control combined online parameter adjustment method and system |
| CN104458824A (en) * | 2014-12-23 | 2015-03-25 | 冠礼控制科技（上海）有限公司 | High-precision concentration meter and measuring method thereof |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106802269A (en) * | 2017-03-24 | 2017-06-06 | 广东美的制冷设备有限公司 | Dust sensor adjusting zero method, device and purifier for purifier |
| CN106802269B (en) * | 2017-03-24 | 2019-09-06 | 广东美的制冷设备有限公司 | Dust sensor adjusting zero method, device and purification device for purification device |
| CN113670785A (en) * | 2021-09-27 | 2021-11-19 | 北京伟瑞迪科技有限公司 | Particulate matter concentration monitoring method, device, equipment and storage medium |
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| CN105203439B (en) | 2018-01-05 |
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