CN210776304U - Pharmaceutical factory environment purification control system based on Internet of things - Google Patents
Pharmaceutical factory environment purification control system based on Internet of things Download PDFInfo
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- CN210776304U CN210776304U CN201921691677.9U CN201921691677U CN210776304U CN 210776304 U CN210776304 U CN 210776304U CN 201921691677 U CN201921691677 U CN 201921691677U CN 210776304 U CN210776304 U CN 210776304U
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
- Y02A50/2351—Atmospheric particulate matter [PM], e.g. carbon smoke microparticles, smog, aerosol particles, dust
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The utility model discloses a pharmaceutical factory environment purification control system based on the Internet of things, which comprises intelligent nodes and purification modules; the intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone; the purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain. The sensors of the sensing module comprise a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde toluene sensor, a dust sensor and an illumination intensity measuring instrument; the acousto-optic alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module. The problem of current medicine factory building to air quality monitoring incomplete and do not manage is solved.
Description
Technical Field
The utility model belongs to medicine factory building environmental monitoring equipment, concretely relates to pharmaceutical factory environment purifies control system based on thing networking.
Background
Research experience for years at home and abroad shows that one important reason for causing quality problems such as microbial pollution of medicines is that the production environment does not meet the requirements, and how to keep the air quality in a pharmaceutical factory stable and excellent for a long time is a key topic. In addition, the environmental safety of the pharmaceutical factory has a great influence on workers and people living around the factory building, and therefore, monitoring and purifying the indoor air of the pharmaceutical factory is of great significance to daily life.
In the prior art, the indoor air quality detection and regulation device of a pharmaceutical factory is single, generally only conventional temperature and humidity detection is carried out, certain harmful gases such as carbon monoxide and sulfur dioxide which exist in the factory building all the time are not involved, the reliability of data collected by sensor nodes is not evaluated, the data quality cannot be guaranteed, and the collected overproof quality data which are not qualified alive are not processed.
Therefore, the multi-node pharmaceutical factory environment purification control system based on the internet of things is provided to solve the problems, so that the environmental data in the pharmaceutical factory can be better monitored, the real-time collection and transmission of the air quality data can be realized, a user can know and control the indoor air quality condition in real time through a computer or a mobile phone, the reliability of the collected data is evaluated, and the influence of the unreliable data on the analysis work is eliminated.
SUMMERY OF THE UTILITY MODEL
An object of the utility model is to provide a pharmaceutical factory environment purification control system based on thing networking for solve current medical factory building to the air quality monitoring problem not enough and not administered.
In order to realize the technical purpose, the utility model discloses the technical scheme who takes does:
a pharmaceutical factory environment purification control system based on the Internet of things comprises intelligent nodes and a purification module;
the intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone;
the purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain.
Preferably, the sensor of the sensing module comprises a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde and toluene sensor, a dust sensor and an illumination intensity measuring instrument; the digital temperature and humidity sensor is directly connected with the input end of the main controller of the processing module; the methane sensor, the carbon monoxide sensor, the formaldehyde toluene sensor, the dust sensor and the illumination intensity measuring instrument are connected with the input end of the processing module main controller through the A/D conversion module.
Preferably, the sound and light alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module.
Preferably, the main controller of the processing module is a circuit module having an STM32F104 chip as a core.
Preferably, the digital temperature and humidity sensor is a DHT11 temperature and humidity sensor; the methane sensor adopts an MQ-4 methane sensor; the carbon monoxide sensor adopts an MQ-9 carbon monoxide sensor; the formaldehyde toluene sensor adopts MS1100 formaldehyde toluene sensor powder; the dust sensor adopts a summer-common GP2Y1010AU dust sensor; the illumination intensity measuring instrument adopts a DT-1300 photometer.
Preferably, the network layer wireless network of the processing module adopts a LORA scheme, and the module selects an ATK-LORA-01 wireless serial port communication module SX 1278.
Preferably, the processing module collects sensor data and performs a quality assessment of the air quality based on the data.
The utility model discloses following beneficial effect has:
the utility model can synchronously monitor a plurality of air quality parameters in all directions in a factory building through the arrangement of a plurality of monitoring point acquisition sensors, and can ensure that monitoring data are continuous and diverse; the main control unit outputs processed monitoring data to the server and the control terminal through a wireless network, and uses a local abnormal factor algorithm to perform quality assessment on the data, give more accurate reference value to workers, so that the purification operation can be performed manually or automatically, and the data are further output to the alarm device, so that when certain indoor air index exceeds a set threshold value, the workers can be reminded by using sound and light, in addition, the monitoring on illumination intensity is increased, the purification is realized through a shielding curtain, and when the indoor air is bad and the purification device needs a long time to purify to a certain degree, the exhaust device is started immediately, the indoor fresh air volume is increased, so that the concentration of a pollution source is reduced, and the monitoring and purification process of the indoor air quality is realized.
Drawings
Fig. 1 is a system work flow chart of the pharmaceutical factory environment purification control system based on the internet of things;
fig. 2 is a schematic diagram of a single measurement system of the pharmaceutical factory environment purification control system based on the internet of things;
fig. 3 is the utility model relates to a local abnormal factor algorithm flow chart of pharmaceutical factory environment purification control system based on thing networking.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings.
A pharmaceutical factory environment purification control system based on the Internet of things comprises intelligent nodes and a purification module;
the intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone;
the purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain.
In specific implementation, the sensors of the sensing module comprise a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde and toluene sensor, a dust sensor and an illumination intensity measuring instrument; the digital temperature and humidity sensor is directly connected with the input end of the main controller of the processing module; the methane sensor, the carbon monoxide sensor, the formaldehyde toluene sensor, the dust sensor and the illumination intensity measuring instrument are connected with the input end of the processing module main controller through the A/D conversion module.
In specific implementation, the acousto-optic alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module.
In a specific implementation, the main controller of the processing module is a circuit module with an STM32F104 chip as a core.
In specific implementation, the digital temperature and humidity sensor adopts a DHT11 temperature and humidity sensor; the methane sensor adopts an MQ-4 methane sensor; the carbon monoxide sensor adopts an MQ-9 carbon monoxide sensor; the formaldehyde toluene sensor adopts MS1100 formaldehyde toluene sensor powder; the dust sensor adopts a summer-common GP2Y1010AU dust sensor; the illumination intensity measuring instrument adopts a DT-1300 photometer.
In specific implementation, a network layer wireless network of the processing module adopts a LORA scheme, and the module selects an ATK-LORA-01 wireless serial port communication module SX 1278.
When the method is specifically implemented, the network layer is used for sending the acquired data to the user terminal in real time, so that the user can conveniently master the indoor environment condition at any time and make corresponding measures. The server can compare and store the data acquired in the near period of time to judge whether the purification device needs to be started or not, and judge whether the device of the purification module needs to be replaced or cleaned or not according to the purification times and the purification degree in the near period of time; the computer/mobile phone can check indoor air quality and specific data in real time, and can manually start the purification device at the computer/mobile phone end, and in addition, a certain time period can be set, and the purification module can be automatically started at the computer/mobile phone end when the indoor environment is not good and the purification device is not started.
And the sound and light alarm module is used for giving an alarm when the monitored air data exceeds a normal value so as to remind a worker.
In specific implementation, the processing module collects sensor data, quality evaluation is carried out on the air quality according to the data, a local abnormal factor algorithm is adopted by a quality evaluation algorithm, the algorithm analyzes, summarizes and summarizes the outlier degree of each data point through a series of defined point-to-point relations, a proper outlier judgment threshold value is selected according to an experimental result, and the final result of outlier analysis depends on the selection of a user on the values of relevant factors. The following introduces the relevant definition of the local anomaly factor algorithm:
definition 1: distance d of point pk(p) is defined as dk(p) ═ d (p, o), d (p, o) is the distance between two points p and o, the kth distance of p, that is, the distance from the kth point of p, excluding p, and the following two conditions are satisfied:
a) at least k points o 'epsilon C { x ≠ p } in the set, excluding p, satisfying d (p, o') ≦ d (p, o);
b) at most k-1 points in the set, o 'epsilon C { x ≠ p } excluding p, satisfying d (p, o') < d (p, o).
Definition 2: k-th distance neighborhood N of point pk(p), all points within the kth distance of p, including the kth distance, so the number of points in the kth neighborhood of p, Nk(p)|≥k。
Definition 3: the k-th reachable distance (rd) from point o to point p is defined as:
rd＝max{k-distance(o)，d(p，o)} (1)
is the maximum of the distance between two data points and the kth distance of data point o.
Definition 4: the local achievable density of data points p (lrd). The local reachable density of a data point p is the data point p and its Nk(p) the inverse of the mean of the reachable distances of all other data points within the set.
Definition 5: the Local Outlier Factor (LOF) for a point p represents the neighborhood of point N for point pk(p) an average of a ratio of the local achievable density of (p) to the local achievable density of point p.
As shown in equation (3), the smaller the local reachable density of the data point p is, the larger the local outlier factor is, the higher the probability that the data point is an outlier is, and vice versa. And finishing the evaluation of the data quality of the nodes by calculating the non-outlier rate of the node data.
The system comprises the following specific working steps:
step 1, determining a target data set acquired by a number of sensors;
selecting a proper parameter k, wherein an excessively large k value can enable normal data caused by an emergency environment event to be isolated, so that the normal data is judged to be an outlier data point, the accuracy of the data set can be lower than the actual accuracy, similarly, an excessively small k value can enable the accuracy of the data set to be higher than the actual accuracy, and the value of the k is 5% of the total amount of the target data set under a general condition;
step 3, calculating an outlier factor of each data point in the target data set;
and 4, evaluating the reliability of the data collected by the node by integrating the non-outlier rate of different data of each node.
Compared with unprocessed data, the reliability of the data quality acquired by a certain sensor node can be preliminarily judged through a local abnormal factor algorithm, a certain reference basis is provided for the later-stage data processing of researchers, and the result can be used for reference through the design of the sensor node placement position.
The system generally monitors the concentration of each index commonly seen in the indoor space in real time, and various devices can manually or automatically make corresponding actions through network connection. When the indoor air is bad and the purifying device needs a long time for purifying to a certain degree, the exhaust device is started immediately, and the indoor fresh air quantity is increased to reduce the concentration of a pollution source, so that the monitoring and purifying process of the indoor air quality is realized.
Above only the utility model discloses an it is preferred embodiment, the utility model discloses a scope of protection not only limits in above-mentioned embodiment, and the all belongs to the utility model discloses a technical scheme under the thinking all belongs to the utility model discloses a scope of protection. It should be noted that, for those skilled in the art, a plurality of modifications and decorations without departing from the principle of the present invention should be considered as the protection scope of the present invention.
Claims (7)
1. The utility model provides a pharmaceutical factory environment purification control system based on thing networking which characterized in that: the control system comprises an intelligent node and a purification module;
the intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone;
the purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain.
2. The pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: the sensors of the sensing module comprise a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde toluene sensor, a dust sensor and an illumination intensity measuring instrument; the digital temperature and humidity sensor is directly connected with the input end of the main controller of the processing module; the methane sensor, the carbon monoxide sensor, the formaldehyde toluene sensor, the dust sensor and the illumination intensity measuring instrument are connected with the input end of the processing module main controller through the A/D conversion module.
3. The pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: and the acousto-optic alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module.
4. The pharmaceutical factory environment purification control system based on the Internet of things as claimed in claim 2, wherein: the main controller of the processing module is a circuit module taking an STM32F104 chip as a core.
5. The pharmaceutical factory environment purification control system based on the Internet of things as claimed in claim 2, wherein: the digital temperature and humidity sensor adopts a DHT11 temperature and humidity sensor; the methane sensor adopts an MQ-4 methane sensor; the carbon monoxide sensor adopts an MQ-9 carbon monoxide sensor; the formaldehyde toluene sensor adopts MS1100 formaldehyde toluene sensor powder; the dust sensor adopts a summer-common GP2Y1010AU dust sensor; the illumination intensity measuring instrument adopts a DT-1300 photometer.
6. The pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: the network layer wireless network of the processing module adopts an LORA scheme, and the module selects an ATK-LORA-01 wireless serial port communication module SX 1278.
7. The pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: the processing module collects sensor data and performs quality assessment on air quality according to the data.
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| CN110580030A (en) * | 2019-10-11 | 2019-12-17 | 南京铁道职业技术学院 | Pharmaceutical factory environment purification control system based on Internet of things |
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| CN110580030A (en) * | 2019-10-11 | 2019-12-17 | 南京铁道职业技术学院 | Pharmaceutical factory environment purification control system based on Internet of things |
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Granted publication date: 20200616 Termination date: 20201011 |