CN201697870U - Automatic flue gas blackness monitoring and analyzing system - Google Patents
Automatic flue gas blackness monitoring and analyzing system Download PDFInfo
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- CN201697870U CN201697870U CN2010202350793U CN201020235079U CN201697870U CN 201697870 U CN201697870 U CN 201697870U CN 2010202350793 U CN2010202350793 U CN 2010202350793U CN 201020235079 U CN201020235079 U CN 201020235079U CN 201697870 U CN201697870 U CN 201697870U
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Abstract
The utility model discloses an automatic flue gas blackness monitoring and analyzing system, which comprises a video monitoring subsystem and a data processing and analysis subsystem; the video monitoring subsystem comprises a camera which is used for collecting pollution source discharge images and is connected with a video encoder used for coding the collected image data; the data processing and analysis subsystem comprises a switch which has routing function and is connected with the video encoder through a network and a server integrating a Ringelmann blackness detector; and the server is used for recording the collected images and sending warning signals if a pollution source exceeding the standard tested by the Ringelmann blackness detector. The system provided by the utility model performs the video recording on flue gas blackness discharge and sends warning signals in case of overproof flue gas tested by the Ringelmann blackness detector, thereby shortening the time of testing the degree of smog discharge and improving the detection efficiency.
Description
Technical field
The utility model relates to supervisory system, is meant a kind of automatic monitor and analysis system of blackness of exhaustion especially.
Background technology
Along with the continuous quickening of China's process of industrialization, energy resource consumption constantly increases, and the atmospheric pollution situation is serious all the more.Be that raw material is formed by 75% with coal in China's energy structure, give off a large amount of flue dust and sulphuric dioxide behind the coal burning, not only directly human body is produced harm, also can form acid rain, cause a large amount of economic losses.Blackness of exhaustion is the index directly perceived of dust concentration in the reflection discharging flue gas, by can effectively judge the level of pollution of discharging flue gas to the monitoring of blackness of exhaustion.
Present widely used blackness of exhaustion assay method comprises artificial observation and Instrument measuring." mensuration of fixed-contamination source emission blackness of exhaustion-Lin Geman blackness of exhaustion figure method " (the HJ/T 398-2007) that artificial observation is mainly issued according to national environmental protection portion, Lin Geman blackness of exhaustion figure put in position go up, the blackness of flue gas is compared with the blackness on the figure, measure the blackness of fixed-contamination source emission flue gas by observer with visualization with qualification.Also can adopt telesmoke to measure, during observation, can be with the blackness figure comparative measurements in flue gas and the eyeglass.The artificial observation blackness of exhaustion is because of observation personnel's the experience and the kind of observation instrument, and the accuracy of observation that obtains has very big error." in the mensuration of solid pollution source emission blackness of exhaustion-Lin Geman blackness of exhaustion figure method explanation of compilation " that Beijing Environmental Protection Monitoring Centre formulates pointed out; the difference that 0.5～0.6 lingemann grade number is arranged between the unbred observer has the difference of 0.28～0.32 lingemann grade number between the trained observer.Instrument measuring mainly carries out on-site measurement by flue gas lingemann blackness analytic system, and Lin Geman blackness of exhaustion analyzer can show Lin Geman flue dust blackness image, can also do quantitative test simultaneously, has overcome the coarse shortcoming of artificial analysis contrastive detection.But owing to need the testing staff to detect to the discharging scene, detection time is longer, can not realize real-time detection, grasps the pollution source emission behaviour at any time.
The utility model content
In view of this, the utility model is to provide a kind of automatic monitor and analysis system of blackness of exhaustion, and is above-mentioned owing to the artificial blackness of exhaustion analyzer that uses needs manually-operated, the problem that grow, can not monitor in real time detection time to solve.
For addressing the above problem, the utility model provides a kind of automatic monitor and analysis system of blackness of exhaustion, comprising: video monitoring subsystem and Data Management Analysis subsystem;
Described video monitoring subsystem comprises: gather the camera of pollution source discharging image, described camera connects the video encoder that the view data of gathering is encoded,
Described Data Management Analysis subsystem comprises: the switch with routing function that connects described video encoder by network, described switch connects the server of integrated lingemann blackness analyzer, the image of the described collection of described server record, and detect by described lingemann blackness analyzer and to send alerting signal after pollution source exceed standard.
Further, described video encoder is by data line, or among its inner integrated wifi, GPRS, CDMA, WCDMA module any one connects network.
Further, described switch also connects control desk, and described control desk comprises input-output apparatus; Described input equipment is microphone or keyboard, and described output device is projector or display.
Further, described switch also connects the DVR of the view data that is used to write down described camera collection.
Further, described server also connects described DVR;
Described server comprises:
The image comparison module when being used for the view data of twice reception of comparison, triggers the described DVR recording image data that connects;
Image processing module is used for described view data and is optimized processing, and the image data transmission after will handling is to the described lingemann blackness analyzer that connects;
Described lingemann blackness analyzer is used to detect and export the blackness grade of described view data;
Discrimination module is used for after described blackness grade exceeds standard, and triggers the alarm that connects and sends the warning of sound/light.
Further, described server also comprises the geographic position that shows described each camera, carries the geography information GIS module of the attribute information of fume emission information and blackness grade.
Further, described server also connects the supervisory user equipment to its control.
System in the utility model, the view data that can gather by contrast when comparing the image gathered with last time not simultaneously, is recorded a video to fume emission, and after finding that by the lingemann blackness detector flue gas exceeds standard, sends alerting signal.Realization has improved detection efficiency to the automatic detection of fume emission.
Description of drawings
Fig. 1 is the cut-away view of system in the utility model;
Fig. 2 is the structure principle chart of system in the utility model;
Fig. 3 is the internal module structural drawing in the server;
Fig. 4 is the workflow diagram of system;
Fig. 5 is the functional block diagram of system.
Embodiment
For clearly demonstrating the technical scheme in the utility model, provide preferred embodiment below and be described with reference to the accompanying drawings.
Internal system structural drawing referring to shown in Figure 1 comprises: video monitoring subsystem and Data Management Analysis subsystem.
The video monitoring subsystem comprises: low-light (level) colour TV camera and video encoder; The low-light (level) colour TV camera is connected with video encoder, can adopt data line to connect or wireless communication module realization data transmission, as wireless modes such as wifi.
Video encoder combines H.264 coding on coding techniques, also adopted the management of multistage many authorities at management aspect.In addition, adopted the numeral flag technology, in case the video recording content is arbitrarily distorted in the video recording content.
Video monitoring system can realize every road video image is all recorded a video, and every road code stream is controlled between the 384K-512K.System has taken into full account effectively the taking of bandwidth, and adopts advanced H.264 encoding mechanism, and adopt differentiated control on system layout, reduces the taking of key bandwidth guaranteed that other system also can normally move as far as possible.
Video encoder is connected with the Data Management Analysis system by cable network or wireless network, and wireless mode can adopt its inner integrated wifi, GPRS, CDMA, WCDMA communication module etc., and cable network can adopt optical fiber access, broadband A SL access etc.Can be the enterprise network of enterprises special use, also can be the internet.Video encoder is by network connection data Treatment Analysis subsystem.
The Data Management Analysis subsystem comprises:
Switch, switch with routing function connect equipment such as DVR, control desk, application server respectively.
Switch can be realized the mapping of the network port, and the monitor terminal of being convenient to outer net and corporate intranet can be visited the data of the fume emission of camera and storage.
DVR is used for the data that the store video Monitor And Control Subsystem is taken, and control desk comprises input-output apparatus, and output device can adopt display, projector etc., and the image of taking is outputed on the screen by projector.
Input equipment comprises microphone, keyboard, the networking telephone etc., can realize showing the data of camera collection, the view data of broadcast DVR storage, sends command information by input equipment.
Application server connects two alarms, is respectively voice guard and visual alarm; Application server can be analyzed the view data of camera collection, and reports to the police after blackness of exhaustion exceeds standard judging.
System architecture schematic diagram of the present utility model can be referring to Fig. 2, comprise: the video camera that is deployed in each monitoring position connects video encoder respectively, video camera is constantly monitored the blackness of exhaustion of each position, and the data that video encoder is taken video camera are sent to by network and connect Surveillance center and remote monitoring subscriber equipment.
Surveillance center comprises: local monitor subscriber equipment, video and blackness Analysis server etc., the local monitor subscriber equipment can pass through control desk identification camera data monitored, camera is constantly taken the image of monitored point, it is the discharging of flue gas, and be sent to video and blackness Analysis server by Video Decoder, and video and blackness Analysis server are the application server among Fig. 1, its inside comprises with lower module, referring to Fig. 3, comprising:
The image comparison module is used for the view data that receives is compared with the last view data that receives, and when twice image is inconsistent, triggers the DVR recording image data;
Image processing module is used for state diagram image brightness, exposure compensating etc., and the image after will handling, is that fume emission figure is sent to the blackness instrument; To collecting to such an extent that figure carries out signature analysis,, accurately obtain the figure of fume emission part by image recognition technology by light balance and exposure compensating technology.
The lingemann blackness analyzer is used for the blackness of fume emission figure is analyzed, and the output of the blackness grade after will analyzing;
Discrimination module is used for triggering to this fume emission process record, and discrimination module has blackness of exhaustion comparison storehouse, by judging relatively with the figure in comparison storehouse whether blackness exceeds standard.By the lingemann blackness analyzer lingemann blackness grade of discharging flue gas is measured accurately, and write down numerical value automatically, and differentiate the blackness grade above starting alarm and emergency system behind the warning value.
Geography information GIS module is used to show and the geographic position of each camera carries the attribute information of fume emission and blackness grade.
Video and blackness Analysis server also connect the local monitor subscriber equipment, and the local monitor subscriber equipment is controlled the video and the blackness Analysis server that connect.
Video and blackness Analysis server can also carry out preliminary setting to the alarm limit in smoke pollution source, can set monitoring time (promptly fume emission source user mode being monitored once automatically) at interval every how long, set maximum warning value (be fume emission source blackness surpass index how many times just start warning function), open or close monitor state and alarm, to the smoke pollution source of monitoring write down, function such as playback.
But the local monitor user is managing video and blackness Analysis server also, makes it automatically generate blackness of exhaustion curve, blackness of exhaustion numerical tabular, and checks and revise.Add, show, safeguard camera; The basic attribute data of interpolation, display monitoring point.Also can be connected, confirm mutually, when other discharge indexs exceed standard, trigger native system equally, can carry out instant image recording and report to the police with other on-line parameters with other on-line monitoring system of delaying.
The workflow of system also can may further comprise the steps referring to process flow diagram shown in Figure 4:
S41: pollution source begin to discharge flue gas;
S42: camera collection view data;
S43: video and blackness server are handled image;
S44: video and blackness server are to the image detection of dynamic;
S45: image is carried out luminance balance, exposure compensating;
S46: image recognition;
S47: the lingemann blackness instrument is measured;
S48: carry out logical process according to measurement result;
S49: judge whether to surpass warning value; If surpass, execution in step S50; If do not surpass, execution in step S51;
S50: start audible-visual annunciator and execution in step S51 and S52, start emergency system;
S51: the data that camera is taken are carried out record;
S52: start emergency system.
Other function of system also can be referring to the function declaration shown in Fig. 5.Blackness of exhaustion analytic system software comprises that basic information management, monitor message management, GIS show, monitor automatically and the system management part.Basic information management can be carried out user management, business administration, equipment control and control point management; Monitor message management can be carried out preset point management and the setting path of cruising; Automatically control can be carried out real-time video and video playback, and real-time blackness memory is monitored, can issue warning message when blackness is exceeded standard.System management can be carried out system's setting, and has system help.
For the system that is set forth among each embodiment of the utility model, all within spirit of the present utility model and principle, any modification of being done, be equal to replacement, improvement etc., all should be included within the protection domain of the present utility model.
Claims (7)
1. the automatic monitor and analysis system of a blackness of exhaustion is characterized in that, comprising: video monitoring subsystem and Data Management Analysis subsystem;
Described video monitoring subsystem comprises: gather the camera of pollution source discharging image, described camera connects the video encoder that the view data of gathering is encoded,
Described Data Management Analysis subsystem comprises: the switch with routing function that connects described video encoder by network, described switch connects the server of integrated lingemann blackness analyzer, the image of the described collection of described server record, and detect by described lingemann blackness analyzer and to send alerting signal after pollution source exceed standard.
2. system according to claim 1 is characterized in that, described video encoder is by data line, or in its inner integrated wifi, GPRS, CDMA, the WCDMA module any one connects network.
3. system according to claim 1 is characterized in that described switch also connects control desk, and described control desk comprises input-output apparatus; Described input equipment is microphone or keyboard, and described output device is projector or display.
4. system according to claim 1 is characterized in that, described switch also connects the DVR of the view data that is used to write down described camera collection.
5. system according to claim 4 is characterized in that described server also connects described DVR;
Described server comprises:
The image comparison module when being used for the view data of twice reception of comparison, triggers the described DVR recording image data that connects;
Image processing module is used for described view data and is optimized processing, and the image data transmission after will handling is to the described lingemann blackness analyzer that connects;
Described lingemann blackness analyzer is used to detect and export the blackness grade of described view data;
Discrimination module is used for after described blackness grade exceeds standard, and triggers the alarm that connects and sends the warning of sound/light.
6. system according to claim 5 is characterized in that described server also comprises the geographic position that shows described each camera, carries the geographical location information GIS module of the attribute information of fume emission information and blackness grade.
7. system according to claim 1 is characterized in that, described server also connects the supervisory user equipment to its control.
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| Application Number | Priority Date | Filing Date | Title |
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| CN2010202350793U CN201697870U (en) | 2010-06-24 | 2010-06-24 | Automatic flue gas blackness monitoring and analyzing system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN2010202350793U CN201697870U (en) | 2010-06-24 | 2010-06-24 | Automatic flue gas blackness monitoring and analyzing system |
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| CN201697870U true CN201697870U (en) | 2011-01-05 |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156099A (en) * | 2011-01-17 | 2011-08-17 | 深圳市朗驰欣创科技有限公司 | Method and system for detecting atmospheric pollutants |
| CN103454228A (en) * | 2013-09-16 | 2013-12-18 | 北京首钢自动化信息技术有限公司 | Smoke blackness monitoring system adopting motion monitoring technology |
| CN108872031A (en) * | 2018-09-17 | 2018-11-23 | 中国科学院武汉物理与数学研究所 | Motor vehicle flue gas blackness measuring device and method |
| CN111178786A (en) * | 2020-01-08 | 2020-05-19 | 中科宇图科技股份有限公司 | Emission source position determining method and system for guaranteeing regional air quality |
| CN112255234A (en) * | 2020-09-27 | 2021-01-22 | 广州能源检测研究院 | Method and system for measuring smoke blackness of chimney |
| CN112268863A (en) * | 2020-10-13 | 2021-01-26 | 上海市计量测试技术研究院 | Illumination box for calibrating Ringelmann blackness instrument and calibration method |
-
2010
- 2010-06-24 CN CN2010202350793U patent/CN201697870U/en not_active Expired - Fee Related
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102156099A (en) * | 2011-01-17 | 2011-08-17 | 深圳市朗驰欣创科技有限公司 | Method and system for detecting atmospheric pollutants |
| CN102156099B (en) * | 2011-01-17 | 2013-01-23 | 深圳市朗驰欣创科技有限公司 | Method and system for detecting atmospheric pollutants |
| CN103454228A (en) * | 2013-09-16 | 2013-12-18 | 北京首钢自动化信息技术有限公司 | Smoke blackness monitoring system adopting motion monitoring technology |
| CN103454228B (en) * | 2013-09-16 | 2015-07-29 | 北京首钢自动化信息技术有限公司 | Adopt the flue gas blackness supervisory system of motion detecting technology |
| CN108872031A (en) * | 2018-09-17 | 2018-11-23 | 中国科学院武汉物理与数学研究所 | Motor vehicle flue gas blackness measuring device and method |
| CN108872031B (en) * | 2018-09-17 | 2019-12-13 | 中国科学院武汉物理与数学研究所 | Motor vehicle smoke blackness measuring device and method |
| CN111178786A (en) * | 2020-01-08 | 2020-05-19 | 中科宇图科技股份有限公司 | Emission source position determining method and system for guaranteeing regional air quality |
| CN111178786B (en) * | 2020-01-08 | 2023-04-25 | 中科宇图科技股份有限公司 | Emission source position determining method and system for guaranteeing regional air quality |
| CN112255234A (en) * | 2020-09-27 | 2021-01-22 | 广州能源检测研究院 | Method and system for measuring smoke blackness of chimney |
| CN112255234B (en) * | 2020-09-27 | 2021-11-16 | 广州能源检测研究院 | Method and system for measuring smoke blackness of chimney |
| CN112268863A (en) * | 2020-10-13 | 2021-01-26 | 上海市计量测试技术研究院 | Illumination box for calibrating Ringelmann blackness instrument and calibration method |
| CN112268863B (en) * | 2020-10-13 | 2023-06-20 | 上海市计量测试技术研究院 | Illumination box for calibrating ringeman blackness meter and calibration method |
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