CN109145439A - A kind of complete intelligent danger medium leakage process real-time dynamic forecast method based on tank car vehicle-mounted gas arrangement for detecting - Google Patents
A kind of complete intelligent danger medium leakage process real-time dynamic forecast method based on tank car vehicle-mounted gas arrangement for detecting Download PDFInfo
- Publication number
- CN109145439A CN109145439A CN201810948856.XA CN201810948856A CN109145439A CN 109145439 A CN109145439 A CN 109145439A CN 201810948856 A CN201810948856 A CN 201810948856A CN 109145439 A CN109145439 A CN 109145439A
- Authority
- CN
- China
- Prior art keywords
- tank car
- concentration
- leakage
- prediction
- real
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Examining Or Testing Airtightness (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The complete intelligent danger medium leakage process real-time dynamic forecast method based on tank car vehicle-mounted gas arrangement for detecting that the present invention relates to a kind of, when mobile tank car is when continuous release occurs in highway transportation, the present invention on tank car by arranging that multiple gas concentrations is popped one's head in, under conditions of comprehensively considering the factors such as wind direction, concentration value and probe distance, select the available point of 2 gas leakage concentration, again by improved prediction technique, the complete real-time dynamic prediction of intelligence is realized to the overall process of tank car dielectric leakage.The present invention can automatic running in a computer, Automatic sieve selects 2 available gas concentration sensing points after gas concentration probe reaches alarming value, and can predict damage sequence range in real time.Short, it can be achieved that unattended the time required to this method, precision of prediction is significantly higher than Gauss model.Compared to the improvement prediction model based on unmanned plane, the time required to prediction and precision of prediction is further increased, and the consequence especially suitable for tank car leakage accident is predicted.
Description
Technical field:
The invention belongs to the diffusion processes of danger medium continuous release to predict field.Specifically, mobile tank car is in highway
Occur continuous release when transport, which is embedded in vehicle-mounted emergency system platform, it can be achieved that unattended is automatic
Result is simultaneously sent back to platform and emergency flight control center, visualization display real-time dynamic forecast result by early warning, automatic Prediction.This method
Two available point concentration can be chosen from the sensing point that tank car is arranged in advance automatically, and according to its ground two-dimensional coordinate, it is pre- in real time
It surveys danger medium and leaks range.
Background technique:
In industry, especially in pressure-bearing special equipment trade, inflammable, explosive and poisonous and harmful substance is in production, storage
And it is prone to leakage accident in transportational process, effectively to carry out accident emergency rescue, control and the consequence for reducing leakage accident,
Domestic and foreign scholars have done numerous studies in terms of leakage Diffusion Simulation and hazard evaluation, mainly divide non-heavy gas dispersion model and again gas
Diffusion model two major classes, Typical Representative is three-dimensional diffusion model in heavy gas dispersion model, such as Fluid Mechanics Computation (CFD) method,
This method precision of prediction is high, has preferable accuracy, but since its computation complexity is excessive, overlong time is calculated, in reality
In industrial application, and it is not suitable for；In non-heavy gas dispersion model, Gauss model is due to proposing that the time is early, and research is more mature, and mould
Type is simple, and operand is smaller, can preferably take into account computation complexity and accuracy, is more suitable for actual industrial application, especially right
The emergency disposal of the higher burst accident of time requirement, Gauss model are widely used, and the formulation of many relevant criterions is all
Based on the model.It is however restricted as existing for the model itself: (1) to need by having experience and professional knowledge background
Personnel predict, and are mainly in highway and field condition for mobile tank car leakage accident, often only amateur nothing
The driver of technical foundation can not carry out effective emergency disposal at the first time；(2) real time leak feelings can not be shown in prediction
Condition, prediction result cannot dynamic changes at any time；(3) under normal conditions, completely by the spot detecting after leakage accident occurs
Method fully understand to scene of the accident hazardous material situations source strength and can not or be cannot achieve, and uses leakage aperture
Estimated value carries out the prediction of concentration distribution, and the margin of error of taken estimated value can make prediction result generate inevitably intrinsic miss
Difference；Therefore, the method predicted leakage hole area, precision of prediction and reliability, stability are unable to get effective guarantor
Card；(4) improved model based on unmanned plane needs to manipulate unmanned plane during flying, though it can solve the problems, such as in (2) (3), for problem (1)
It is but difficult to apply in time in tank car highway transportation emergency, therefore tank car is pre- in requisition for a set of specific aim for being more suitable for self-character
Survey model.
In conclusion predicting that danger medium leakage process, simulated effect is often based on basic Gaussian plume model
It is not accurate enough and intuitive, and do not have timeliness, lead to the finger of the work such as the command scheduling to burst accident emergency disposal, rescue
It leads and has little significance.And basic Gaussian plume model and the improved model based on unmanned plane cannot achieve full intelligent predicting, need
Skilled addressee is wanted to operate, live applicability has to be hoisted.
Summary of the invention:
The shortcomings that in view of existing model described above, the purpose of the present invention is to provide based on tank car vehicle-mounted gas detecting dress
The complete intelligent danger medium leakage process real-time dynamic forecast method set, for improving the emergency of mobile tank car highway transportation accident
Disposing capacity and efficiency, solution is not high by former Gaussian plume model precision of prediction in the prior art, does not have timeliness, is non-special
The problems such as industry personage can not operate.
To achieve the above object, the present invention provides a kind of complete intelligent danger medium based on tank car vehicle-mounted gas arrangement for detecting
Leakage process real-time dynamic forecast method, and realize computer automation, comprising the following steps:
Step S10, mobile tank car vehicle-mounted gas arrangement for detecting collection in worksite related data, and according to the characteristic of danger medium
Early warning concentration value is set, and after reaching the concentration, system platform starts Prediction program automatically.
According to the calculating demand of prediction model, data collection point need to meet following principle of layouting: in tank car all around four
Eight sensing points are arranged, according to the architectural characteristic of different tank cars, in the method easily leaked in a orientation, and its vertically position altogether
The corresponding sensing point of the location arrangements such as orchid, valve.
Step S20, after Prediction program starting, according to the parameter initialization relevant parameter of collection in worksite, the collection in worksite
Parameter include danger medium classification, wind speed, wind direction, weather condition, leak position place etc..
Based on Gaussian plume model shown in formula (1), known parameters are inputted, and initialize correlation according to the known parameters
Parameter；
The known parameters include danger medium classification, wind speed, wind direction, weather condition, leak position place etc.；
The leakage concentration of lower wind direction any point can be found out according to this model.Wherein, groundlevel concentration (z=0):
Step S30, can Auto-matching diffusion coefficient when according to practical weather, geographical location, leakage situation sequential operation；Institute
The practical weather stated is such as: ground wind speed, intensity of sunshine, atmospheric stability；
Step S40: Automatic sieve selects two difference (x from the multiple sensing points arranged on tank car1,y1), (x2,y2)。
According to the calculating demand of model, the automatic screening foundation of setting program: screening is more than the effective of warning concentration first
Sensing point；Secondly, according to lower wind direction, the maximum two o'clock of automatic screening relative position linear distance；Finally, system setting branch
Hold manual screening.
After filtering out most suitable two o'clock, its concentration for polluting poisonous substance of continuous acquisition is respectively C1(x1,y1),C2(x2,y2),
Formula (5,6) are then obtained by formula (2):
Step S50: according to the field measurement data constantly acquired, effective source height H and leakage source strength Q are predicted:
Step S60: the new prediction model of lower wind direction plume center line (y=z=0) floor projection concentration is obtained:
Step S70: according to warning concentration<C>* (x, y, 0) (definite value) of the dangerous substance, above formula is brought into formula (7), will
The formula arrived carries out abbreviation, obtains final new prediction model；
Wherein
Step S80: leakage can be obtained in conjunction with tank car vehicle-mounted gas arrangement for detecting detection data by the model of formula (13)
Any t moment, any fixed concentration C, arbitrary height are the isoconcentration curve of corresponding flat at z.
The utility model has the advantages that improvement prediction model of the invention is full intelligent method, it is embedded in after platform and supports automatic alarm, automatic
Predict and result played into emergency flight control center, and visualization display on emergency platform, it can be achieved that unattended, to amateur
Personnel's strong applicability facilitates the on-site emergency disposal of first time；And its precision of prediction and stability, reliability are significantly high
In master mould, the two o'clock C of vehicle-mounted gas arrangement for detecting one group of data of every detection of mobile tank car1(x1,y1), C2(x2,y2), equal energy
The danger medium Release and dispersion situation at corresponding moment is obtained according to the amendment prediction technique of the application, it can the newest prediction of real-time update
Situation, it is larger to the directive significance of the work such as command scheduling, the rescue of emergency disposal, thus the application value with height.
Detailed description of the invention:
It is dangerous that Fig. 1 is shown as a kind of full intelligence based on tank car vehicle-mounted gas arrangement for detecting disclosed in the embodiment of the present invention
The flow diagram of dielectric leakage process real-time dynamic forecast method.
Fig. 2 be take different leakage pore size (when 6mm, 9mm, 12mm), the amendment prediction models based on unmanned plane, and
Using under the different situations such as this paper correction model, after liquid ammonia storage tank leakage, a certain t moment, 30mg/m3Isoconcentration curve prediction pair
Than figure.
Specific embodiment:
Illustrate embodiments of the present invention below by way of specific specific example, those skilled in the art can be by this specification
Content easily understands other advantages and effect of the invention.The present invention can also add by way of a different and different embodiment
To implement or apply, the various details in this specification can also be based on different viewpoints and application, without departing from of the invention
Spirit is lower to carry out various modifications or alterations.It should be noted that in the absence of conflict, the spy in following embodiment and embodiment
Sign can be combined with each other.
Embodiment 1
A kind of Dynamic Simulation Method of the complete intelligent Release and dispersion of the gas sensing device based on tank car, specifically such as Fig. 1 institute
Show, includes the following steps:
Step S10, mobile tank car vehicle-mounted gas arrangement for detecting collection in worksite related data, and according to the characteristic of danger medium
Early warning concentration value is set, and after reaching the concentration, system platform starts Prediction program automatically.
According to the calculating demand of prediction model, data collection point need to meet following principle of layouting: in tank car all around four
Eight sensing points are arranged in a orientation, and its vertically position, further according to the architectural characteristic of different tank cars, in the method easily leaked
The corresponding sensing point of the location arrangements such as orchid, valve.
Step S20, after Prediction program starting, according to the parameter initialization relevant parameter of collection in worksite, the collection in worksite
Parameter include danger medium classification, wind speed, wind direction, weather condition, leak position place etc.；
Based on Gaussian plume model (continuous point source Gauss model), the practical pollutant concentration in arbitrary point such as formula in range is leaked
(1) shown in:
The leakage concentration of lower wind direction any point can be found out according to this model:
Wherein, groundlevel concentration (z=0) are as follows:
Lower wind direction plume center line floor projection concentration (y=z=0) are as follows:
In formula, Q: leakage source strength, units/kg/s；H: effective source height, m；U: wind speed, m/s, C are ground certain point (x, y, 0)
The mass concentration of danger medium in t moment air, unit mg/m3；σx、σy、σzRespectively horizontal vertical pivot, horizontal cross shaft and
Diffusion parameter vertically upward；X, y, z is respectively lower wind direction distance, crosswind to distance, vertical wind direction distance, unit m.
The following table 1 is embedded in platform Prediction program by step S30, when making sequential operation can Auto-matching diffusion coefficient, according to table
Practical weather, geographical location provided by 1-3, leakage situation determine:
The determination of 1 atmospheric stability of table
The determination of 2 intensity of sunshine of table
3 continuous release diffusion coefficient calculation formula of table
Step S40, Automatic sieve selects two most suitable difference (x from the multiple sensing points arranged on tank car1,y1),
(x2,y2)。
According to the calculating demand of model, the automatic screening foundation of setting program: screening is more than the effective of warning concentration first
Sensing point；Secondly, according to lower wind direction, the maximum two o'clock of automatic screening relative position linear distance；Finally, system setting branch
Hold manual screening.
After filtering out most suitable two o'clock, its concentration for polluting poisonous substance of continuous acquisition is respectively C1(x1,y1),C2(x2,y2),
Formula (5,6) are then obtained by formula (2):
Step S50: according to field measurement data, effective source height H and leakage source strength Q are predicted:
(2) formula is compared with (3) formula:
According to (7) formula, (5), (6) be may be expressed as:
It is compared, can be obtained in conjunction with (8) effectively former high by (5) (6) two formula:
(10), which are brought into (5) abbreviation, to obtain source strength:
Step S60: (10) (11) are substituted into formula (3), obtain lower wind direction plume center line (y=z=0) floor projection concentration
New prediction model:
Step S70: according to the warning concentration<C>of the dangerous substance*(x, y, 0) (definite value), above formula are brought into formula (7), will
The formula arrived carries out abbreviation, obtains final new prediction model；
Wherein
Step S80: by formula (13) model, in conjunction with the field data that gas sensing device on mobile tank car constantly acquires,
Any t moment of leakage can be obtained, the fixed concentration C arbitrarily set, the isoconcentration curve at ground.
Embodiment 2
In order to illustrate more clearly of the present invention, initial parameter is arranged the present embodiment are as follows:
4 initial parameter of table
| Danger medium | Tank volume V | Leak aperture r | Pressure P in leak | The outer pressure of leak |
| Liquefied ammonia | 60m3 | 9mm | 1.06×106Pa | 1.013×105Pa |
| Position | Weather | Wind speed u | C1(60,12.809,0) | C2(80,19.155,0) |
| Open field | Cloudy day | 3.5m/s | 553mg/m3 | 140mg/m3 |
In the identical situation of other conditions, if accident occurs, leakage aperture size it is unknown, take respectively leakage pore radius be
6mm, 9mm, 12mm, then 30mg/m3When isoconcentration curve comparison diagram as shown in Fig. 2, in figure master mould 1 be leakage aperture valuation be
Isoconcentration curve when 12mm, master mould 2 is master pattern in figure, when leakage aperture valuation is actual size 9mm etc. it is dense
It writes music line, master mould 3 is the isoconcentration curve leaked when aperture valuation is 6mm in figure.X-axis indicates lower wind direction danger medium diffusion
Distance.
Using identical real case, any two points C is taken1(60,12.809), C2(80,19.155), the concentration at two o'clock
Respectively C1: 553mg/m3, C2: 140mg/m3, calculated according to correction model, then when t moment, isoconcentration curve as shown in Fig. 2,
Correction model curve is the prediction curve in figure.
In Fig. 2, master mould 2 is the Accurate Prediction range assumed.Master mould 1 is that prediction leakage hole radius takes 12mm (quasi-
True value 9mm, positive error+3mm) when prediction result.Master mould 3 is that prediction leakage hole radius takes 6mm (exact value 9mm, negative mistake
Difference -3mm) when prediction result.Correction model (unmanned plane) in figure (be detailed in application for a patent for invention (application number:
2017113997515) " a kind of danger medium leakage process real-time dynamic forecast method based on unmanned plane detection is invented ") it is base
In the prediction result of the amendment prediction model of unmanned plane detection.Correction model (tank car) is to correct the pre- of prediction technique using this case
Survey result.The leakage region prediction area of 5 prediction curves, is specifically shown in Table 5.
It can obtain through analysis: in the case where leakage hole area is unknown, be predicted using master mould, in the present embodiment
As estimation radius error ± 3mm, leakage region prediction area error is (- 63%~112%), uses the amendment based on unmanned plane
It is 2.36% that model, which carries out prediction error, and is predicted using the correction model that the new prediction technique based on tank car obtains, accidentally
Difference is 0.56%.It can be seen that the precision of prediction and stability of new prediction technique of the invention, reliability are all remarkably higher than master mould, and
Relative to the correction model based on unmanned plane, the precision of prediction of the model is further improved.Meanwhile the prediction model
The calculating time, i.e. the jamming in computer CPU time further shortens, and can promote the timeliness of scene emergency.
5 leakage region prediction area of table
One group of two point data C of every screening1(x1,y1), C2(x2,y2), can be obtained according to the amendment prediction technique to it is corresponding when
The danger medium Release and dispersion situation at quarter when emergency management and rescue, facilitates the newest accident situation of real-time update, to the finger of emergency disposal
The directive significance for waving the work such as scheduling, rescue is larger, thus the application value with height.
The above-described embodiments merely illustrate the principles and effects of the present invention, and is not intended to limit the present invention.It is any ripe
The personage for knowing this technology all without departing from the spirit and scope of the present invention, carries out modifications and changes to above-described embodiment.Cause
This, institute is complete without departing from the spirit and technical ideas disclosed in the present invention by those of ordinary skill in the art such as
At all equivalent modifications or change, should be covered by the claims of the present invention.
Claims (5)
1. a kind of complete intelligent danger medium leakage process real-time dynamic forecast method based on tank car vehicle-mounted gas arrangement for detecting, packet
Include following steps:
Step S10, mobile tank car vehicle-mounted gas arrangement for detecting collection in worksite data, data collection point need to meet principle of layouting, and
According to the featured configuration early warning concentration value of danger medium, after reaching the concentration, system platform starts Prediction program automatically；
Step S20, after Prediction program starting, according to the data initialization relevant parameter of collection in worksite；
Q: leakage source strength, units/kg/s；H: effective source height, m；U: wind speed, m/s, C are ground certain point (x, y, 0) in t moment sky
The mass concentration of danger medium in gas, unit mg/m3；σx、σy、σzRespectively horizontal vertical pivot, horizontal cross shaft and vertically upward
Diffusion parameter；X, y, z is respectively lower wind direction distance, crosswind to distance, vertical wind direction distance, unit m；
Step S30 can find out the leakage concentration of lower wind direction any point according to this model；
Wherein, groundlevel concentration is obtained according to formula (2):
Step S40: diffusion coefficient is determined according to practical weather, geographical location, leakage situation Auto-matching；
Step S50: Automatic sieve selects two different location (x in the multiple sensing points arranged on tank car1,y1, 0), (x2,y2,
0) concentration for, measuring pollution poisonous substance is respectively C1(x1,y1,0),C2(x2,y2, 0), then formula (5,6) are obtained by formula (2):
Step S60: according to the field measurement data constantly acquired, effective source height H and leakage source strength Q are predicted:
Step S70: the new prediction model of lower wind direction plume center line (y=z=0) floor projection concentration is obtained:
Step S80: according to the warning concentration<C>of the dangerous substance*(x, y, 0) (definite value), above formula bring formula (7), the public affairs that will be obtained into
Formula carries out abbreviation, obtains final new prediction model；
Wherein
Step S90: leakage t moment, any fixed concentration C, ground can be obtained in conjunction with detection data by the model of formula (13)
The corresponding isoconcentration curve in position.
2. a kind of complete intelligent danger medium leakage process based on tank car vehicle-mounted gas arrangement for detecting according to claim 1
Real-time dynamic forecast method, which is characterized in that in step S10, the data of the collection in worksite include danger medium classification, wind
Speed, wind direction, weather condition, leak position place.
3. a kind of complete intelligent danger medium leakage process based on tank car vehicle-mounted gas arrangement for detecting according to claim 1
Real-time dynamic forecast method, which is characterized in that in step S50, automatic screening in the multiple sensing points arranged on tank car
Two different locations refer to out, and 2 available points are filtered out from multiple sensing points that tank car is arranged according to following screening principle
Concentration: firstly, screening is more than effective sensing point of warning concentration；Secondly, automatic screening relative position is straight according to lower wind direction
The maximum two o'clock of linear distance；Finally, manual screening is supported in system setting.
4. a kind of complete intelligent danger medium leakage process based on tank car vehicle-mounted gas arrangement for detecting according to claim 1
Real-time dynamic forecast method, which is characterized in that in step S10, data collection point need to meet following principle of layouting: before and after tank car
Four orientation in left and right, and its vertically position arrange that eight sensing points are easily being let out according to the architectural characteristic of different tank cars altogether
Leak the corresponding sensing point of location arrangements.
5. a kind of complete intelligent danger medium leakage process based on tank car vehicle-mounted gas arrangement for detecting according to claim 1
Real-time dynamic forecast method, which is characterized in that in step S40, practical weather refers to ground wind speed, intensity of sunshine, atmospheric stability
Degree.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810948856.XA CN109145439B (en) | 2018-08-20 | 2018-08-20 | Full-intelligent real-time dynamic prediction method for dangerous medium leakage process based on tank car-mounted gas detection device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810948856.XA CN109145439B (en) | 2018-08-20 | 2018-08-20 | Full-intelligent real-time dynamic prediction method for dangerous medium leakage process based on tank car-mounted gas detection device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109145439A true CN109145439A (en) | 2019-01-04 |
| CN109145439B CN109145439B (en) | 2021-07-02 |
Family
ID=64790513
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810948856.XA Active CN109145439B (en) | 2018-08-20 | 2018-08-20 | Full-intelligent real-time dynamic prediction method for dangerous medium leakage process based on tank car-mounted gas detection device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109145439B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102567808A (en) * | 2010-12-31 | 2012-07-11 | 北京工业大学 | Method for forecasting and warning accident consequence of major hazard installation by combining with real-time meteorological information |
| CN106202679A (en) * | 2016-07-04 | 2016-12-07 | 重庆大学 | A kind of Forecasting Methodology of gas Release and dispersion process based on UAS |
| CN108053052A (en) * | 2017-11-20 | 2018-05-18 | 淮阴工学院 | A kind of oil truck oil and gas leakage speed intelligent monitor system |
| CN108091111A (en) * | 2017-11-20 | 2018-05-29 | 淮阴工学院 | A kind of oil truck oil and gas leakage intelligent early-warning system |
| CN108108832A (en) * | 2017-11-20 | 2018-06-01 | 淮阴工学院 | A kind of oil truck oil and gas leakage intelligent monitor system based on wireless sensor network |
| CN108122051A (en) * | 2017-12-22 | 2018-06-05 | 南京市锅炉压力容器检验研究院 | A kind of danger medium leakage process real-time dynamic forecast method based on unmanned plane detection |
| CN108280849A (en) * | 2018-01-23 | 2018-07-13 | 中国矿业大学(北京) | A kind of correction of pipe gallery gas leakage concentration field prediction and slip method of estimation |
-
2018
- 2018-08-20 CN CN201810948856.XA patent/CN109145439B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102567808A (en) * | 2010-12-31 | 2012-07-11 | 北京工业大学 | Method for forecasting and warning accident consequence of major hazard installation by combining with real-time meteorological information |
| CN106202679A (en) * | 2016-07-04 | 2016-12-07 | 重庆大学 | A kind of Forecasting Methodology of gas Release and dispersion process based on UAS |
| CN108053052A (en) * | 2017-11-20 | 2018-05-18 | 淮阴工学院 | A kind of oil truck oil and gas leakage speed intelligent monitor system |
| CN108091111A (en) * | 2017-11-20 | 2018-05-29 | 淮阴工学院 | A kind of oil truck oil and gas leakage intelligent early-warning system |
| CN108108832A (en) * | 2017-11-20 | 2018-06-01 | 淮阴工学院 | A kind of oil truck oil and gas leakage intelligent monitor system based on wireless sensor network |
| CN108122051A (en) * | 2017-12-22 | 2018-06-05 | 南京市锅炉压力容器检验研究院 | A kind of danger medium leakage process real-time dynamic forecast method based on unmanned plane detection |
| CN108280849A (en) * | 2018-01-23 | 2018-07-13 | 中国矿业大学(北京) | A kind of correction of pipe gallery gas leakage concentration field prediction and slip method of estimation |
Non-Patent Citations (1)
| Title |
|---|
| 朱渊等: "LNG罐车泄漏火灾罐体超压失效预警及防控", 《天然气工业》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109145439B (en) | 2021-07-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108050394B (en) | Gas pipeline leakage detection positioning experiment platform based on sound pressure signal identification | |
| CN103927410B (en) | Chemical accident emergency preplan dynamic deduces simulation system and method | |
| CN103914622B (en) | A kind of chemical leakage fast prediction alarm emergency response decision-making method | |
| CN104897853A (en) | Thermal power plant pollutant discharging monitoring display method based on tower type diffusion model | |
| CN106501451B (en) | A kind of disposition optimization method, system and the server of gas sensor | |
| CN104657573A (en) | Leaking gas diffusion forecasting method used for three-dimensional space | |
| CN102967689B (en) | A kind of Pollution Source Monitoring points distributing method | |
| US8903646B2 (en) | Method and determining system for automatically determining emission locations, and method and traffic control system based thereon for immission-dependent traffic control | |
| CN107505267B (en) | Gas detector distribution point analysis method and device | |
| CN102902860A (en) | Workplace occupational exposure simulation analysis method based on computational fluid dynamics (CFD) technology | |
| CN105043382B (en) | Unmanned plane cruise method and device | |
| CN109446696A (en) | Quick atmospheric environment capacity measuring method, storage medium and terminal based on CMAQ model | |
| KR20210050831A (en) | Real-time fine dust monitoring system and its methods | |
| Edussuriya et al. | Urban morphology and air quality in dense residential environments: Correlations between morphological parameters and air pollution at street-level | |
| CN110633339A (en) | GIS-based petrochemical enterprise gas leakage continuous dynamic simulation display method | |
| CN108122051A (en) | A kind of danger medium leakage process real-time dynamic forecast method based on unmanned plane detection | |
| CN107067174A (en) | A kind of distributed energy resource system three dimensional design appraisal procedure based on BIM | |
| CN116362113A (en) | Accident disaster evolution simulation method and system based on digital twinning | |
| CN113837692B (en) | Intelligent scheduling decision method and decision system for port operation site vehicles | |
| CN207623771U (en) | A kind of coal-burning power plant's atmosphere pollution diffusion monitoring system | |
| CN108108545A (en) | Display methods and device are deduced in fire incident simulation based on GIS-Geographic Information System | |
| CN109145439A (en) | A kind of complete intelligent danger medium leakage process real-time dynamic forecast method based on tank car vehicle-mounted gas arrangement for detecting | |
| CN110560194A (en) | Leakage diffusion real-time simulation experiment platform | |
| CN107589063A (en) | A kind of dynamic atmospheric corrosion area map data processing method, apparatus and system | |
| Xu et al. | CFD simulation of chemical gas dispersion under atmospheric boundary conditions |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |