CN104235617A - Pipeline leakage emergency instruction self-decision-making system based on monitoring network - Google Patents

Abstract

The invention discloses a pipeline leakage emergency instruction self-decision-making system based on a monitoring network, which comprises: the system comprises a monitoring terminal, a collector and a server, wherein the monitoring terminal is connected with the collector; the monitoring terminal comprises a leakage monitor, a flow speed monitor, a flow monitor, a wind condition monitor and an oil film thickness monitor; the collector is connected with each monitor in the monitoring terminals and used for collecting the oil leakage parameters, the environmental parameters and the oil film thickness parameters; and the server introduces the oil leakage parameter, the environmental parameter and the oil film thickness parameter into an improved Fay model, an improved Navy model, a Fingas evaporation equation and a Lagergren secondary adsorption rate equation for operation to obtain the diffusion parameter of the oil film.

Description

A kind of pipe leakage based on monitoring network is met an urgent need instruction self-decision system

Technical field

The present invention relates to pipe leakage emergency processing field, particularly relate to a kind of pipe leakage based on monitoring network and to meet an urgent need instruction self-decision system.

Background technique

Trans-regional national pipeline transport pipe network has become the most important passage of China's energy conveying, plays irreplaceable supporting effect.But the long distance pipeline of up to ten thousand kilometers is unavoidable needs river crossing.The pipeline River Crossing point that quantity is various and the frequent leakage occurred cause great risk of environmental pollution to water body, make pipeline emergency operation faces enormous challenge.Under the accident state of emergency, formulate the key that quick, reasonable, effective Emergency decision is accident emergency rescue success or failure.Successful Emergency decision comprises and reasonably judges leakage rate and oil slick thickness, follows the trail of and report oil head position, choose and contain position (spill containment boom installation position), reasonably choose the equipment of containing etc. accurately in time.

But the Emergency decision of existing pipe leakage is rely on subjective judgement and manual decision substantially, cannot ensure decision-making promptness and accuracy, cause the accident the slow of rescue and consequence serious.Moreover, leakage accident situation is often very complicated, and hydrologic condition and leakage parameters change very fast, the decision information needed adjusts renewal in time, quantity of information is very large, relies on traditional mode cannot acquisition real-time live information promptly and accurately, more cannot ensure the trustworthiness of manual decision.

Summary of the invention

The object of the invention is to provide a kind of pipe leakage based on monitoring network to meet an urgent need instruction self-decision system, more accurately and timely can obtain the field data of pipe leakage, improve the ability of fast processing pipe leakage.

Embodiments provide a kind of pipe leakage based on monitoring network to meet an urgent need instruction self-decision system, comprising: monitoring terminal, collector and server, wherein;

Described monitoring terminal comprises leak detector, flow monitor, flow monitor, wind resemble monitor and oil slick thickness monitor, and wherein, described leak detector is arranged on described pipeline, for gathering the oil liquid leakage parameter of described pipeline; Described flow monitor, described flow monitor and described wind resemble monitor and are arranged in the river course corresponding with described pipeline, for gathering enviromental parameter; Described oil slick thickness monitor is arranged on contains receipts oil drop, for gathering oil slick thickness parameter in described river course;

Collector, for being connected with each monitor in described monitoring terminal, gather the described oil liquid leakage parameter that described leak detector sends, gather the described enviromental parameter that described flow monitor, described flow monitor and described wind resemble monitor transmission, and gather the described oil slick thickness parameter of described oil slick thickness monitor transmission;

Described server, for receiving described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter that described collector sends, and described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter importing improvement Fay model, improvement Navy model, Fingas evaporation equation and Lagergren secondary absorption rate equation are carried out computing, obtain the diffusion parameter of oil film.

Optionally, described improvement Fay model is specially:

d _s＝ωσ _s

d _n＝ωσ _n

σ _s＝0.001t ^1.17

$\mathrm{\σ}={\mathrm{\σ}}_s/{\mathrm{\σ}}_n=\sqrt{10}$

$A^{\′}={2\mathrm{\π\σ}}_s{\mathrm{\σ}}_n\ln \frac{{\mathrm{Ve}}^{-\mathrm{kt}}}{{2\mathrm{\π\σ}}_s{\mathrm{\σ}}_n{h}_k}$

$A=\frac{\mathrm{\π}}{4}(d_s+d_f)(d_n+d_f)$

$k_{\mathrm{eq}}=\sqrt{A^{\′}/A}$

D _s＝k _eq(d _f+d _s)

D _n＝k _eq(d _f+d _n)

A＝d×D

Wherein, s represents the long axis direction of oil film; N represents oil film short-axis direction; d _sfor representing self the expansion yardstick of oil film in s direction, d _nfor representing self the expansion yardstick of oil film in n direction, ω is scaling factor, σ _sfor representing the quality mean square deviation of oil film in s direction, σ _nfor representing the quality mean square deviation of oil film in n direction, the film area of A ' for monitoring, k is for representing the damping coefficient of oil spilling volatilization and degraded, h _kfor representing the minimum oil film thickness in the oil slick thickness that monitors, A is for representing the real area of oil film, and keq is scale factor, the time that reduction process and oil film for representing greasy dirt scope disappear, D _sfor representing the major axis yardstick of oil film in s direction, D _nfor representing the minor axis yardstick of oil film in n direction, be x-y coordinate by s-n coordinate transformation, obtain oval maximum of points in x-axis, the oil film namely caused by oil slick spread moves to downstream distance D, if D _nbe greater than the river width in described river course, then A=d × D.

Optionally, described improvement Navy model is specially:

${\stackrel{\→}{R}}_s=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(k_1{\stackrel{\→}{u}}_c+k_{2}u){\mathrm{\Δt}}_i$

Wherein, k ₁for representing the surperficial drift coefficient in described river course, for representing the surface velocity in described river course, k ₂for representing the wind drift coefficient corresponding with described river course, for representing the wind speed corresponding with described river course;

If in the oil spilling response time, flow rate of water flow and wind speed do not change, then

${\stackrel{\→}{R}}_s=(k_1{\stackrel{\→}{u}}_c+k_{2}u)t$

In conjunction with the result of calculation of oil slick spread step simulations, can obtain the distance L that oil film migrates to downstream is:

$L={\stackrel{\→}{R}}_s+1/2D.$

Optionally, described Lagergren secondary absorption rate equation is specially:

$q_t=\frac{{\mathrm{kq}}_e^2}{1+{\mathrm{kq}}_{e}t}t$

Wherein, q _tfor representing the extent of adsorption during adsorption time of oil film, k is for representing secondary absorption velocity constant, q _efor representing the equilibrium adsorption capacity of oil film, t is for representing the time;

According to above-mentioned formula, so the shoreline attachment amount obtaining oil spilling is:

Q _t＝q _t×L×ΔH

Wherein, Δ H is for representing the riverbank thickness range of oil spill, and L is for representing the water front length of oil spill.

Optionally, described Fingas evaporation equation is specially:

Vaporization=[0.165 (%D)+0.045 (T-15)] lnt

Wherein, %D for represent 180 DEG C distill time mass fraction, T is for representing oil product temperature, and oil spilling steam output is: Q _vam=E × V`.

Optionally, the diffusion parameter of described oil film comprises oil slick spread area, migration distance, steam output, extent of adsorption and remaining oil mass, and wherein, described residual oil amount is specially: Q _now=V-Q _t-Q _vam

Wherein, Q _nowfor representing existing oil mass, V is for representing oil spilling volume, Q _tfor representing shoreline attachment amount, Q _vamfor representing oil spilling steam output.

Optionally, described system also comprises: user instruction terminal, and described server is used for the diffusion parameter according to described oil film, and the control command of correspondence is sent to described user instruction terminal;

Described user instruction terminal, for receiving the described control command that described server sends, and adopts the processing scheme corresponding with described control command.

By an embodiment or multiple embodiment, the present invention has following beneficial effect or advantage:

Owing to passing through oil liquid leakage parameter during monitoring terminal Real-time Obtaining pipe leakage in the embodiment of the present application, enviromental parameter and oil slick thickness parameter, and above-mentioned parameter is transferred to server by collector, then described server is by described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter import improves Fay model, improve Navy model, Fingas evaporates equation and Lagergren secondary absorption rate equation carries out computing, obtain the diffusion parameter of oil film, make it possible to the field data obtaining pipe leakage more accurately and timely, improve rapid-action ability.

Accompanying drawing explanation

Fig. 1 is the first structural representation of instruction self-decision system of meeting an urgent need based on the pipe leakage of monitoring network in the embodiment of the present invention;

Fig. 2 is the second structural representation of instruction self-decision system of meeting an urgent need based on the pipe leakage of monitoring network in the embodiment of the present invention.

In figure, appended with drawings mark is as follows:

10---monitoring terminal, 11---leak detector, 12---flow monitor, 13---flow monitor, 14---wind resembles monitor, and 15---oil slick thickness monitor, 20---collector, 30---server, 40---user instruction terminal.

Embodiment

The object of the invention is to provide a kind of pipe leakage based on monitoring network to meet an urgent need instruction self-decision system, more accurately and timely can obtain the field data of pipe leakage, improve the ability of fast processing pipe leakage.

Below in conjunction with accompanying drawing, the main of embodiment of the present invention technological scheme is realized principle, embodiment and set forth in detail the beneficial effect that should be able to reach.

One embodiment of the invention provides a kind of pipe leakage based on monitoring network and to meet an urgent need instruction self-decision system, see Fig. 1, comprising: monitoring terminal 10, collector 20 and server 30, wherein;

Monitoring terminal 10 comprises leak detector 11, flow monitor 12, flow monitor 13, wind resemble monitor 14 and oil slick thickness monitor 15, and wherein, leak detector 11 is arranged on described pipeline, for gathering the oil liquid leakage parameter of described pipeline; Flow monitor 12, flow monitor 13 and wind resemble monitor 14 and are arranged in the river course corresponding with described pipeline, for gathering enviromental parameter; Oil slick thickness monitor 15 is arranged on contains receipts oil drop, for gathering oil slick thickness parameter in described river course;

Collector 20, for being connected with each monitor in monitoring terminal 10, gather the described oil liquid leakage parameter that leak detector 11 sends, gather the described enviromental parameter that flow monitor 12, flow monitor 13 and wind resemble monitor 14 transmission, and gather the described oil slick thickness parameter of oil slick thickness monitor 15 transmission;

Server 30, for receiving described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter that collector 20 sends, and described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter importing improvement Fay model, improvement Navy model, Fingas evaporation equation and Lagergren secondary absorption rate equation are carried out computing, obtain the diffusion parameter of oil film.

Wherein, leak detector 11 can for being arranged on the optical fiber transducer of sonic sensor on pipeline or pipeline, every a segment distance such as 50 meters, 20 meters etc. a leak detector all can be installed, whether leak for Real-Time Monitoring pipeline, when pipeline occurs to leak, for gathering the oil liquid leakage parameter of described pipeline.

Secondly, flow monitor 12, flow monitor 13 and wind resemble monitor 14 for being arranged on the monitor combination in river course, flow to every 5km-10km along river course and arrange one group, wherein, at least comprise a flow monitor, a flow monitor and a wind in the combination of each monitor and resemble monitor.

Further, oil slick thickness monitor 15 can be the interim sensor arranged, and contains the recovering state receiving oil drop Real-Time Monitoring oil described in being laid in, and for gathering oil slick thickness parameter.

Concrete, leak detector 11, for when monitoring pipeline and occurring to leak, reports to the police; Flow monitor 12, flow monitor 13 and wind resemble monitor 14 and detect real time leak field data respectively, wherein, and the flowing velocity of the water body in the described river course of water volume flow rate monitoring 12 detection and the oil film of the fluid of leakage in described river course; Flow monitor 13, can also be used for detecting oil slick thickness in conjunction with preset information as river width etc. calculates the flow of oil film and then the assessment as leakage rate; And wind resembles monitor cloth 14 and is located at above described river course and monitors the wind such as wind speed, wind direction image information, so, described enviromental parameter is made to comprise the water body in described river course and leak the flowing velocity of oil film of fluid in described river course, the flow of described oil film, wind speed information and wind direction information; A real-time detection is contained with reclaiming the change procedure carrying out oil slick thickness described in oil slick thickness monitor 15 is laid in.

In specific implementation process, collector 20 can be single-chip microcomputer or embedded chip, for being connected with each monitor in monitoring terminal 10, and pretreatment can be carried out to the data gathered from each monitoring unit, then by wireless or wired or satellite communication mode by pretreated data transmission to server 30, the described oil liquid leakage parameter that server 30 sends for receiving collector 20, described enviromental parameter and described oil slick thickness parameter, and by described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter import improves Fay model, improve Navy model, Fingas evaporates equation and Lagergren secondary absorption rate equation carries out computing, obtain the diffusion parameter of oil film.

Wherein, described improvement Fay model is specially:

Due to the existence, particularly ephermeral stream of wind field and current, when the wet season, flow action accounts for leading factor, and think oil film in oval row before tactile bank, after touching bank, two sides, river, oil film shape is consistent with river shape, is strip, and width is equal to river width.

Represent under wind drags the effect of draging with s, the long axis direction of oil film, it is identical with wind direction; Oil film short-axis direction is represented with n:

D _s=ω σ _sformula (1)

D _n=ω σ _nformula (2)

In formula (1) and formula (2):

D _sfor representing self the expansion yardstick of oil film in s direction, d _nfor representing self the expansion yardstick of oil film in n direction;

ω, for representing scaling factor, gets 121/2;

σ _sfor representing the quality mean square deviation of oil film in s direction, σ _nfor representing the quality mean square deviation of oil film in n direction.

Again according to the some Through observation data in situ of summary, think that diffusion causes oil film quality approximate normal distribution, oil film diameter is directly proportional to quality mean square deviation.Under isotropic condition, oil film peripheral limit keeps circular, and can measure oil film scope by diameter, the oil film diameter drawn is only relevant with the time, therefore, and σ _scorresponding formula is:

σ _s=0.001t ^1.17formula (3)

$\mathrm{\σ}={\mathrm{\σ}}_s/{\mathrm{\σ}}_n=\sqrt{10}$ Formula (4)

The film area that can observe is calculated as follows:

$A^{\′}={2\mathrm{\π\σ}}_s{\mathrm{\σ}}_n\ln \frac{{\mathrm{Ve}}^{-\mathrm{kt}}}{{2\mathrm{\π\σ}}_s{\mathrm{\σ}}_n{h}_k}$ Formula (5)

The film area that can observe is calculated as follows:

In formula (5):

A ' is for representing the film area that can observe, and unit is m ²;

K, for representing the damping coefficient of the volatilization of combined reaction oil spilling and degraded, generally gets 0.5 (1/d);

H _kfor representing the minimum thickness of Observable oil film, generally get 10 ^-4mm ~ 10 ^-3mm, this model gets 5 × 10 ^-4mm.

A is for representing the real area of oil film, and unit is m ², calculate by formula (6):

$A=\frac{\mathrm{\π}}{4}(d_s+d_f)(d_n+d_f)$ Formula (6)

Keq is scale factor, increase in time and reducing, and reacted the time that the reduction process of greasy dirt scope and oil film disappear, keq value, from 1 to 0, calculates by formula (7):

$k_{\mathrm{eq}}=\sqrt{A^{\′}/A}$ Formula (7)

Oil film is at the major axis yardstick D in s direction _srepresent, calculate by formula (8):

D _s=k _eq(d _f+ d _s) formula (8)

Oil film is D at the minor axis yardstick in n direction _nrepresent, calculate by formula (9):

D _n=k _eq(d _f+ d _n) formula (9)

Be finally x-y coordinate by s-n coordinate transformation, obtain oval maximum of points in x-axis, the oil film namely caused by oil slick spread moves to downstream distance D, if D _nbe greater than the river width in described river course, then A=d × D formula (10).

Secondly, described improvement Navy model is specially:

The simulation of Drift Process adopts the Navy model simplified, and is that direction is fixed from upstream to downstream, obtains formula (11) the oil spilling barycenter transit time for ordinary river flow direction after displacement be:

${\stackrel{\→}{R}}_s=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}(k_1{\stackrel{\→}{u}}_c+k_{2}u){\mathrm{\Δt}}_i$ Formula (11)

In formula (11):

K ₁for representing the surperficial drift coefficient in described river course, this model gets 1.15;

for representing the surface velocity in described river course;

K ₂for representing the wind drift coefficient corresponding with described river course, this model gets 0.025;

for representing the wind speed corresponding with described river course.

If in the oil spilling response time, flow rate of water flow and wind speed do not change, then

${\stackrel{\→}{R}}_s=(k_1{\stackrel{\→}{u}}_c+k_{2}u)t$ Formula (12)

In conjunction with the result of calculation of oil slick spread step simulations, can obtain the distance L that oil film migrates to downstream is:

$L={\stackrel{\→}{R}}_s+1/2D.$ Formula (13).

Further, because the water surface affects by the factor such as wave or physical features, oil film will with the medium generation suction-operated of certain thickness bank, described Lagergren secondary absorption rate equation is specially:

$q_t=\frac{{\mathrm{kq}}_e^2}{1+{\mathrm{kq}}_{e}t}t$ Formula (14)

In formula (14):

Q _tfor representing the extent of adsorption during adsorption time of oil film, unit is mL/cm ²;

K is for representing secondary absorption velocity constant, and unit is mL/ (cm ²× min);

Q _efor representing the equilibrium adsorption capacity of oil film, unit is mL/cm ²;

T is for representing the time, and unit is second (s);

According to formula (11), so the shoreline attachment amount obtaining oil spilling is:

Q _t=q _t× L × Δ H formula (15)

In formula (15),

Δ H is for representing the riverbank thickness range of oil spill, and unit is m ²;

L is for representing the water front length of oil spill, and unit is rice (m).

Further, the direct evaporation equation calculated from distillation data that Fingas proposes is:

Vaporization=[0.165 (%D)+0.045 (T-15)] lnt formula (16)

In formula (16),

%D for represent 180 DEG C distill time mass fraction;

T is for representing oil product temperature, and unit is degree Celsius (DEG C).

Wherein, oil spilling steam output is: Q _vam=E × V` formula (17).

Finally carry out the calculation of residual oil gauge, be specially:

Calculate the difference that an existing oil mass demand goes out the total leakage rate of oil product and shoreline attachment amount, oil evaporation amount:

Q _now=V-Q _t-Q _vamformula (18)

In formula (14):

Q _nowfor representing existing oil mass, unit is m ³;

V is for representing oil spilling volume, and unit is m ³;

Q _tfor representing shoreline attachment amount, unit is m ³;

Q _vamfor representing oil spilling steam output, unit is m ³.

Concrete, server 30 is by described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter import improves Fay model, improve Navy model, Fingas evaporates equation and Lagergren secondary absorption rate equation carries out computing, obtain the diffusion parameter of described oil film, wherein, the diffusion parameter of described oil film comprises oil slick spread area, migration distance, steam output, extent of adsorption and remaining oil mass, wherein, described residual oil measurer body can pass through formula (18) and can be calculated, wherein, server 30 can be such as desktop computer, the electronic equipments such as notebook computer.

Concrete, described system can also comprise user instruction terminal 40, server 30 is for the diffusion parameter according to described oil film, generate fixed control command, and the control command of described correspondence is sent to user instruction terminal 40, after user instruction terminal 40 receives the described control command of server 30 transmission, and adopt the processing scheme corresponding with described control command to process described pipe leakage, because server 30 more accurately and timely can obtain the field data of pipe leakage, make user instruction terminal 40 also can receive control command in time and fast, then by described control command, can in time and process leakage accident fast, processing scheme can better also more accurately be processed described pipe leakage, wherein, user instruction terminal 40 can be such as smart mobile phone, the electronic equipments such as panel computer.

In actual application, see Fig. 2, a kind of pipe leakage based on monitoring network is met an urgent need instruction self-decision system, and this system body comprises four parts, is stereoscopic monitoring net respectively, communications system, decision system software and user instruction terminal.

Wherein, stereoscopic monitoring net is resembled monitor, oil slick thickness monitor and data acquisition unit formed by leak detector, flow monitor, flow monitor, wind, wherein, leak detector is be arranged on the sonic sensor on pipeline or the optical fiber transducer around body; It is the monitor combination be arranged in river course that flow monitor, flow monitor, wind resemble monitor, flows to every 5km-10km arrange one group along river course; Oil slick thickness monitor is temporary sensory device, is laid in the recovering state contained and receive oil drop Real-Time Monitoring oil; Each monitor or the Monitoring Data of monitor assembly cover laying data acquisition unit to detection carry out pretreatment, pass through communications system transmission afterwards, data acquisition unit can be single-chip microcomputer or embedded chip, can increase or reduce monitor types and quantity as required.

Further, leak detector can for being arranged on the sonic sensor on pipeline or the optical fiber transducer around body, and pipelines leakage signal realizes warning function; Flow monitor, flow monitor, wind resemble monitor and detect real time leak field data respectively, the wherein flowing velocity of flow monitor detection water body and oil film, flow monitor detection oil slick thickness is in conjunction with preset information as river width etc. calculates the flow of oil film and then the assessment as leakage rate, and wind resembles monitor and is laid in above river course and monitors the wind such as wind speed, wind direction image information; Oil slick thickness monitor is laid in contains a real-time detection with reclaiming the change procedure carrying out oil slick thickness, and the signal of data acquisition unit acquires monitor is also by communications system transmission, and wherein, communications system can take satellite communication or radio communication.

Decision system software is a kind of software systems based on computer hardware and software, comprise data acquisition module, GIS background data base, data backstage computing module and decision instruction module, wherein, the data information that data collecting module collected communications system transmits, and information is stored to GIS background data base, data backstage computing module prestores from GIS background data base Automatically invoked and real time data carries out simulation trial, result is in the display of decision instruction module, and the module of decision instruction simultaneously issues decision instruction from trend user instruction terminal.

GIS background data base prestores and the real time data that gathers storage can comprise hydrographic information, weather information and leakage oil product information, wherein, described hydrographic information comprises flow velocity, water temperature, stream shape and trend, bank vegetation, along the river building, bridge, sewage draining exit, river sink information etc.; Described weather information comprises wind speed information and wind direction information etc.; The information such as described leakage oil product packets of information oil scraper film thickness, oil head position, oily flow, yield and residual oil film thickness.

User instruction terminal comprises instruction feedback module and command reception module, and described instruction feedback module realizes user manually to decision system software feedback field data, corrects decision-making systems soft ware; Described command reception module receives the instruction from decision system software, and the decision instruction of action is instructed in concrete display in user instruction terminal.

The described pipe leakage based on monitoring network instruction self-decision systematic simulation calculation process of meeting an urgent need is as follows: system initialization starts each several part element, each monitoring equipment collects data communication to self-decision system, data collecting module collected stores data, data backstage computing module calls desired data, import model, by the Fay model improved, the Navy model improved, Fingas evaporates equation, Lagergren secondary absorption rate equation simulation trial, specifically image data is substituted into formula (1) ~ formula and carry out computing in (18), obtain the diffusion parameter of oil film, wherein, the diffusion parameter of described oil film comprises oil slick spread area, migration distance, steam output, extent of adsorption, remaining oil mass etc.

Laboratory small-scale test simulation is carried out in the present embodiment, instruction self-decision system of being met an urgent need by pipe leakage based on monitoring network is laid in the simulating riverway of wide 3m, and simulation flow velocity is 0.3m/s, and the depth of water is 1.5m, leak detector adopts sonic sensor, and communications system is WLAN communication module.Artificial to leak detector signal, set out after reporting to the police, the spontaneous startup of system, response time < 2s.In river course, pour down or forth 5KG crude oil, oil film drifts about along river course after expanding rapidly.Monitor monitors is to oil film flow velocity 0.28m/s, oil slick thickness 1.6um, and wind speed is 0.05m/s (being considered as calm situation).Pass in software systems by communications system after data acquisition unit acquires data, software systems record, response time < 1s.After system-computed, instruction is as follows: use spill containment boom < 10m, uses asphalt felt < 3 ㎡.Analog result shows, this system components coordinate well, and working condition is good, can effectively work in the state of accident.

By an embodiment or multiple embodiment, the present invention has following beneficial effect or advantage:

One, owing to passing through oil liquid leakage parameter during monitoring terminal Real-time Obtaining pipe leakage in the embodiment of the present application, enviromental parameter and oil slick thickness parameter, and above-mentioned parameter is transferred to server by collector, then described server is by described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter import improves Fay model, improve Navy model, Fingas evaporates equation and Lagergren secondary absorption rate equation carries out computing, obtain the diffusion parameter of oil film, make it possible to the field data obtaining pipe leakage more accurately and timely, improve rapid-action ability.

They are two years old, because server in the embodiment of the present application can according to the diffusion parameter of described oil film, generate fixed control command, and the control command of described correspondence is sent to user instruction terminal, make user instruction terminal receive server send described control command after, and adopt the processing scheme corresponding with described control command to process described pipe leakage, because described server more accurately and timely can obtain the field data of pipe leakage, make described user instruction terminal also can receive control command in time and fast, then by described control command, can in time and process leakage accident fast, processing scheme can better also more accurately be processed described pipe leakage.

Obviously, those skilled in the art can carry out various change and modification to the present invention and not depart from the spirit and scope of the present invention.Like this, if these amendments of the present invention and modification belong within the scope of the claims in the present invention and equivalent technologies thereof, then the present invention is also intended to comprise these change and modification.

Claims (7)

1. to meet an urgent need an instruction self-decision system based on the pipe leakage of monitoring network, it is characterized in that, comprise monitoring terminal, collector and server, wherein;

Described monitoring terminal comprises leak detector, flow monitor, flow monitor, wind resemble monitor and oil slick thickness monitor, and wherein, described leak detector is arranged on described pipeline, for gathering the oil liquid leakage parameter of described pipeline; Described flow monitor, described flow monitor and described wind resemble monitor and are arranged in the river course corresponding with described pipeline, for gathering enviromental parameter; Described oil slick thickness monitor is arranged on contains receipts oil drop, for gathering oil slick thickness parameter in described river course;

Described collector, for being connected with each monitor in described monitoring terminal, gather the described oil liquid leakage parameter that described leak detector sends, gather the described enviromental parameter that described flow monitor, described flow monitor and described wind resemble monitor transmission, and gather the described oil slick thickness parameter of described oil slick thickness monitor transmission;

Described server, for receiving described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter that described collector sends, and described oil liquid leakage parameter, described enviromental parameter and described oil slick thickness parameter importing improvement Fay model, improvement Navy model, Fingas evaporation equation and Lagergren secondary absorption rate equation are carried out computing, obtain the diffusion parameter of oil film.

2. self-decision system as claimed in claim 1, it is characterized in that, described improvement Fay model is specially:

d _s＝ωσ _s

d _n＝ωσ _n

σ _s＝0.001t ^1.17

$\mathrm{\&sigma;}={\mathrm{\&sigma;}}_s/{\mathrm{\&sigma;}}_n=\sqrt{10}$

$A^{\&prime;}={2\mathrm{\&pi;\&sigma;}}_s{\mathrm{\&sigma;}}_n\ln \frac{{\mathrm{Ve}}^{-\mathrm{kt}}}{{2\mathrm{\&pi;\&sigma;}}_s{\mathrm{\&sigma;}}_n{h}_k}$

$A=\frac{\mathrm{\&pi;}}{4}(d_s+d_f)(d_n+d_f)$

$k_{\mathrm{eq}}=\sqrt{A^{\&prime;}/A}$

D _s＝k _eq(d _f+d _s)

D _n＝k _eq(d _f+d _n)

A＝d×D

Wherein, s represents the long axis direction of oil film; N represents oil film short-axis direction; d _sfor representing self the expansion yardstick of oil film in s direction, d _nfor representing self the expansion yardstick of oil film in n direction, ω is scaling factor, σ _sfor representing the quality mean square deviation of oil film in s direction, σ _nfor representing the quality mean square deviation of oil film in n direction, the film area of A ' for monitoring, k is for representing the damping coefficient of oil spilling volatilization and degraded, h _kfor representing the minimum oil film thickness in the oil slick thickness that monitors, A is for representing the real area of oil film, and keq is scale factor, the time that reduction process and oil film for representing greasy dirt scope disappear, D _sfor representing the major axis yardstick of oil film in s direction, D _nfor representing the minor axis yardstick of oil film in n direction, be x-y coordinate by s-n coordinate transformation, obtain oval maximum of points in x-axis, the oil film namely caused by oil slick spread moves to downstream distance D, if D _nbe greater than the river width in described river course, then A=d × D.

3. self-decision system as claimed in claim 2, it is characterized in that, described improvement Navy model is specially:

${\stackrel{\&RightArrow;}{R}}_s=\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}(k_1{\stackrel{\&RightArrow;}{u}}_c+k_{2}u){\mathrm{\&Delta;t}}_i$

Wherein, k ₁for representing the surperficial drift coefficient in described river course, for representing the surface velocity in described river course, k ₂for representing the wind drift coefficient corresponding with described river course, for representing the wind speed corresponding with described river course;

If in the oil spilling response time, flow rate of water flow and wind speed do not change, then

${\stackrel{\&RightArrow;}{R}}_s=(k_1{\stackrel{\&RightArrow;}{u}}_c+k_{2}u)t$

In conjunction with the result of calculation of oil slick spread step simulations, can obtain the distance L that oil film migrates to downstream is:

$L={\stackrel{\&RightArrow;}{R}}_s+1/2D.$

4. self-decision system as claimed in claim 3, it is characterized in that, described Lagergren secondary absorption rate equation is specially:

$q_t=\frac{{\mathrm{kq}}_e^2}{1+{\mathrm{kq}}_{e}t}t$

Wherein, q _tfor representing the extent of adsorption during adsorption time of oil film, k is for representing secondary absorption velocity constant, q _efor representing the equilibrium adsorption capacity of oil film, t is for representing the time;

According to above-mentioned formula, so the shoreline attachment amount obtaining oil spilling is:

Q _t＝q _t×L×ΔH

Wherein, Δ H is for representing the riverbank thickness range of oil spill, and L is for representing the water front length of oil spill.

5. self-decision system as claimed in claim 4, is characterized in that, described Fingas evaporates equation and is specially:

Vaporization=[0.165 (%D)+0.045 (T-15)] lnt

Wherein, %D for represent 180 DEG C distill time mass fraction, T is for representing oil product temperature, and oil spilling steam output is: Q _vam=E × V`.

6. self-decision system as claimed in claim 5, it is characterized in that, the diffusion parameter of described oil film comprises oil slick spread area, migration distance, steam output, extent of adsorption and remaining oil mass, and wherein, described residual oil amount is specially: Q _now=V-Q _t-Q _vam

Wherein, Q _nowfor representing existing oil mass, V is for representing oil spilling volume, Q _tfor representing shoreline attachment amount, Q _vamfor representing oil spilling steam output.

7. the self-decision system as described in any one of claim 1 ~ 6, is characterized in that, described system also comprises: user instruction terminal, and described server is used for the diffusion parameter according to described oil film, and the control command of correspondence is sent to described user instruction terminal;

Described user instruction terminal, for receiving the described control command that described server sends, and adopts the processing scheme corresponding with described control command.