CN110231833A - A kind of oil field inspection fixed-point data acquisition system and method based on multiple no-manned plane - Google Patents
A kind of oil field inspection fixed-point data acquisition system and method based on multiple no-manned plane Download PDFInfo
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Abstract
The present invention provides a kind of oil field inspection fixed-point data acquisition system and method based on multiple no-manned plane, is related to oil field production technical field.The present invention includes setting unmanned plane number m and each unmanned plane to need task point and mission area in inspection wellblock, and the planning that each unmanned plane carries out polling path obtains optimal path；All unmanned planes carry out fixed point acquisition to allocated task point according to its optimal path；It obtains data and judges whether the data are valid data, if reacquiring data in vain, after if effective each unmanned plane clicks through the acquisition of row data to task, task point is marked to the unmanned plane that the mark information is shared with to other work compounds, judge whether each unmanned plane has traversed its responsible all task point, if then until all unmanned planes complete the data acquisition of all task points distributed it, if otherwise unmanned plane reaches next task point acquisition data.The efficiency of oil field inspection and the safety of Petroleum Production and management can be improved in this method.
Description
Technical Field
The invention relates to the technical field of oilfield production, in particular to an oilfield patrol fixed-point data acquisition system and method based on multiple unmanned aerial vehicles.
Background
The petroleum industry is a high risk and high profit industry, and therefore the safe production of petroleum is the basis and precondition for the production and development of the petroleum industry. Because most of the petroleum collection equipment exists in the field and the corresponding safety facilities are incomplete, the traditional manual inspection needs to spend a great deal of time on checking the conditions in the oil field, which is time-consuming and labor-consuming; the semi-automatic inspection method also needs to check the installed equipment regularly, which wastes time and costs much. In addition, in recent years, the phenomenon of illegal oil stealing is often prohibited, and the collected or stored equipment is seriously damaged, thereby causing great influence on the safety production of the oil industry. Meanwhile, if the oil outlet temperature of the oil well is too low, the oil well can be waxed, so that the petroleum extraction is influenced, the liquid levels of the water tank and the oil tank need to be monitored frequently, so that the data are very necessary to be collected, meanwhile, the crude oil is required to be managed and transported properly after being extracted, the pressure value of the oil pipeline has corresponding requirements on the transportation distance and the surrounding environment, so that the measurement of the crude oil pressure is also necessary, and therefore, the important data in the petroleum industry are very necessary to be obtained timely. Therefore, the traditional manual inspection and semi-automatic inspection methods have many problems and defects.
Disclosure of Invention
The technical problem to be solved by the invention is to provide the oil field inspection fixed point data acquisition system and method based on the multiple unmanned aerial vehicles aiming at the defects of the prior art, and the method can improve the oil field inspection efficiency and the safety and management of oil production.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
on one hand, the invention provides an oil field inspection fixed point data acquisition system based on multiple unmanned aerial vehicles, which comprises multiple unmanned aerial vehicle ends, multiple tested equipment ends and a ground end;
each unmanned aerial vehicle end comprises an infrared obstacle avoidance sensor, a control module and a wireless communication module; the infrared obstacle avoidance sensor is arranged on the unmanned aerial vehicle, and the output end of the infrared obstacle avoidance sensor is connected with the control module; the control module comprises an unmanned aerial vehicle GPS, a path planning module and a camera; the output end of the unmanned aerial vehicle GPS is connected with the input end of the path planning module and the input end of the wireless communication module; the path planning module is used for planning paths according to the task points, the task areas and the received GPS information of the unmanned aerial vehicle; the camera is arranged on the unmanned aerial vehicle, and the output end of the camera is connected with the wireless communication module; the wireless communication module comprises a wireless data receiving module and a wireless data sending module, and the wireless data receiving module is used for receiving data output by the tested equipment terminal, the unmanned aerial vehicle GPS and the camera and transmitting the received data to the wireless data sending module; the wireless data sending module is used for transmitting all received data to a ground end and transmitting the received position data to other unmanned aerial vehicles;
each tested equipment end comprises a data acquisition module, an equipment end GPS, an equipment end wireless data sending module and a driving module; the data acquisition module is used for acquiring data of a sensor on the tested equipment and outputting the data to the equipment end wireless data transmission module; the equipment end GPS is connected with the equipment end wireless data sending module; the equipment end wireless data sending module is used for transmitting the received data and the position information to a wireless data receiving module of the unmanned aerial vehicle end; the driving module is used for driving all devices at the tested equipment end, and the output ends of the driving module are respectively connected with the input ends of the data acquisition module, the equipment end GPS and the equipment end wireless data sending module;
the ground end comprises a data storage module; the data storage module is used for receiving data sent by the unmanned aerial vehicle, and arranging and storing the data.
On the other hand, the invention provides an oil field inspection fixed point data acquisition method based on multiple unmanned aerial vehicles, which is realized by the oil field inspection fixed point data acquisition system based on the multiple unmanned aerial vehicles, and comprises the following steps:
step 1: the number m of the unmanned aerial vehicles is set by a user, and the task points and the task areas of the unmanned aerial vehicles in the well area to be inspected are respectively input into the control module of each unmanned aerial vehicle; the task point is that the unmanned aerial vehicle carries out position positioning on an equipment end GPS on the collected equipment according to the unmanned aerial vehicle GPS carried by the unmanned aerial vehicle, and one point which is w meters away from the positioning point is set as the task point, wherein w is less than 2.5; the GPS on the collected equipment is arranged at one side close to the sensor;
step 2: the control module of the unmanned aerial vehicle plans a routing inspection path according to the data input in the step 1; the planning method comprises the following steps:
step 2.1: establishing a fitness function C of unmanned aerial vehicle path planning;
C＝ω1Lc+ω2Hc
wherein C is the total fitness function; l iscThe maximum flight distance of the unmanned aerial vehicle; hcThe sum of the flight height differences of all the unmanned aerial vehicles on the path; omega1、ω2Is a proportionality coefficient, l is 1 or 2; z is a radical ofi,jA Z-axis coordinate value of the unmanned aerial vehicle i on the path;
m is the number of unmanned aerial vehicles; n is the total number of points on the path;
wherein d isi,jkThe Euclidean distance from a point j to a point k on the ith unmanned aerial vehicle is set; d is a set of all task points; a. theiA task sequence for unmanned aerial vehicle i; xi,jkThe meaning of (A) is as follows:
step 2.2: optimizing all initial paths of the unmanned aerial vehicle i through an improved whale optimization algorithm, taking the path with the minimum overall fitness function as the optimal path of the unmanned aerial vehicle, and solving the optimal path set of all unmanned aerial vehicles
Step 2.2.1: initializing a parameter set of the unmanned aerial vehicle i according to the condition of the oilfield field, wherein the parameter set comprises a population number N, a space dimension Dim and an iteration number Tmax；
Step 2.2.2: according to the barrier information output by the infrared barrier avoidance sensor, on the premise of ensuring that the barrier is avoided, randomly generating initial path points among all tasks to form h initial paths, calculating the fitness value of all the initial path points through the fitness function C in the step 2.1, and outputting the path with the lowest fitness as an optimal path X';
step 2.2.3: performing iterative optimization on all initial path points by using a whale algorithm, performing fitness calculation on all optimized path points according to a fitness function C, outputting a path X ' with the lowest fitness, comparing fitness values of X ' and X ', and outputting the path X with the lowest fitness as a global optimal path Xbest(ii) a The method comprises the following steps:
H＝|(2·rand())·Xbest-X(t)|
X(t+1)＝Xbest-(2·p·rand()-p)·H
wherein t is the number of current iterations; xbestIs a global optimal path; x (t) is the current path; p is a coefficient of linear decreasing; rand () is a random number of 0 to 1; t ismaxIs the maximum iteration number;
wherein b is a constant coefficient; e represents an exponential function; q is a random number between (0, 1);
X(t+1)＝X(t)-(2·p·rand()-p)·|(2·rand())·Xbest-X(t)|
step 2.2.4: optimal path X output by step 2.2.3 using fruit fly optimization algorithmbestCarrying out local optimization; the path coordinates are locally optimized according to the following formula to obtain the optimal path of the unmanned aerial vehicle i
Wherein,representing the X-axis coordinate value of drone i at waypoint α for the number of iterations t,Yi α(t) represents the Y-axis coordinate value of drone i at waypoint α for the number of iterations t,represents the Z-axis coordinate value of drone i at waypoint α for the number of iterations t,represents the optimized X-axis coordinate value of drone i at path point α for iteration number t +1,represents the optimized Y-axis coordinate value of drone i at waypoint α at iteration number t +1,representing the optimized Z-axis coordinate value of the unmanned aerial vehicle i on the path point α when the iteration number t +1 is reached;
step 2.2.5: judging whether the current iteration times are larger than the set maximum iteration times or not, if so, terminating the iteration and outputting an optimal path; otherwise, returning to the step 2.2.3;
step 2.2.6: repeating the steps 2.2.1 to 2.2.5 to obtain the optimal path set of all the unmanned aerial vehicles
And step 3: all unmanned aerial vehicles perform fixed-point traversal collection on the distributed task points according to the optimal paths; the unmanned aerial vehicle carries out specific position positioning on all task points in an optimal path which is responsible for the unmanned aerial vehicle through an unmanned aerial vehicle GPS and a device end GPS on the tested device, detects obstacles along the path according to an infrared obstacle avoidance module and avoids the obstacles through the change of the flying height or direction, simultaneously opens a camera, carries out video recording on the routing inspection process, and transmits video recording data to a data storage module in real time through a wireless communication module on the unmanned aerial vehicle;
and 4, step 4: acquiring data; the data acquisition module outputs acquired sensor data to the wireless data sending module, when the unmanned aerial vehicle reaches a task point, the wireless data receiving module on the unmanned aerial vehicle is connected with the wireless data sending module on the tested equipment, and meanwhile, the wireless data sending module sends the data to the wireless data receiving module of the unmanned aerial vehicle;
and 5: the unmanned aerial vehicle judges whether the data is valid data or not after receiving the data, the acquired data needs to be judged through a parity check bit when the data is received, when the parity check bit is 1, the data is valid, the data is transmitted to a data storage module through a wireless data transmitting module carried by the unmanned aerial vehicle, the acquisition and storage of the data of the task point are completed, when the parity check bit is 0, the data is invalid, the data received at this time is ignored, and the data is continuously received until the valid data is received;
step 6: after the unmanned aerial vehicle collects data of the task point, the unmanned aerial vehicle collecting the data marks the collected task point through the GPS and the wireless communication module of the unmanned aerial vehicle and shares the marking information to other unmanned aerial vehicles working cooperatively, and other unmanned aerial vehicles mark the task point through the respective GPS and the wireless communication module and cannot visit the task point again within a certain time; when a task point needs to be acquired for multiple times, the unmanned aerial vehicle is set in the control module, so that the unmanned aerial vehicle cannot mark or share information to other unmanned aerial vehicles after acquiring data of the task point;
and 7: after the unmanned aerial vehicle finishes the current task point, the unmanned aerial vehicle can continuously adjust the flight track of the unmanned aerial vehicle according to the position of the next task point; detecting obstacles along the way according to the infrared obstacle avoidance module, avoiding the obstacles to reach the next task point through the change of the flying height or direction, and executing the steps 4-6 until all the unmanned aerial vehicles finish data acquisition of all task points distributed by the unmanned aerial vehicles;
in the unmanned aerial vehicle working process, the user can be through the camera of carrying on the unmanned aerial vehicle to the real time monitoring of well area situation, when multimachine collaborative work, when having unmanned aerial vehicle to break down wherein, the user will manually arrange other unmanned aerial vehicles to replace the unmanned aerial vehicle completion collection task of damage.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: according to the oil field inspection fixed point data acquisition system and method based on the multiple unmanned aerial vehicles, the unmanned aerial vehicles have the advantages of high flexibility, low cost, high safety performance and the like. According to the invention, multiple unmanned aerial vehicles are adopted to simultaneously cooperate, so that the data acquisition efficiency of the unmanned aerial vehicles is improved, and the data acquisition accuracy is also improved. And when many unmanned aerial vehicle operations, the staff can have approximate understanding to surrounding environment and equipment operation condition through the camera on the unmanned aerial vehicle, can prevent the emergence of the unexpected condition and the oil condition of stealing, greatly increased the security of oil field production, solved moreover that current unmanned aerial vehicle system of patrolling and examining has had shortcomings such as inefficiency and information inaccuracy.
Drawings
Fig. 1 is a system structure diagram of oil field inspection fixed point data acquisition of multiple unmanned aerial vehicles according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for collecting oil field inspection setpoint data of multiple unmanned aerial vehicles according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an unmanned aerial vehicle inspection area and an unmanned aerial vehicle inspection route in an oil field according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
The method of this example is as follows.
On one hand, the invention provides an oil field inspection fixed point data acquisition system based on multiple unmanned aerial vehicles, which comprises multiple unmanned aerial vehicle ends, multiple tested equipment ends and a ground end, as shown in fig. 1;
each unmanned aerial vehicle end comprises an infrared obstacle avoidance sensor, a control module and a wireless communication module; the infrared obstacle avoidance sensor is arranged on the unmanned aerial vehicle, and the output end of the infrared obstacle avoidance sensor is connected with the control module; the control module comprises an unmanned aerial vehicle GPS, a path planning module and a camera; the unmanned aerial vehicle GPS is used for positioning the unmanned aerial vehicles and the tested equipment end, and the output end of the unmanned aerial vehicle GPS is connected with the input end of the path planning module and the input end of the wireless communication module; the path planning module is used for planning paths according to the task points, the task areas and the received GPS information of the unmanned aerial vehicle; the camera is arranged on the unmanned aerial vehicle and used for monitoring the sub-flight conditions and the surrounding environment of the unmanned aerial vehicle in real time, and the output end of the camera is connected with the wireless communication module; the wireless communication module comprises a wireless data receiving module and a wireless data sending module, and the wireless data receiving module is used for receiving data output by the tested equipment terminal, the unmanned aerial vehicle GPS and the camera and transmitting the received data to the wireless data sending module; the wireless data sending module is used for transmitting all received data to a ground end and transmitting the received position data to other unmanned aerial vehicles; data sharing is carried out among all unmanned aerial vehicles through a wireless communication module;
each tested equipment end comprises a data acquisition module, an equipment end GPS, an equipment end wireless data sending module and a driving module; the data acquisition module is used for acquiring data of a sensor on the tested equipment and outputting the data to the equipment end wireless data transmission module; the equipment terminal GPS is used for positioning the collected equipment position and transmitting the position information to the equipment terminal wireless data sending module; the equipment end wireless data sending module is used for transmitting the received data and the position information to a wireless data receiving module of the unmanned aerial vehicle end; the driving module is used for driving all devices at the tested equipment end, and the output ends of the driving module are respectively connected with the input ends of the acquisition module, the equipment end GPS and the equipment end wireless data sending module;
the ground end comprises a data storage module; the data storage module is used for receiving data sent by the unmanned aerial vehicle, and arranging and storing the data.
In the embodiment, an unmanned plane quad-rotor unmanned plane is adopted, a wireless communication module is a ZigBee module, and a GPS adopts sirf 3; the sensor at the equipment end comprises an acquisition module pressure gauge (used for acquiring oil pressure, casing pressure and back pressure), an indicator diagram acquisition instrument (used for acquiring stroke and stroke frequency) and an electric power parameter metering instrument (used for acquiring motor current);
on the other hand, the invention provides a method for collecting the oil field inspection fixed point data based on multiple unmanned aerial vehicles, which is realized by the oil field inspection fixed point data collecting system based on multiple unmanned aerial vehicles, and as shown in fig. 2, the method comprises the following steps:
step 1: the number m of the unmanned aerial vehicles is set by a user, and the task points and the task areas of the unmanned aerial vehicles in the well area to be inspected are respectively input into the control module of each unmanned aerial vehicle; the task point is that the unmanned aerial vehicle carries out position positioning on a GPS on the acquired equipment according to the GPS carried by the unmanned aerial vehicle, and one point which is w meters away from the positioning point is set as the task point, wherein w is less than 2.5; the GPS on the collected equipment is arranged at one side close to the sensor;
in this embodiment, m is 3, which is UAV1, UAV2, and UAV 3; the oil field inspection area comprises an oil pumping well, an oil tank, a water tank and the like;
step 2: the control module of the unmanned aerial vehicle plans a routing inspection path according to the data input in the step 1; the improved whale algorithm has better local searching capability due to the addition of the drosophila optimization algorithm, so that the improved whale algorithm can jump out of a local optimal solution more easily and find a global optimal solution; meanwhile, the improved algorithm has better search results (the global optimal solution is more accurate), and the calculation speed is also high; because the parameters in the fruit fly algorithm are few, the influence of the parameters on the solution and algorithm mechanism can be reduced. The planning method comprises the following steps:
step 2.1: establishing a fitness function C of unmanned aerial vehicle path planning;
C＝ω1Lc+ω2Hc
wherein C is the total fitness function; l iscThe total path length of all the unmanned aerial vehicles, namely the maximum flight distance of the unmanned aerial vehicles;
Hcthe sum of the flight height differences of all the unmanned aerial vehicles on the path; omega1、ω2Is a proportionality coefficient, l ═ 1 or 2, and represents the index of the proportionality coefficient; z is a radical ofi,jA Z-axis coordinate value of the unmanned aerial vehicle i on the path; m is the number of unmanned aerial vehicles; n is the total number of points on the path, and a plurality of path points exist between two task points and are used for path planning and obstacle avoidance;
wherein d isi,jkThe Euclidean distance from a point j to a point k on the ith unmanned aerial vehicle is set; d is a set of all task points; a. theiA task sequence for unmanned aerial vehicle i; xi,jkThe meaning of (A) is as follows:
step 2.2: optimizing all initial paths of the unmanned aerial vehicle i through an improved whale optimization algorithm, taking the path with the minimum overall fitness function as the optimal path of the unmanned aerial vehicle, and solving the optimal path set of all unmanned aerial vehicles
Step 2.2.1: initializing a parameter set of the unmanned aerial vehicle i according to the condition of the oilfield field, wherein the parameter set comprises a population number N, a space dimension Dim and an iteration number Tmax；
In this embodiment, the population number 40, the spatial dimension 3, and the iteration number 100 are set;
step 2.2.2: according to the barrier information output by the infrared barrier avoidance sensor, on the premise of ensuring that the barrier is avoided, randomly generating initial path points among all tasks to form h initial paths, calculating the fitness value of all the initial path points through the fitness function C in the step 2.1, and outputting the path with the lowest fitness as an optimal path X';
step 2.2.3: performing iterative optimization on all initial path points (the initial path points refer to the path points between tasks) by using a whale algorithm, performing fitness calculation on all optimized path points according to a fitness function C, outputting a path X with the lowest fitness, comparing fitness values of X 'and X', and outputting the path X with the lowest fitness value as an optimal path Xbest(ii) a The method comprises the following steps:
H＝|(2·rand())·Xbest-X(t)|
X(t+1)＝Xbest-(2·p·rand()-p)·H
wherein H is an assignment letter; t is the number of current iterations; xbestIs a global optimal path; x (t) is the current path; p is a coefficient of linear decreasing; rand () is a random number of 0 to 1; t ismaxIs the maximum number of iterations.
Wherein b is a constant coefficient; e represents an exponential function, q is a random number between (0, 1);
X(t+1)＝X(t)-(2·p·rand()-p)·|(2·rand())·Xbest-X(t)|
step 2.2.4: on the basis of optimizing the whale optimization algorithm, the optimal path X output in the step 2.2.3 is optimized by using the drosophila optimization algorithmbestCarrying out local optimization; the path coordinates are locally optimized according to the following formula to obtain the optimal path of the unmanned aerial vehicle i
Wherein,x-axis coordinate value, Y-axis coordinate value of unmanned plane i at path point α representing number of iterations ti α(t) represents the number of iterationsthe Y-axis coordinate value of drone i at waypoint α at t,represents the Z-axis coordinate value of drone i at waypoint α for the number of iterations t,represents the optimized X-axis coordinate value of drone i at path point α for iteration number t +1,represents the optimized Y-axis coordinate value of drone i at waypoint α at iteration number t +1,representing the optimized Z-axis coordinate value of the unmanned aerial vehicle i on the path point α when the iteration number t +1 is reached;
step 2.2.5: judging whether the current iteration times are larger than the set maximum iteration times or not, if so, terminating the iteration and outputting an optimal path; otherwise, returning to the step 2.2.3;
step 2.2.6: repeating the steps 2.2.1 to 2.2.5 to obtain the optimal path set of all the unmanned aerial vehicles
And step 3: all unmanned aerial vehicles perform fixed-point traversal collection on the distributed task points according to the optimal paths; the unmanned aerial vehicle carries out specific position positioning on all task points in an optimal path which is responsible for the unmanned aerial vehicle through a GPS of the unmanned aerial vehicle and a GPS on the tested equipment, detects obstacles along the path according to an infrared obstacle avoidance module, avoids the obstacles through the change of the flying height or direction, simultaneously opens a camera, carries out video recording on the routing inspection process, and transmits video recording data to a data storage module in real time through a wireless communication module on the unmanned aerial vehicle;
and 4, step 4: acquiring data; the data acquisition module outputs acquired sensor data (such as pressure of an Christmas tree acquired through a pressure sensor, temperature of oil acquired through a temperature sensor, liquid level of a water tank and an oil tank acquired through a liquid level sensor and the like) to the wireless data sending module;
the sensor needs sampling time when acquiring data, but in the process, the wireless data transmitting equipment on the acquired equipment continuously transmits data outwards, and the transmitting time is far shorter than the sampling time;
and 5: the unmanned aerial vehicle judges whether the data is valid data or not after receiving the data, the acquired data needs to be judged through a parity check bit when the data is received, when the parity check bit is 1, the data is valid, the data is transmitted to a data storage module through a wireless data transmitting module carried by the unmanned aerial vehicle, the collection and storage of the data of the task point are completed, when the parity check bit is 0, the data is invalid, the data received this time is ignored, and the data is continuously received until the valid data is received;
step 6: after each unmanned aerial vehicle acquires data of the task point, the unmanned aerial vehicle acquiring the data marks the acquired task point through the GPS and the wireless communication module of the unmanned aerial vehicle and shares the marking information to other unmanned aerial vehicles working cooperatively, and the other unmanned aerial vehicles mark the task point through the respective GPS and the wireless communication module and cannot access the task point again within a certain time; when a task point needs to be acquired for multiple times, setting needs to be carried out in the control module (the access times of the task point can be set in a memorial manner), so that the unmanned aerial vehicle cannot mark or share information to other unmanned aerial vehicles after acquiring the data of the task point;
and 7: after the unmanned aerial vehicle finishes the current task point, the unmanned aerial vehicle can continuously adjust the flight track (such as height, flight direction, speed and the like) of the unmanned aerial vehicle according to the position of the next task point due to the fact that the geographical position and the height of the collected equipment are different; detecting obstacles along the way according to an infrared obstacle avoidance module and avoiding the obstacles through the change of the flying height or direction, so that the flying track of the unmanned aerial vehicle in the three-dimensional space is optimal; after the next task point is reached, executing the steps 4-6 until all the unmanned aerial vehicles finish data acquisition of all the task points distributed by the unmanned aerial vehicles;
in the unmanned aerial vehicle working process, the user can prevent unexpected emergence to the real time monitoring of well area situation through the camera of carrying on the unmanned aerial vehicle. When the multi-machine cooperative operation is carried out, when an unmanned aerial vehicle breaks down, the user manually arranges other unmanned aerial vehicles to replace the damaged unmanned aerial vehicle to complete the acquisition task, and the occurrence of accidents is avoided.
The needed data is obtained by combining the oil field inspection area with the method, as shown in figure 3; as shown in table 1;
TABLE 1 oil well data sheet in oil field inspection area
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (3)
1. The utility model provides an oil field inspection fixed point data acquisition system based on many unmanned aerial vehicles which characterized in that: the system comprises a plurality of unmanned aerial vehicles, a plurality of tested equipment and a ground end;
each unmanned aerial vehicle end comprises an infrared obstacle avoidance sensor, a control module and a wireless communication module; the infrared obstacle avoidance sensor is arranged on the unmanned aerial vehicle, and the output end of the infrared obstacle avoidance sensor is connected with the control module; the control module comprises an unmanned aerial vehicle GPS, a path planning module and a camera; the output end of the unmanned aerial vehicle GPS is connected with the input end of the path planning module and the input end of the wireless communication module; the path planning module is used for planning paths according to the task points, the task areas and the received GPS information of the unmanned aerial vehicle; the camera is arranged on the unmanned aerial vehicle, and the output end of the camera is connected with the wireless communication module; the wireless communication module comprises a wireless data receiving module and a wireless data sending module, and the wireless data receiving module is used for receiving data output by the tested equipment terminal, the unmanned aerial vehicle GPS and the camera and transmitting the received data to the wireless data sending module; the wireless data sending module is used for transmitting all received data to a ground end and transmitting the received position data to other unmanned aerial vehicles;
each tested equipment end comprises a data acquisition module, an equipment end GPS, an equipment end wireless data sending module and a driving module; the data acquisition module is used for acquiring data of a sensor on the tested equipment and outputting the data to the equipment end wireless data transmission module; the equipment end GPS is connected with the equipment end wireless data sending module; the equipment end wireless data sending module is used for transmitting the received data and the position information to a wireless data receiving module of the unmanned aerial vehicle end; the driving module is used for driving all devices at the tested equipment end, and the output ends of the driving module are respectively connected with the input ends of the data acquisition module, the equipment end GPS and the equipment end wireless data sending module;
the ground end comprises a data storage module; the data storage module is used for receiving data sent by the unmanned aerial vehicle, and arranging and storing the data.
2. An oil field inspection fixed point data acquisition method based on multiple unmanned aerial vehicles is realized by the oil field inspection fixed point data acquisition system based on the multiple unmanned aerial vehicles, which is characterized in that: the method comprises the following steps:
step 1: the number m of the unmanned aerial vehicles is set by a user, and the task points and the task areas of the unmanned aerial vehicles in the well area to be inspected are respectively input into the control module of each unmanned aerial vehicle; the task point is that the unmanned aerial vehicle carries out position positioning on an equipment end GPS on the collected equipment according to the unmanned aerial vehicle GPS carried by the unmanned aerial vehicle, and one point which is w meters away from the positioning point is set as the task point, wherein w is less than 2.5; the GPS on the collected equipment is arranged at one side close to the sensor;
step 2: the control module of the unmanned aerial vehicle plans a routing inspection path according to the data input in the step 1; the planning method comprises the following steps:
step 2.1: establishing a fitness function C of unmanned aerial vehicle path planning;
C＝ω1Lc+ω2Hc
wherein C is the total fitness function; l iscThe maximum flight distance of the unmanned aerial vehicle; hcThe sum of the flight height differences of all the unmanned aerial vehicles on the path; omega1、ω2Is a proportionality coefficient, l is 1 or 2; z is a radical ofi,jA Z-axis coordinate value of the unmanned aerial vehicle i on the path;
m is the number of unmanned aerial vehicles; n is the total number of points on the path;
wherein d isi,jkThe Euclidean distance from a point j to a point k on the ith unmanned aerial vehicle is set; d is a set of all task points; a. theiA task sequence for unmanned aerial vehicle i; xi,jkThe meaning of (A) is as follows:
step 2.2: optimizing all initial paths of the unmanned aerial vehicle i through an improved whale optimization algorithm, taking the path with the minimum overall fitness function as the optimal path of the unmanned aerial vehicle, and solving the optimal path set of all unmanned aerial vehicles
Step 2.2.1: initializing a parameter set of the unmanned aerial vehicle i according to the condition of the oilfield field, wherein the parameter set comprises a population number N, a space dimension Dim and an iteration number Tmax；
Step 2.2.2: according to the barrier information output by the infrared barrier avoidance sensor, on the premise of ensuring that the barrier is avoided, randomly generating initial path points among all tasks to form h initial paths, calculating the fitness value of all the initial path points through the fitness function C in the step 2.1, and outputting the path with the lowest fitness as an optimal path X';
step 2.2.3: performing iterative optimization on all initial path points by using a whale algorithm, performing fitness calculation on all optimized path points according to a fitness function C, outputting a path X ' with the lowest fitness, comparing fitness values of X ' and X ', and outputting the path X with the lowest fitness as a global optimal path Xbest(ii) a The method comprises the following steps:
H＝|(2·rand())·Xbest-X(t)|
X(t+1)＝Xbest-(2·p·rand()-p)·H
wherein t is the number of current iterations; xbestIs a global optimal path; x (t) is the current path; p is a coefficient of linear decreasing; rand () is a random number of 0 to 1; t ismaxIs the maximum iteration number;
wherein b is a constant coefficient; e represents an exponential function; q is a random number between (0, 1);
X(t+1)＝X(t)-(2·p·rand()-p)·|(2·rand())·Xbest-X(t)|
step 2.2.4: optimal path X output by step 2.2.3 using fruit fly optimization algorithmbestCarrying out local optimization; the path coordinates are locally optimized according to the following formula to obtain the optimal path of the unmanned aerial vehicle i
Wherein,x-axis coordinate value, Y-axis coordinate value of unmanned plane i at path point α representing number of iterations ti α(t) represents the Y-axis coordinate value of drone i at waypoint α for the number of iterations t,represents the Z-axis coordinate value of drone i at waypoint α for the number of iterations t,the X-axis coordinate value and Y-axis coordinate value of the unmanned aerial vehicle i after optimization on the path point α when representing the iteration number t +1i α′(t +1) represents the optimized Y-axis coordinate value of drone i at waypoint α for iteration number t +1,representing the number of iterationsthe optimized Z-axis coordinate value of the unmanned aerial vehicle i on the path point α at t + 1;
step 2.2.5: judging whether the current iteration times are larger than the set maximum iteration times or not, if so, terminating the iteration and outputting an optimal path; otherwise, returning to the step 2.2.3;
step 2.2.6: repeating the steps 2.2.1 to 2.2.5 to obtain the optimal path set of all the unmanned aerial vehicles
And step 3: all unmanned aerial vehicles perform fixed-point traversal collection on the distributed task points according to the optimal paths; the unmanned aerial vehicle carries out specific position positioning on all task points in an optimal path which is responsible for the unmanned aerial vehicle through an unmanned aerial vehicle GPS and a device end GPS on the tested device, detects obstacles along the path according to an infrared obstacle avoidance module and avoids the obstacles through the change of the flying height or direction, simultaneously opens a camera, carries out video recording on the routing inspection process, and transmits video recording data to a data storage module in real time through a wireless communication module on the unmanned aerial vehicle;
and 4, step 4: acquiring data; the data acquisition module outputs acquired sensor data to the wireless data sending module, when the unmanned aerial vehicle reaches a task point, the wireless data receiving module on the unmanned aerial vehicle is connected with the wireless data sending module on the tested equipment, and meanwhile, the wireless data sending module sends the data to the wireless data receiving module of the unmanned aerial vehicle;
and 5: the unmanned aerial vehicle judges whether the data is valid data or not after receiving the data, the acquired data needs to be judged through a parity check bit when the data is received, when the parity check bit is 1, the data is valid, the data is transmitted to a data storage module through a wireless data transmitting module carried by the unmanned aerial vehicle, the acquisition and storage of the data of the task point are completed, when the parity check bit is 0, the data is invalid, the data received at this time is ignored, and the data is continuously received until the valid data is received;
step 6: after the unmanned aerial vehicle collects data of the task point, the unmanned aerial vehicle collecting the data marks the collected task point through the GPS and the wireless communication module of the unmanned aerial vehicle and shares the marking information to other unmanned aerial vehicles working cooperatively, and other unmanned aerial vehicles mark the task point through the respective GPS and the wireless communication module and cannot visit the task point again within a certain time; when a task point needs to be acquired for multiple times, the unmanned aerial vehicle is set in the control module, so that the unmanned aerial vehicle cannot mark or share information to other unmanned aerial vehicles after acquiring data of the task point;
and 7: after the unmanned aerial vehicle finishes the current task point, the unmanned aerial vehicle can continuously adjust the flight track of the unmanned aerial vehicle according to the position of the next task point; and (4) detecting obstacles along the way according to the infrared obstacle avoidance module, avoiding the obstacles to reach the next task point through the change of the flying height or direction, and executing the steps 4-6 until all the unmanned aerial vehicles finish data acquisition of all task points distributed by the unmanned aerial vehicles.
3. The oil field inspection fixed point data acquisition method based on multiple unmanned aerial vehicles according to claim 2, characterized in that: in the unmanned aerial vehicle working process, the user can be through the camera of carrying on the unmanned aerial vehicle to the real time monitoring of well area situation, when multimachine collaborative work, when having unmanned aerial vehicle to break down wherein, the user will manually arrange other unmanned aerial vehicles to replace the unmanned aerial vehicle completion collection task of damage.
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