CN116295442B - Anti-drop control method, device and equipment for pipeline operation equipment and storage medium - Google Patents
Anti-drop control method, device and equipment for pipeline operation equipment and storage medium Download PDFInfo
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Abstract
The invention provides a drop-proof control method, a drop-proof control device, drop-proof control equipment and a storage medium for pipeline operation equipment, and relates to the field of autonomous detection of underground pipelines, wherein the drop-proof control method comprises the following steps: acquiring current attitude data of the pipeline running equipment and obtaining a speed state of the pipeline running equipment, and obtaining longitude, latitude and elevation of the pipeline running equipment at any historical moment through the current attitude data; further obtaining the motion trail; inputting the current distribution track, the current gesture data and the terrain distribution of the pipeline within a preset range into a pipeline environment prediction network to obtain a motion track of pipeline running equipment within a preset time period in the future, and further obtaining the trend of the pipeline within the preset time period in the future; and further obtaining a falling risk area of the pipeline running equipment, thereby controlling the pipeline running equipment to perform falling prevention actions corresponding to the falling risk area. The invention makes anti-falling action in advance aiming at the falling risk area, thereby ensuring the safety and stability of the operation of the pipeline operation equipment.
Description
Technical Field
The invention relates to the field of autonomous detection of underground pipelines, in particular to a pipeline running equipment anti-drop control method, device and equipment and a storage medium.
Background
The pipeline operation equipment comprises equipment such as a cable line detection trolley and the like which move in a narrow pipeline, and the cable line detection trolley generally searches in the pipeline of the underground cable line, so that whether the state of the underground cable line reaches the normal working standard or not is mastered, an important role is played for the economic and social development of a city, and when the pipeline operation equipment moves in the pipeline, the pipeline can possibly encounter the conditions that the pipeline is concave downwards, convex upwards, reaches the edge of the pipeline and the like. The state of the pipeline in front of the pipeline running equipment is detected in real time, and whether the pipeline running equipment needs to make anti-drop reactions, such as braking, decelerating, turning and the like, is judged.
In the prior art, the MEMS (Micro-electro-mechanical system) technology is based on detecting the pipeline state, although the MEMS technology-based sensor has high sensitivity and can react to the moving state and pipeline state of the pipeline running device, the pipeline trend cannot be detected, because the pipeline trend is changed along with the surrounding topography, the pipeline running device is easy to fall down, the pipeline environment condition in a certain range cannot be detected only by detecting the pipeline image in front of a certain distance and detecting the distance between the pipeline and the pipeline running device, and meanwhile, whether the overall pipeline trend is dangerous or not is ignored, so that the overall pipeline arrangement is ignored, if the pipeline arrangement with an overlarge inclination angle or a higher height is performed, at this time, the pipeline running device is not timely in response, and an unpredictable falling phenomenon is very easy to occur.
Disclosure of Invention
The invention mainly solves the technical problem of avoiding falling risks under the trend of the pipeline which is easy to cause falling of pipeline operation equipment.
In order to solve the above problems, the present invention provides a fall protection control method for a pipeline operation device, including:
acquiring current gesture data of pipeline operation equipment, wherein the current gesture data comprises acceleration, angular speed and angular gesture data of the pipeline operation equipment;
obtaining a speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset interval duration;
obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
Inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the topographic distribution of the pipeline within a preset range into a pipeline environment prediction network, wherein the pipeline environment prediction network outputs the motion track of the pipeline running equipment within a preset time period in the future;
obtaining the trend of the pipeline in the future preset time period through the motion trail of the pipeline running equipment in the future preset time period;
obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area;
and controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment.
Optionally, the controlling the pipeline running device to perform a fall-preventing action corresponding to the fall risk area according to the fall risk area of the pipeline running device and the speed state of the pipeline running device includes:
If the pipeline running equipment is in the alarm area and is not in the avoidance area, controlling the pipeline running equipment to send a primary alarm signal, judging whether the speed state of the pipeline running equipment is in the acceleration state, and if so, reducing the moving speed of the pipeline running equipment according to the distance between the pipeline running equipment and the avoidance area and a preset deceleration rule;
and if the pipeline running equipment is in the avoidance area, controlling the pipeline running equipment to stop moving and sending a secondary alarm signal.
Optionally, the step of obtaining a fall risk area of the pipeline running device according to the trend of the pipeline in the future preset time period includes:
obtaining longitude, latitude and elevation of the pipeline corresponding to the trend according to the trend of the pipeline in the future preset time period;
judging whether the pipeline has an area exceeding a preset safety angle and an area exceeding a preset safety height according to the longitude, the latitude and the elevation of the pipeline;
and taking the area exceeding the preset safety angle and the area exceeding the preset safety height as the fall risk area of the pipeline running equipment.
Optionally, the method further comprises: establishing the pipeline environment prediction network;
the establishing the pipeline environment prediction network comprises the following steps:
acquiring an initial deep neural network;
acquiring pipeline distribution of an experimental pipeline, attitude data of the pipeline operation equipment in the operation of the experimental pipeline and terrain distribution in the preset range around the experimental pipeline, wherein the attitude data are the current attitude data corresponding to the pipeline operation equipment at any position of the experimental pipeline;
obtaining a complete motion track of the pipeline running equipment according to the pipeline distribution;
according to the complete motion trail of the pipeline running equipment, the current motion trail of the pipeline running equipment at any moment in the experimental pipeline and the future motion trail of the pipeline running equipment after the any moment are obtained;
the current motion trail and the future motion trail form the complete motion trail;
taking a current motion track of the pipeline running equipment at a preset moment, gesture data of the pipeline running equipment at the preset moment and terrain distribution in the preset range around the pipeline as inputs of the initial depth neural network, and taking the future motion track of the pipeline running equipment as outputs of the initial depth neural network for training;
And taking the trained initial deep neural network as the pipeline environment prediction network.
Optionally, according to the drop risk area of the pipeline running device and the speed state of the pipeline running device, controlling the pipeline running device to perform a drop-preventing action corresponding to the drop risk area, and further including:
when the speed state of the pipeline running equipment is the acceleration state and the change value of the acceleration of the pipeline running equipment in a preset duration is larger than an acceleration change threshold value, controlling the pipeline running equipment to perform deceleration action;
and stopping the deceleration action of the pipeline running equipment when the change value of the acceleration of the pipeline running equipment is smaller than an acceleration change safety threshold value.
Optionally, the method further comprises:
acquiring the inner diameter of the pipeline at a preset detection distance of the pipeline running equipment in the moving direction;
and when the inner diameter of the pipeline exceeds a preset standard value, controlling the pipeline running equipment to stop moving.
Optionally, the obtaining, by the pipeline running device, all the acceleration, the angular velocity and the angular pose data from the beginning of the movement time to the current time, the longitude, the latitude and the elevation of the pipeline running device at any historical time includes:
Obtaining longitude, latitude and elevation of the pipeline running equipment at the starting movement moment according to the starting position information of the pipeline running equipment;
the initial position information of the pipeline running equipment comprises initial position longitude and latitude and initial height;
and obtaining the longitude, latitude and elevation of the pipeline running equipment at any historical moment according to the longitude, the latitude and the elevation of the pipeline running equipment at the starting movement moment through the acceleration, the angular speed and the angular posture data of the pipeline running equipment.
The invention also provides a drop-proof control device of the pipeline running equipment, which comprises:
the detection unit is used for acquiring current gesture data of the pipeline running equipment, wherein the current gesture data comprise acceleration, angular speed and angular gesture data of the pipeline running equipment;
the processing unit is used for obtaining the speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset time lengths;
Obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
the prediction unit is used for inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the terrain distribution of the pipeline within a preset range into a pipeline environment prediction network, and outputting the motion track of the pipeline running equipment within a future preset time period by the pipeline environment prediction network;
the processing unit is further used for obtaining the trend of the pipeline in the future preset time period through the motion track of the pipeline running equipment in the future preset time period;
the analysis unit is used for obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area;
And the control unit is used for controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment.
The invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the anti-falling control method of the pipeline running equipment when executing the computer program.
The invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the pipeline running apparatus fall prevention control method of any one of the above.
According to the pipeline running equipment anti-drop control method, device, equipment and storage medium, the running state of the pipeline running equipment is judged according to the current posture data by acquiring the current posture data of the pipeline running equipment in the pipeline, and the position parameters, namely the longitude, the latitude and the elevation, of the pipeline running equipment at any historical moment are obtained, and as the pipeline running equipment moves in the pipeline in a manner of being attached to the inner wall of the pipeline, the current distribution track of the pipeline can be mapped according to the longitude, the latitude and the Gao Chengji of the pipeline running equipment, wherein the current distribution track of the pipeline corresponds to the current movement track of the pipeline running equipment, the current distribution track of the pipeline is obtained, the current distribution track of the pipeline and the corresponding terrain distribution around the pipeline are utilized, the trend of the pipeline running equipment in the future is predicted through the pipeline environment prediction network, so that the trend of the pipeline corresponding to the pipeline running equipment in the future can be obtained, whether a risk area exists can be found in time through the trend of the pipeline, and the anti-drop action is performed in advance for the risk area in the pipeline, and the safety and the stability of the pipeline running equipment are ensured.
Drawings
FIG. 1 is a flow chart of a method for fall control of a pipeline operation device in an embodiment of the invention;
FIG. 2 is a flow chart of a method for fall control of a pipeline operation device in an embodiment of the invention;
FIG. 3 is a schematic view of a fall arrest control device for a pipeline operation apparatus according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a fall arrest control device for a pipeline operation apparatus according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the invention provides a fall control method for pipeline running equipment, which comprises the following steps:
s1: acquiring current gesture data of pipeline operation equipment, wherein the current gesture data comprises acceleration, angular speed and angular gesture data of the pipeline operation equipment;
Specifically, current posture data of the pipeline running device are obtained to detect the running condition of the pipeline running device in a pipeline, meanwhile, accurate data are provided for predicting a motion track of the pipeline running device in a certain time period in the future, in a preferred embodiment of the invention, the current posture data can be measured through a sensor of an inertial measurement unit, acceleration of the pipeline running device in a motion direction is measured through an accelerometer, speed and displacement can be calculated according to integration, angular speed of the pipeline running device in a turning process is measured through a gyroscope, angular posture data of the pipeline running device are measured through a magnetometer, the angular posture data comprise a pitch angle, a roll angle and a course angle of the pipeline running device, and the current posture data of the pipeline running device are obtained through filtering and integrating the measured data.
S2: obtaining a speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
specifically, the measured acceleration of the pipeline running equipment is combined, the speed state of the pipeline running equipment can be judged, and if the acceleration is positive and the speed of the pipeline running equipment is faster, the pipeline running equipment is in an acceleration state; if the acceleration is negative and the pipe running apparatus is slower and slower, the pipe running apparatus is in a decelerating state.
S3: obtaining longitude, latitude and elevation of the pipeline running equipment at any historical moment through all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting moving moment to the current moment, wherein the historical moment is any moment from the starting moving moment to the current moment, and the adjacent historical moments are preset interval duration;
specifically, after the acceleration, the angular velocity and the angular posture data of the pipeline running device are obtained, longitude, latitude and altitude of the pipeline running device at any historical moment can be obtained through a data storage unit such as a data center or a cloud end, in the preferred embodiment of the invention, the longitude, latitude and altitude of the pipeline running device can be calculated through a combined navigation algorithm, wherein the combined navigation algorithm combines the current posture data measured by the sensor of the inertial measurement unit with a satellite positioning system, and the position observation value of a coordinate system in the satellite positioning system is used for correcting errors, so that the longitude, latitude and altitude with high precision are obtained.
S4: obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
Specifically, since the pipeline operation device moves in the pipeline while being fitted to the inner wall of the pipeline, the current distribution track of the pipeline can be mapped according to the longitude, latitude and Gao Chengji of the pipeline operation device.
S5: inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the topographic distribution of the pipeline within a preset range into a pipeline environment prediction network, wherein the pipeline environment prediction network outputs the motion track of the pipeline running equipment within a preset time period in the future;
specifically, the trend of the pipeline running equipment in the future is predicted by the pipeline environment prediction network by utilizing the current distribution track of the pipeline and the corresponding terrain distribution around the pipeline and combining the gesture data of the pipeline running equipment, so that the trend of the pipeline corresponding to the trend of the pipeline running equipment in the preset time period in the future can be obtained.
S6: obtaining the trend of the pipeline in the future preset time period through the motion trail of the pipeline running equipment in the future preset time period;
Specifically, because the pipeline running equipment is attached to the inner wall of the pipeline for movement in the pipeline, the trend of the pipeline in the future preset time period is obtained through the movement track of the pipeline running equipment in the future preset time period.
S7: obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area;
specifically, whether a falling risk area exists or not is timely found through a pipeline distribution track, in the preferred embodiment of the invention, before pipeline operation equipment works, the properties and characteristics of the pipeline operation equipment can be evaluated, the corresponding falling height is determined, whether the falling risk area exists or not is determined according to the falling height and future trend of the pipeline, and after the falling risk area exists, an alarm area and an avoidance area corresponding to the falling risk area are endowed according to the falling risk of the area.
In the preferred embodiment of the invention, when the pipeline running equipment performs acceleration movement at a part with steep pipeline trend, the pipeline running equipment is very easy to cause the excessive speed and uncontrolled in the part with steep pipeline trend due to the excessive speed and the steep pipeline trend angle, and the pipeline running equipment is damaged due to the phenomenon similar to falling in the part with steep pipeline trend angle; and when the pipeline is in a trend that is approximately 90 degrees of corners due to the limitation of the terrain, the pipeline running equipment is directly dropped to cause damage. For the above phenomenon, a part with an included angle of more than 45 degrees between the pipeline trend and the horizontal plane is taken as a falling risk area.
S8: and controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment.
Specifically, after the fall risk area is determined, the fall-preventing actions such as moving speed, steering or stopping of the pipeline running equipment are adjusted by combining the speed state of the pipeline running equipment.
According to the pipeline running equipment anti-drop control method, the running state of the pipeline running equipment is judged according to the current posture data by acquiring the current posture data of the pipeline running equipment in the pipeline, and the position parameters, namely the longitude, the latitude and the elevation, of the pipeline running equipment at any historical moment are obtained, and as the pipeline running equipment is attached to the inner wall of the pipeline to move, the current distribution track of the pipeline can be mapped according to the longitude, the latitude and the Gao Chengji of the pipeline running equipment, wherein the current distribution track of the pipeline corresponds to the current movement track of the pipeline running equipment, and after the current distribution track of the pipeline is obtained, the current distribution track of the pipeline and the corresponding terrain distribution around the pipeline are utilized, the trend of the pipeline running equipment in the future is predicted through the pipeline environment prediction network, so that the trend of the pipeline corresponding to the trend of the pipeline running equipment in the future can be obtained, the risk area of the pipeline can be found in time through the trend of the pipeline, and the anti-drop action is made in advance for the falling area in the pipeline, and the safety and the stability of the pipeline running equipment are ensured.
In the embodiment of the present invention, according to the fall risk area of the pipeline operation device and the speed state of the pipeline operation device, the controlling the pipeline operation device to perform a fall protection action corresponding to the fall risk area includes:
if the pipeline running equipment is in the alarm area and is not in the avoidance area, controlling the pipeline running equipment to send a primary alarm signal, judging whether the speed state of the pipeline running equipment is in the acceleration state, and if so, reducing the moving speed of the pipeline running equipment according to the distance between the pipeline running equipment and the avoidance area and a preset deceleration rule;
and if the pipeline running equipment is in the avoidance area, controlling the pipeline running equipment to stop moving and sending a secondary alarm signal.
In this embodiment, the anti-falling action corresponding to the pipeline running device is controlled by detecting the distance between the pipeline running device and the alarm area and the avoidance area, where when the pipeline running device enters the alarm area but does not enter the avoidance area, the moving speed of the pipeline running device needs to be reduced, so that the moving speed of the pipeline running device needs to be reduced, and the preset speed reduction rule is to reduce the speed of the pipeline running device to different degrees according to the current speed of the pipeline running device and the distance between the pipeline running device and the avoidance area, so that the speed reduction degree can be reduced when the acceleration degree is too low, the speed reduction degree can be increased when the acceleration degree is too high, and meanwhile, a first-level alarm signal is sent. When entering the avoidance area, the pipeline running equipment can be controlled to stop moving at once in the avoidance area through the deceleration operation, and a secondary alarm signal is sent.
According to the anti-falling control method for the pipeline running equipment, the alarm area and the avoidance area are set, and the alarm signal is sent, so that the pipeline running equipment can be timely controlled to perform anti-falling actions such as speed reduction and stopping, the state detection and control of the pipeline running equipment are realized, the safe and stable running of the pipeline running equipment is ensured, and the equipment is ensured to safely pass through the falling risk area.
In combination with fig. 2, in the embodiment of the present invention, S7: obtaining a fall risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the fall risk area comprises the following components:
s71: obtaining longitude, latitude and elevation of the pipeline corresponding to the trend according to the trend of the pipeline in the future preset time period;
s72: judging whether the pipeline has an area exceeding a preset safety angle and an area exceeding a preset safety height according to the longitude, the latitude and the elevation of the pipeline;
s73: and taking the area exceeding the preset safety angle and the area exceeding the preset safety height as the fall risk area of the pipeline running equipment.
In this embodiment, since the track of the pipeline is also changed due to the change of the terrain around the pipeline during the design or arrangement of the pipeline, and the arrangement form of the pipeline, such as a nearly vertical track, which is easy to cause the pipeline running device to fall, is not excluded, the pipeline running device is caused to fall in the pipeline, so that a preset safety angle capable of ensuring the safe running of the pipeline running device needs to be set according to the included angle between the pipeline and the horizontal plane.
According to the anti-falling control method for the pipeline operation equipment, the falling risk area of the pipeline is defined, the height and the angle between the pipeline and the horizontal plane are taken as influence factors to be considered, the falling risk area of the pipeline is accurately judged, the safety of the pipeline operation equipment is ensured, meanwhile, the change of the pipeline environment is known in time, and the safe operation of the pipeline is ensured.
In the embodiment of the invention, the method further comprises the following steps: establishing the pipeline environment prediction network;
the establishing the pipeline environment prediction network comprises the following steps:
acquiring an initial deep neural network;
acquiring pipeline distribution of an experimental pipeline, attitude data of the pipeline operation equipment in the operation of the experimental pipeline and terrain distribution in the preset range around the experimental pipeline, wherein the attitude data are the current attitude data corresponding to the pipeline operation equipment at any position of the experimental pipeline;
obtaining a complete motion track of the pipeline running equipment according to the pipeline distribution;
according to the complete motion trail of the pipeline running equipment, the current motion trail of the pipeline running equipment at any moment in the experimental pipeline and the future motion trail of the pipeline running equipment after the any moment are obtained;
The current motion trail and the future motion trail form the complete motion trail;
taking a current motion track of the pipeline running equipment at a preset moment, gesture data of the pipeline running equipment at the preset moment and terrain distribution in the preset range around the pipeline as inputs of the initial depth neural network, and taking the future motion track of the pipeline running equipment as outputs of the initial depth neural network for training;
and taking the trained initial deep neural network as the pipeline environment prediction network.
In this embodiment, in the pipeline environment prediction system based on the neural network, we need to perform data preprocessing and feature engineering first, extract effective feature information in the input data, and perform normalization, standardization, and other processes on the extracted feature information, i.e. establish a data set, so as to better adapt to different training algorithms and network structures. And then acquiring an initial deep neural network for training, such as a convolutional neural network, a cyclic neural network, a long-short-term memory network and the like, and adjusting and optimizing network parameters through a back propagation algorithm to finally obtain a pipeline environment prediction network with good performance and high prediction precision, wherein the pipeline environment prediction network can be obtained according to the following steps of 70:15:15, dividing the data set into a training data set, a verification data set and a test data set, when training is completed, taking the initial deep neural network as a pipeline environment prediction network, selecting a proper training strategy and an evaluation method, and performing model verification and performance test by utilizing means such as historical data, simulation and the like. In the preferred embodiment of the invention, because the pipeline environment prediction involves a complex coupling relation of multiple variables and multiple factors, early warning mechanisms such as random interference of unknown factors and processing of abnormal conditions are added when a prediction model is trained, so that the response capacity of pipeline operation equipment is improved.
According to the pipeline running equipment anti-drop control method, the trend of the pipeline running equipment in the future is predicted through the pipeline environment prediction network, so that the trend of the pipeline in the preset time period corresponding to the trend of the pipeline running equipment in the future can be obtained, and whether a drop risk area exists or not can be timely found through the trend of the pipeline, and the safety and the stability of the operation of the pipeline running equipment can be achieved.
In the embodiment of the present invention, according to the fall risk area of the pipeline operation device and the speed state of the pipeline operation device, the method controls the pipeline operation device to perform a fall protection action corresponding to the fall risk area, and further includes:
when the speed state of the pipeline running equipment is the acceleration state and the change value of the acceleration of the pipeline running equipment in a preset duration is larger than an acceleration change threshold value, controlling the pipeline running equipment to perform deceleration action;
and stopping the deceleration action of the pipeline running equipment when the change value of the acceleration of the pipeline running equipment is smaller than an acceleration change safety threshold value.
In this embodiment, when the pipeline running device is controlled to perform the anti-falling action, a corresponding policy needs to be formulated according to the speed state and the acceleration change condition of the pipeline running device. If the speed state of the pipeline running equipment is an acceleration state and the change value of the acceleration within the preset time period is larger than the preset acceleration change threshold value, the pipeline running equipment needs to be decelerated so as to avoid falling risks. Meanwhile, when the change value of the acceleration of the pipeline running equipment is smaller than the set acceleration change safety threshold value, the deceleration action can be stopped.
In the preferred embodiment of the invention, factors such as the type, specification, load and the like of the pipeline running equipment are also taken into control of the pipeline running equipment, so as to aim at special situations such as sudden braking, emergency stop and the like under different environments.
According to the anti-falling control method for the pipeline running equipment, various conditions possibly occurring under different conditions are fully considered, so that accidents and losses of the pipeline equipment are effectively reduced or avoided. Particularly, the deceleration control under the acceleration state is intelligently adjusted according to the acceleration change condition, so that the prediction and treatment of risks are enhanced, and the safety of the pipeline running equipment in high-speed movement is ensured.
In the embodiment of the invention, the method further comprises the following steps:
acquiring the inner diameter of the pipeline at a preset detection distance of the pipeline running equipment in the moving direction;
and when the inner diameter of the pipeline exceeds a preset standard value, controlling the pipeline running equipment to stop moving.
In the present embodiment, since the inner diameter of the pipe has a certain limit, if the measured inner diameter suddenly changes greatly, it is indicated that an obstacle or a drop-prone area occurs in the pipe, in the excellent embodiment of the present invention, the inner diameter of the pipe can be measured by the infrared ranging sensor, when the pipe road is flat, the ranging distance is in a normal range, and the distance change is continuous; when the infrared measuring distance of the front end is detected to be larger than the inner diameter of the pipeline, the underground cable pipeline detects that the trolley stops moving, and at the moment, the control system sends an advancing drop warning to the upper computer platform and waits for a retreating instruction.
According to the anti-drop control method for the pipeline running equipment, the pipeline running equipment is guaranteed to normally run in the pipeline by detecting the inner diameter of the pipeline, which is the same as the moving direction, of the pipeline running equipment and is located at the preset detection distance.
In an embodiment of the present invention, the obtaining, by the pipe running device, all the acceleration, the angular velocity, and the angular pose data from the start of the movement of the pipe running device to the current time, the longitude, the latitude, and the elevation of the pipe running device at any historical time includes:
obtaining longitude, latitude and elevation of the pipeline running equipment at the starting movement moment according to the starting position information of the pipeline running equipment;
the initial position information of the pipeline running equipment comprises initial position longitude and latitude and initial height;
and obtaining the longitude, latitude and elevation of the pipeline running equipment at any historical moment according to the longitude, the latitude and the elevation of the pipeline running equipment at the starting movement moment through the acceleration, the angular speed and the angular posture data of the pipeline running equipment.
In this embodiment, the starting position information of the pipeline running device may be obtained according to a positioning device such as a GPS on the pipeline running device, and on the basis of the starting position information, the obtained data may be calibrated, and the longitude, latitude and altitude of the initial moment are used as reference points, and in combination with the acceleration, angular velocity and angular posture data of the pipeline running device, the longitude, latitude and altitude of the pipeline running device at any moment later are calculated, and a corresponding pipeline trend graph is drawn. In a preferred embodiment of the present invention, kalman filtering or other filters are used to process the raw acceleration, angular velocity and angular pose data, suppress random errors, and properly increase the data update frequency and accuracy to obtain more accurate position information.
According to the anti-drop control method for the pipeline running equipment, the position of the pipeline can be rapidly judged through the position of the pipeline running equipment, so that future pipeline environments can be predicted for follow-up according to the current arrangement track of the pipeline.
Referring to fig. 3, the present invention further provides a fall protection control device 100 for a pipeline operation device, including:
a detecting unit 110, configured to obtain current gesture data of a pipeline running device, where the current gesture data includes acceleration, angular velocity, and angular gesture data of the pipeline running device;
a processing unit 120, configured to obtain a speed state of the pipe running device according to the acceleration of the pipe running device, where the speed state includes an acceleration state and a deceleration state; obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset time lengths; obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
A prediction unit 130, configured to input the current distribution track of the pipeline, the current gesture data of the pipeline running device, and a terrain distribution of the pipeline within a preset range into a pipeline environment prediction network, where the pipeline environment prediction network outputs a motion track of the pipeline running device within a preset time period in the future;
the processing unit 120 is further configured to obtain, according to a motion track of the pipeline running device in the future preset time period, a trend of the pipeline in the future preset time period;
the analysis unit 140 is configured to obtain a fall risk area of the pipeline running device according to the trend of the pipeline in the future preset time period, where the fall risk area includes an alarm area and an avoidance area, and the alarm area is greater than the avoidance area;
and the control unit 150 is used for controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment.
The control unit 150 is further configured to control the pipeline operation device to send a first-level alarm signal and determine whether the speed state of the pipeline operation device is the acceleration state if the pipeline operation device is in the alarm region and not in the avoidance region, and if yes, reduce the moving speed of the pipeline operation device according to the distance between the pipeline operation device and the avoidance region and a preset deceleration rule; and if the pipeline running equipment is in the avoidance area, controlling the pipeline running equipment to stop moving and sending a secondary alarm signal.
The analysis unit 140 is further configured to obtain longitude, latitude, and elevation of the pipeline corresponding to the trend according to the trend of the pipeline in the future preset time period; judging whether the pipeline has an area exceeding a preset safety angle and an area exceeding a preset safety height according to the longitude, the latitude and the elevation of the pipeline; and taking the area exceeding the preset safety angle and the area exceeding the preset safety height as the fall risk area of the pipeline running equipment.
Referring to fig. 4, in a preferred embodiment of the present invention, the pipeline operation device anti-drop control apparatus 100 further includes a modeling unit 160, a measuring unit 170;
the modeling unit 160 is configured to establish the pipeline environment prediction network, where the establishing the pipeline environment prediction network includes: acquiring an initial deep neural network; acquiring pipeline distribution of an experimental pipeline, attitude data of the pipeline operation equipment in the operation of the experimental pipeline and terrain distribution in the preset range around the experimental pipeline, wherein the attitude data are the current attitude data corresponding to the pipeline operation equipment at any position of the experimental pipeline; obtaining a complete motion track of the pipeline running equipment according to the pipeline distribution; according to the complete motion trail of the pipeline running equipment, the current motion trail of the pipeline running equipment at any moment in the experimental pipeline and the future motion trail of the pipeline running equipment after the any moment are obtained; the current motion trail and the future motion trail form the complete motion trail; taking a current motion track of the pipeline running equipment at a preset moment, gesture data of the pipeline running equipment at the preset moment and terrain distribution in the preset range around the pipeline as inputs of the initial depth neural network, and taking the future motion track of the pipeline running equipment as outputs of the initial depth neural network for training; and taking the trained initial deep neural network as the pipeline environment prediction network.
The control unit 150 is further configured to control the pipeline running device to perform a deceleration action when the speed state of the pipeline running device is the acceleration state and a change value of the acceleration of the pipeline running device within a preset duration is greater than an acceleration change threshold; and stopping the deceleration action of the pipeline running equipment when the change value of the acceleration of the pipeline running equipment is smaller than an acceleration change safety threshold value.
The measuring unit 170 is used for acquiring the inner diameter of the pipeline at a preset detection distance of the pipeline running equipment in the moving direction; and when the inner diameter of the pipeline exceeds a preset standard value, controlling the pipeline running equipment to stop moving.
The processing unit 120 is configured to obtain, according to starting position information of the pipe running device, longitude, latitude, and altitude of the pipe running device at the starting movement time; the initial position information of the pipeline running equipment comprises initial position longitude and latitude and initial height; and obtaining the longitude, latitude and elevation of the pipeline running equipment at any historical moment according to the longitude, the latitude and the elevation of the pipeline running equipment at the starting movement moment through the acceleration, the angular speed and the angular posture data of the pipeline running equipment.
According to the pipeline running equipment anti-drop control device, the running state of the pipeline running equipment is judged according to the current posture data by acquiring the current posture data of the pipeline running equipment in the pipeline, and the position parameters, namely the longitude, the latitude and the elevation, of the pipeline running equipment at any historical moment are obtained, and as the pipeline running equipment is attached to the inner wall of the pipeline to move, the current distribution track of the pipeline can be mapped according to the longitude, the latitude and the Gao Chengji of the pipeline running equipment, wherein the current distribution track of the pipeline corresponds to the current movement track of the pipeline running equipment, and after the current distribution track of the pipeline is obtained, the current distribution track of the pipeline and the corresponding terrain distribution around the pipeline are utilized, the trend of the pipeline running equipment in the future is predicted through the pipeline environment prediction network, so that the trend of the pipeline corresponding to the trend of the pipeline running equipment in the future can be obtained, the risk area of the pipeline can be found in time through the trend of the pipeline, and the anti-drop action is made in advance for the falling area in the pipeline, and the safety and the stability of the pipeline running equipment are ensured.
The invention also provides, in conjunction with fig. 5, a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
acquiring current gesture data of pipeline operation equipment, wherein the current gesture data comprises acceleration, angular speed and angular gesture data of the pipeline operation equipment;
obtaining a speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset interval duration;
obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
Inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the topographic distribution of the pipeline within a preset range into a pipeline environment prediction network, wherein the pipeline environment prediction network outputs the motion track of the pipeline running equipment within a preset time period in the future;
obtaining the trend of the pipeline in the future preset time period through the motion trail of the pipeline running equipment in the future preset time period;
obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area;
and controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment.
According to the computer equipment, the running state of the pipeline running equipment is judged according to the current posture data by acquiring the current posture data of the pipeline running equipment in the pipeline, and the position parameters, namely the longitude, the latitude and the elevation, of the pipeline running equipment at any historical moment are obtained, and as the pipeline running equipment is attached to the inner wall of the pipeline to move, the current distribution track of the pipeline can be mapped according to the longitude, the latitude and the Gao Chengji of the pipeline running equipment, wherein the current distribution track of the pipeline corresponds to the current movement track of the pipeline running equipment, and after the current distribution track of the pipeline is obtained, the current distribution track of the pipeline and the corresponding terrain distribution around the pipeline are utilized, the trend of the pipeline running equipment is predicted through the pipeline environment prediction network in combination with the posture data of the pipeline running equipment, so that the trend of the pipeline running equipment in the future can be obtained, and whether a falling risk area exists can be found timely through the trend of the pipeline, and the falling prevention action is made in advance for the risk area in the pipeline, and the safety and the stability of the pipeline running equipment are ensured.
The present invention also provides a computer readable storage medium having stored therein a computer program which when executed by a processor performs the steps of:
acquiring current gesture data of pipeline operation equipment, wherein the current gesture data comprises acceleration, angular speed and angular gesture data of the pipeline operation equipment;
obtaining a speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset interval duration;
obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
Inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the topographic distribution of the pipeline within a preset range into a pipeline environment prediction network, wherein the pipeline environment prediction network outputs the motion track of the pipeline running equipment within a preset time period in the future;
obtaining the trend of the pipeline in the future preset time period through the motion trail of the pipeline running equipment in the future preset time period;
obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area;
and controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment.
According to the computer readable storage medium, the running state of the pipeline running equipment is judged according to the current posture data by acquiring the current posture data of the pipeline running equipment in the pipeline, and the position parameters, namely the longitude, the latitude and the elevation, of the pipeline running equipment at any historical moment are obtained, and as the pipeline running equipment is attached to the inner wall of the pipeline to move, the current distribution track of the pipeline can be mapped according to the longitude, the latitude and the Gao Chengji of the pipeline running equipment, wherein the current distribution track of the pipeline corresponds to the current movement track of the pipeline running equipment, and after the current distribution track of the pipeline is obtained, the current distribution track of the pipeline and the corresponding terrain distribution around the pipeline are utilized, the trend of the pipeline running equipment in the future is predicted through the pipeline environment prediction network, so that the trend of the pipeline corresponding to the trend of the pipeline running equipment in the future can be obtained, the risk area can be found in time through the trend of the pipeline, and the falling-down prevention action is performed in advance for the risk area in the pipeline, and the safety and the stability of the operation of the pipeline running equipment are ensured.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A method for fall control of a pipeline operation device, comprising:
step S1: acquiring current gesture data of pipeline operation equipment, wherein the current gesture data comprises acceleration, angular speed and angular gesture data of the pipeline operation equipment;
step S2: obtaining a speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
step S3: obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset interval duration;
step S4: obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
Step S41: establishing a pipeline environment prediction network;
the step S41 specifically includes:
step S411: acquiring an initial deep neural network;
step S412: acquiring pipeline distribution of an experimental pipeline, attitude data of the pipeline operation equipment in the operation of the experimental pipeline and terrain distribution in a preset range around the experimental pipeline, wherein the attitude data are the current attitude data corresponding to the pipeline operation equipment at any position of the experimental pipeline;
step S413: obtaining a complete motion track of the pipeline running equipment according to the pipeline distribution;
step S414: according to the complete motion trail of the pipeline running equipment, the current motion trail of the pipeline running equipment at any moment in the experimental pipeline and the future motion trail of the pipeline running equipment after the any moment are obtained;
the current motion trail and the future motion trail form the complete motion trail;
step S415: taking a current motion track of the pipeline running equipment at a preset moment, gesture data of the pipeline running equipment at the preset moment and terrain distribution in the preset range around the pipeline as inputs of the initial depth neural network, and taking the future motion track of the pipeline running equipment as outputs of the initial depth neural network for training;
Step S416: taking the initial deep neural network after training as the pipeline environment prediction network;
step S5: inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the topographic distribution of the pipeline within a preset range into a pipeline environment prediction network, wherein the pipeline environment prediction network outputs the motion track of the pipeline running equipment within a preset time period in the future;
step S6: obtaining the trend of the pipeline in the future preset time period through the motion trail of the pipeline running equipment in the future preset time period;
step S7: obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area; the step S7 specifically comprises the following steps:
step S71: obtaining longitude, latitude and elevation of the pipeline corresponding to the trend according to the trend of the pipeline in the future preset time period;
step S72: judging whether the pipeline has an area exceeding a preset safety angle and an area exceeding a preset safety height according to the longitude, the latitude and the elevation of the pipeline;
Step S73: taking the area exceeding the preset safety angle and the area exceeding the preset safety height as the fall risk area of the pipeline running equipment;
step S8: according to the falling risk area of the pipeline running equipment and the speed state of the pipeline running equipment, controlling the pipeline running equipment to perform falling prevention actions corresponding to the falling risk area, wherein the step S8 specifically comprises the following steps:
step S81: if the pipeline running equipment is in the alarm area and is not in the avoidance area, controlling the pipeline running equipment to send a primary alarm signal, judging whether the speed state of the pipeline running equipment is in the acceleration state, and if so, reducing the moving speed of the pipeline running equipment according to the distance between the pipeline running equipment and the avoidance area and a preset deceleration rule;
step S82: and if the pipeline running equipment is in the avoidance area, controlling the pipeline running equipment to stop moving and sending a secondary alarm signal.
2. The method for controlling a pipeline operation device according to claim 1, wherein the controlling the pipeline operation device to perform a fall prevention action corresponding to the fall risk region according to the fall risk region of the pipeline operation device and the speed state of the pipeline operation device further comprises:
When the speed state of the pipeline running equipment is the acceleration state and the change value of the acceleration of the pipeline running equipment in a preset duration is larger than an acceleration change threshold value, controlling the pipeline running equipment to perform deceleration action;
and stopping the deceleration action of the pipeline running equipment when the change value of the acceleration of the pipeline running equipment is smaller than an acceleration change safety threshold value.
3. The pipe running apparatus fall control method according to claim 1, further comprising:
acquiring the inner diameter of the pipeline at a preset detection distance of the pipeline running equipment in the moving direction;
and when the inner diameter of the pipeline exceeds a preset standard value, controlling the pipeline running equipment to stop moving.
4. The method for controlling a pipeline operation device to prevent a drop according to claim 1, wherein obtaining, by using all the acceleration, the angular velocity and the angular pose data of the pipeline operation device from a start moving time to a current time, longitude, latitude and altitude of the pipeline operation device at any historical time comprises:
obtaining longitude, latitude and elevation of the pipeline running equipment at the starting movement moment according to the starting position information of the pipeline running equipment;
The initial position information of the pipeline running equipment comprises initial position longitude and latitude and initial height;
and obtaining the longitude, latitude and elevation of the pipeline running equipment at any historical moment according to the longitude, the latitude and the elevation of the pipeline running equipment at the starting movement moment through the acceleration, the angular speed and the angular posture data of the pipeline running equipment.
5. A pipeline operation equipment anti-fall control device, characterized in that a pipeline operation equipment anti-fall control method according to any one of claims 1 to 4 is implemented, the pipeline operation equipment anti-fall control device comprising:
the detection unit is used for acquiring current gesture data of the pipeline running equipment, wherein the current gesture data comprise acceleration, angular speed and angular gesture data of the pipeline running equipment;
the processing unit is used for obtaining the speed state of the pipeline running equipment according to the acceleration of the pipeline running equipment, wherein the speed state comprises an acceleration state and a deceleration state;
obtaining longitude, latitude and altitude of the pipeline running equipment at any historical moment according to all the acceleration, the angular speed and the angular posture data of the pipeline running equipment from the starting movement moment to the current moment, wherein the historical moment is any moment from the starting movement moment to the current moment, and the adjacent historical moments are preset time lengths;
Obtaining a motion track of the pipeline running equipment by using the longitude, latitude and elevation of the pipeline running equipment at all the historical moments, and taking the motion track of the pipeline running equipment as a current distribution track of the pipeline, wherein the longitude, latitude and elevation of all the historical moments consist of the longitude, latitude and elevation of any one of the historical moments;
establishing a pipeline environment prediction network; the establishing a pipeline environment prediction network comprises the following steps: acquiring an initial deep neural network; acquiring pipeline distribution of an experimental pipeline, attitude data of the pipeline operation equipment in the operation of the experimental pipeline and terrain distribution in the preset range around the experimental pipeline, wherein the attitude data are the current attitude data corresponding to the pipeline operation equipment at any position of the experimental pipeline; obtaining a complete motion track of the pipeline running equipment according to the pipeline distribution; according to the complete motion trail of the pipeline running equipment, the current motion trail of the pipeline running equipment at any moment in the experimental pipeline and the future motion trail of the pipeline running equipment after the any moment are obtained; the current motion trail and the future motion trail form the complete motion trail; taking a current motion track of the pipeline running equipment at a preset moment, gesture data of the pipeline running equipment at the preset moment and terrain distribution in the preset range around the pipeline as inputs of the initial depth neural network, and taking the future motion track of the pipeline running equipment as outputs of the initial depth neural network for training;
The prediction unit is used for inputting the current distribution track of the pipeline, the current gesture data of the pipeline running equipment and the terrain distribution of the pipeline within a preset range into a pipeline environment prediction network, and outputting the motion track of the pipeline running equipment within a future preset time period by the pipeline environment prediction network;
the processing unit is further used for obtaining the trend of the pipeline in the future preset time period through the motion track of the pipeline running equipment in the future preset time period;
the analysis unit is used for obtaining a falling risk area of the pipeline running equipment according to the trend of the pipeline in the future preset time period, wherein the falling risk area comprises an alarm area and an avoidance area, and the alarm area is larger than the avoidance area;
obtaining longitude, latitude and elevation of the pipeline corresponding to the trend according to the trend of the pipeline in the future preset time period; judging whether the pipeline has an area exceeding a preset safety angle and an area exceeding a preset safety height according to the longitude, the latitude and the elevation of the pipeline; taking the area exceeding the preset safety angle and the area exceeding the preset safety height as the fall risk area of the pipeline running equipment;
The control unit is used for controlling the pipeline running equipment to perform anti-falling actions corresponding to the falling risk areas according to the falling risk areas of the pipeline running equipment and the speed state of the pipeline running equipment;
if the pipeline running equipment is in the alarm area and is not in the avoidance area, controlling the pipeline running equipment to send a primary alarm signal, judging whether the speed state of the pipeline running equipment is in the acceleration state, and if so, reducing the moving speed of the pipeline running equipment according to the distance between the pipeline running equipment and the avoidance area and a preset deceleration rule; and if the pipeline running equipment is in the avoidance area, controlling the pipeline running equipment to stop moving and sending a secondary alarm signal.
6. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the pipeline operation device fall arrest control method of any one of claims 1 to 4 when the computer program is executed by the processor.
7. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the fall protection control method of a pipeline operation device according to any one of claims 1 to 4.
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