CN113431550A - Anti-impact drilling robot drilling tool attitude determination method based on redundant inertial unit - Google Patents
Anti-impact drilling robot drilling tool attitude determination method based on redundant inertial unit Download PDFInfo
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- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B7/00—Special methods or apparatus for drilling
- E21B7/02—Drilling rigs characterised by means for land transport with their own drive, e.g. skid mounting or wheel mounting
- E21B7/025—Rock drills, i.e. jumbo drills
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- E21—EARTH OR ROCK DRILLING; MINING
- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B44/00—Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
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- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B15/00—Supports for the drilling machine, e.g. derricks or masts
- E21B15/003—Supports for the drilling machine, e.g. derricks or masts adapted to be moved on their substructure, e.g. with skidding means; adapted to drill a plurality of wells
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- E21B—EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B15/00—Supports for the drilling machine, e.g. derricks or masts
- E21B15/04—Supports for the drilling machine, e.g. derricks or masts specially adapted for directional drilling, e.g. slant hole rigs
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- E21B47/00—Survey of boreholes or wells
- E21B47/02—Determining slope or direction
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Abstract
The invention discloses an anti-impact drilling robot drilling tool attitude determination method based on redundant inertial units, which comprises the following steps: respectively fixedly connecting five paths of inertia units to the top point and the center of a tetrahedron to form an inertia sensor; carrying out self-defined fusion formula operation on the five paths of inertial unit data according to a set proportion; guiding the attitude error model measured by the inertial sensor into a neural network for training to obtain a trained neural network prediction model; importing data measured by an inertial sensor into a trained neural network model for error prediction; and leading the prediction error of the neural network into a calculation result of the inertial sensor, and compensating the calculation result. Has the advantages that: the invention effectively reduces the number of working people, effectively reduces the labor capacity, effectively improves the drilling efficiency and can meet the requirements of quick erosion prevention and pressure relief drilling.
Description
Technical Field
The invention relates to the technical field of anti-impact drilling robot drilling tool attitude determination methods, in particular to an anti-impact drilling robot drilling tool attitude determination method based on a redundant inertial unit.
Background
Along with the development of science and technology, the automation degree of the underground drilling equipment is remarkably improved. The coal mine anti-impact drilling robot is used for construction of various engineering holes such as anti-impact pressure relief holes. The conventional coal mine drilling machine usually adjusts the posture of the drilling machine at a fixed position, and simultaneously needs 1 or 2 persons for assistance to observe the operation condition of the rack, so that the drilling efficiency is low, and the labor intensity of constructors is high. The requirement of quick scour prevention and pressure relief drilling cannot be met. In order to improve the use performance of the drilling machine and realize the reduction and the increase of the labor, the drilling machine is required to automatically adjust the posture of the drilling tool, and the automatic adjustment of the drilling tool is based on the accurate posture of the drilling tool.
Therefore, a method for determining the posture of the drilling tool of the anti-impact drilling robot is needed to solve the above problems.
Disclosure of Invention
In order to comprehensively solve the problems, particularly aiming at the defects in the prior art, the invention provides the anti-impact drilling robot drilling tool attitude determination method based on the redundant inertial unit, which can comprehensively solve the problems.
In order to achieve the purpose, the invention adopts the following technical means:
an anti-impact drilling robot drilling tool attitude determination method based on a redundant inertial unit comprises the following steps:
s1, respectively and fixedly connecting the five paths of inertia units to the top point and the center of the tetrahedron to form an inertia sensor;
s2, carrying out self-defined fusion formula operation on the five paths of inertial unit data according to a set proportion;
s3, leading the attitude error model measured by the inertial sensor into a neural network for training to obtain a trained neural network prediction model;
s4, importing the data measured by the inertial sensor into a trained neural network model for error prediction;
and S5, introducing the neural network prediction error into the calculation result of the inertial sensor, and compensating the neural network prediction error.
Preferably, the inertial sensor is fixedly connected to the side part of the movement mechanism of the anti-impact drilling robot, and the inertial sensor acquires angular velocity, acceleration and magnetic force information of the movement mechanism;
the inertial sensor is in communication connection with a microcomputer through a communication line, and the microcomputer reads and stores data acquired by the inertial sensor;
the microcomputer is connected with the PC upper computer, the microcomputer sends the stored data to the PC upper computer, the PC upper computer performs fusion of five paths of data, denoising and filtering operations are performed on the fused data, and the data are displayed.
Preferably, the protecting against shock drilling robot includes protecting against shock drilling robot base, the top of protecting against shock drilling robot base is equipped with the azimuth rotation mechanism that rotates the connection, azimuth rotation mechanism's top is provided with the angle of pitch motion, the angle of pitch motion passes through the pneumatic cylinder and is connected with azimuth rotation mechanism goes up and down, the angle of pitch motion still is connected with azimuth rotation mechanism direction through the guide post, the outside of angle of pitch motion is provided with the drilling rod, the drilling rod passes through the frame and is connected with angle of pitch motion, inertial sensor is connected with angle of pitch motion's lateral wall.
Preferably, the inertial unit is an MPU9250 inertial unit manufactured by InvernSense corporation.
Preferably, the microcomputer is a Raspberry PI4Model B manufactured by amazon corporation.
Preferably, the inertial unit MPU9250 communicates with the microcomputer via I2C protocol.
Preferably, the microcomputer is simultaneously connected with 5 inertial units through an I2C interface, and the microcomputer accesses each MPU9250 one by one to read data, so that the data acquisition of the inertial sensors is realized.
Preferably, the data stored by the microcomputer is transmitted to the PC upper computer by the microcomputer through a serial port line.
Preferably, the fusion of the five paths of data is operated according to a custom fusion formula in a ratio of 4:1.5:1.5:1.5: 1.5.
Preferably, the denoising algorithm employs wavelet threshold denoising.
The invention has the beneficial effects that: according to the invention, the operation condition of the rack does not need to be observed manually, the angular velocity, the acceleration and the magnetic force information of the movement mechanism of the anti-impact drilling robot can be collected through the inertial sensor, the inertial sensor transmits the collected information to the microcomputer through a communication line, the microcomputer sends the obtained data information to the PC upper computer, the PC upper computer performs five-path data fusion, the fused data is subjected to denoising and filtering operation and is displayed, and the posture of the drilling tool can be automatically adjusted rapidly and accurately through the finally obtained data drilling machine, so that the working number is effectively reduced, the labor capacity is effectively reduced, the drilling efficiency is effectively improved, and the requirement of rapid anti-impact pressure-relief drilling can be met.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an anti-impact drilling robot drilling tool attitude determination method based on a redundant inertial unit of the present invention;
FIG. 2 is a distribution diagram of a redundant arrangement of five inertial units according to the present invention;
FIG. 3 is a first schematic structural view of the impact drilling robot of the present invention;
FIG. 4 is a second schematic structural view of the impact drilling robot of the present invention;
FIG. 5 is a flow chart of the inertial unit error compensation algorithm for optimizing the BP neural network based on the genetic algorithm.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
As shown in fig. 1 to 5, the invention provides a drilling tool attitude determination method for an anti-impact drilling robot based on a redundant inertial unit, the anti-impact drilling robot comprises an anti-impact drilling robot base 11, an azimuth angle slewing mechanism 12 in rotary connection is arranged at the top end of the anti-impact drilling robot base 11, a pitch angle movement mechanism 17 is arranged at the top end of the azimuth angle slewing mechanism 12, the pitch angle movement mechanism 17 is in lifting connection with the azimuth angle slewing mechanism 12 through a hydraulic cylinder 16, the pitch angle movement mechanism 17 is also in guiding connection with the azimuth angle slewing mechanism 12 through a guide column 13, a drill rod 15 is arranged outside the pitch angle movement mechanism 17, and the drill rod 15 is connected with the pitch angle movement mechanism 17 through a rack 14. Firstly, five paths of inertial units are arranged at the vertex and the center of a tetrahedron to form an inertial sensor 18, the inertial sensor 18 is fixedly connected to the side wall of a pitch angle movement mechanism 17 of an anti-impact drilling robot drilling tool, then the inertial sensor 18 is communicated with a raspberry group through a communication line, and then the raspberry group is connected with a PC upper computer. This platform gathers angular velocity, acceleration and magnetic force information through installing inertial sensor 18 at protecting against shock drilling robot frame to send through the raspberry and read and save inertial sensor 18 and gather data, then send the data that the raspberry was saved to the PC host computer, the fusion of five data is carried out to the PC host computer, and the data after will fusing is denoised and the filtering operation is and is shown data. The inertial unit adopts MPU9250 inertial unit manufactured by InvernSense company, and Raspberry PI4Model B manufactured by Amazon company. The communication between the inertial unit MPU9250 and the raspberry pi adopts an I2C protocol for communication. The raspberry pie is connected with 5 MPUs 9250 through an I2C interface, and accesses each MPU9250 one by one to read data, so that data acquisition of the inertial sensor 18 is realized. The raspberry pi processor transmits the stored data to the PC upper computer through a serial port line.
And the fusion of the five paths of data is operated according to a self-defined fusion formula in a ratio of 4:1.5:1.5:1.5:1.5 according to a more accurate principle that the inertial unit measures at the central position of the carrier.
The denoising algorithm adopts wavelet threshold denoising, and the principle is that a threshold is set for a wavelet coefficient, the wavelet coefficient higher than the threshold is completely reserved or reserved after proper contraction, the wavelet coefficient lower than the threshold is completely zeroed, and then a wavelet reconstruction signal which is not zeroed is selected to obtain a denoised signal.
As shown in fig. 2, each circle in the figure represents an MPU9250 inertial unit, and the cross in the circle indicates that the thumb points inward when the four fingers of the right hand are turned from the x-axis to the y-axis, i.e., the z-axis points from the outer finger to the inner finger, according to the right hand screw rule. If the circle is a point, the thumb is outward when the four fingers of the right hand are turned from the x axis to the y axis, i.e., the z axis is inward and outward. As can be seen from the figure, the sensitive axes of the inertia units on the four vertexes of the rhomboid are not completely consistent in pointing direction, and the included angle of the two inconstant axes is a straight angle. The structure greatly reduces the fixed offset error caused by external factors such as temperature, vibration and the like when the inertial unit is used for measuring, the undetermined error of the inertial unit measurement is offset to a great extent, and various errors such as certain cone error and the like can be eliminated, so that the measurement accuracy of the inertial system is greatly improved.
According to the tetrahedral symmetrical installation layout mode adopted by the inertial unit and the measurement principle of the inertial unit, a fusion equation of the sensor can be obtained:
the inertial unit MPU9250 angular velocity data fusion equation is as follows:
the inertial unit MPU9250 acceleration fusion equation is as follows:
after the above formula is established, the parameters of the measured carrier of the redundant inertial unit can be obtained
As shown in fig. 5, the flow of the specific inertial unit error compensation algorithm is as follows:
(1) the BP neural network structure determining part determines according to the number of input and output parameters of the fitting function, and further determines the length of the genetic algorithm individual. And optimizing the weight and the threshold of the BP neural network by using a genetic algorithm, wherein each individual in the population comprises all the weight and the threshold of one network, the individual calculates the individual fitness value through a fitness function, and the genetic algorithm finds the individual corresponding to the optimal fitness value through selection, intersection and variation operations. And (3) the BP neural network prediction obtains the optimal individual to network initial test weight and threshold assignment by using a genetic algorithm, and the network predicts function output after being trained.
(2) And importing the data fused by the multiple redundant inertial unit sensors into the trained neural network, and then obtaining a measurement error prediction value of the inertial unit.
(3) And compensating the fused data according to the predicted measurement error of the inertial unit to obtain more accurate data, and leading the obtained accurate data into an attitude calculation program to obtain more accurate drilling tool attitude of the anti-impact drilling robot.
The present invention is illustrated by way of example and not by way of limitation. It will be apparent to those skilled in the art that other variations and modifications may be made in the foregoing disclosure without departing from the spirit or essential characteristics of all embodiments, and that all changes and modifications apparent from the above teachings are within the scope of the invention.
Claims (10)
1. An anti-impact drilling robot drilling tool attitude determination method based on a redundant inertial unit is characterized by comprising the following steps:
s1, respectively and fixedly connecting the five paths of inertia units to the top point and the center of the tetrahedron to form an inertia sensor;
s2, carrying out self-defined fusion formula operation on the five paths of inertial unit data according to a set proportion;
s3, leading the attitude error model measured by the inertial sensor into a neural network for training to obtain a trained neural network prediction model;
s4, importing the data measured by the inertial sensor into a trained neural network model for error prediction;
and S5, introducing the neural network prediction error into the calculation result of the inertial sensor, and compensating the neural network prediction error.
2. The anti-impact drilling robot drilling tool attitude determination method based on the redundant inertial unit is characterized in that the inertial sensor is fixedly connected to the side part of the anti-impact drilling robot movement mechanism, and the inertial sensor acquires angular velocity, acceleration and magnetic force information of the movement mechanism;
the inertial sensor is in communication connection with a microcomputer through a communication line, and the microcomputer reads and stores data acquired by the inertial sensor;
the microcomputer is connected with the PC upper computer, the microcomputer sends the stored data to the PC upper computer, the PC upper computer performs fusion of five paths of data, denoising and filtering operations are performed on the fused data, and the data are displayed.
3. The method as claimed in claim 2, wherein the anti-impact drilling robot comprises an anti-impact drilling robot base, an azimuth angle swing mechanism is rotatably connected to the top end of the anti-impact drilling robot base, a pitch angle movement mechanism is arranged at the top end of the azimuth angle swing mechanism, the pitch angle movement mechanism is connected to the azimuth angle swing mechanism in a lifting manner through a hydraulic cylinder, the pitch angle movement mechanism is further connected to the azimuth angle swing mechanism in a guiding manner through a guide column, a drill rod is arranged outside the pitch angle movement mechanism, the drill rod is connected to the pitch angle movement mechanism through a frame, and the inertial sensor is connected to a side wall of the pitch angle movement mechanism.
4. The method of claim 3, wherein the inertial unit is an MPU9250 inertial unit manufactured by InvernSense.
5. The redundant inertial unit-based anti-impact drilling robot tool pose determination method according to claim 4, wherein the microcomputer is a Raspberry PI4Model B manufactured by amazon corporation.
6. The anti-impact drilling robot drilling tool attitude determination method based on the redundant inertial unit according to claim 5, characterized in that the inertial unit MPU9250 communicates with a microcomputer through an I2C protocol.
7. The anti-impact drilling robot drilling tool attitude determination method based on the redundant inertial units as claimed in claim 6, wherein the microcomputer is simultaneously connected with 5 inertial units through an I2C interface, and the microcomputer accesses each MPU9250 one by one to read data, so as to realize the acquisition of inertial sensor data.
8. The anti-impact drilling robot drilling tool attitude determination method based on the redundant inertial unit according to claim 7, wherein the microcomputer transmits data stored by the microcomputer to a PC upper computer through a serial port line.
9. The anti-impact drilling robot drilling tool attitude determination method based on the redundant inertial unit is characterized in that the five-way data fusion is operated according to a custom fusion formula in a ratio of 4:1.5:1.5:1.5: 1.5.
10. The redundant inertial unit-based anti-impact drilling robot drilling tool pose determination method according to claim 9, wherein the denoising algorithm employs wavelet threshold denoising.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110760994.7A CN113431550B (en) | 2021-07-06 | 2021-07-06 | Anti-impact drilling robot drilling tool attitude determination method based on redundant inertial unit |
| NL2032291A NL2032291B1 (en) | 2021-07-06 | 2022-06-27 | Attitude determination method for drilling tool of drilling robot for rockburst prevention based on redundant inertial units |
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| CN202110760994.7A CN113431550B (en) | 2021-07-06 | 2021-07-06 | Anti-impact drilling robot drilling tool attitude determination method based on redundant inertial unit |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114718546A (en) * | 2022-04-01 | 2022-07-08 | 中国矿业大学 | Novel anti-impact drilling robot pose adjusting method for spatial distribution IMU |
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| US6315062B1 (en) * | 1999-09-24 | 2001-11-13 | Vermeer Manufacturing Company | Horizontal directional drilling machine employing inertial navigation control system and method |
| CN202562485U (en) * | 2012-03-02 | 2012-11-28 | 江阴中科矿业安全科技有限公司 | Drill carriage attitude measurement system based on monocular vision |
| CN103291216A (en) * | 2012-03-02 | 2013-09-11 | 江阴中科矿业安全科技有限公司 | Orientation system for horizontal drill of deep-hole drill carriage |
| CN107390246A (en) * | 2017-07-06 | 2017-11-24 | 电子科技大学 | A kind of GPS/INS Combinated navigation methods based on genetic neural network |
| CN109059909A (en) * | 2018-07-23 | 2018-12-21 | 兰州交通大学 | Satellite based on neural network aiding/inertial navigation train locating method and system |
| CN109186589A (en) * | 2018-07-19 | 2019-01-11 | 中国矿业大学 | A kind of coalcutter localization method based on array inertance element |
-
2021
- 2021-07-06 CN CN202110760994.7A patent/CN113431550B/en active Active
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- 2022-06-27 NL NL2032291A patent/NL2032291B1/en active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6315062B1 (en) * | 1999-09-24 | 2001-11-13 | Vermeer Manufacturing Company | Horizontal directional drilling machine employing inertial navigation control system and method |
| CN202562485U (en) * | 2012-03-02 | 2012-11-28 | 江阴中科矿业安全科技有限公司 | Drill carriage attitude measurement system based on monocular vision |
| CN103291216A (en) * | 2012-03-02 | 2013-09-11 | 江阴中科矿业安全科技有限公司 | Orientation system for horizontal drill of deep-hole drill carriage |
| CN107390246A (en) * | 2017-07-06 | 2017-11-24 | 电子科技大学 | A kind of GPS/INS Combinated navigation methods based on genetic neural network |
| CN109186589A (en) * | 2018-07-19 | 2019-01-11 | 中国矿业大学 | A kind of coalcutter localization method based on array inertance element |
| CN109059909A (en) * | 2018-07-23 | 2018-12-21 | 兰州交通大学 | Satellite based on neural network aiding/inertial navigation train locating method and system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114718546A (en) * | 2022-04-01 | 2022-07-08 | 中国矿业大学 | Novel anti-impact drilling robot pose adjusting method for spatial distribution IMU |
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| NL2032291B1 (en) | 2023-12-14 |
| CN113431550B (en) | 2023-07-14 |
| NL2032291A (en) | 2023-01-10 |
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