CN113586028B - Intelligent monitoring system of counter bore cutter head of anti-well drilling machine based on digital twin - Google Patents
Intelligent monitoring system of counter bore cutter head of anti-well drilling machine based on digital twin Download PDFInfo
- Publication number
- CN113586028B CN113586028B CN202110823235.0A CN202110823235A CN113586028B CN 113586028 B CN113586028 B CN 113586028B CN 202110823235 A CN202110823235 A CN 202110823235A CN 113586028 B CN113586028 B CN 113586028B
- Authority
- CN
- China
- Prior art keywords
- hob
- formation
- monitoring system
- twin
- reamer head
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000005553 drilling Methods 0.000 title claims abstract description 29
- 238000012544 monitoring process Methods 0.000 title claims abstract description 24
- 238000005299 abrasion Methods 0.000 claims abstract description 43
- 238000001514 detection method Methods 0.000 claims abstract description 15
- 230000036541 health Effects 0.000 claims abstract description 14
- 230000015572 biosynthetic process Effects 0.000 claims description 43
- 238000005755 formation reaction Methods 0.000 claims description 43
- 239000011435 rock Substances 0.000 claims description 19
- 238000000034 method Methods 0.000 claims description 15
- 238000012502 risk assessment Methods 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 5
- 230000000007 visual effect Effects 0.000 claims description 5
- 239000002245 particle Substances 0.000 claims description 2
- 230000035515 penetration Effects 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 4
- 230000008569 process Effects 0.000 description 3
- 230000006872 improvement Effects 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP 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
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B2200/00—Special features related to earth drilling for obtaining oil, gas or water
- E21B2200/20—Computer models or simulations, e.g. for reservoirs under production, drill bits
Abstract
The invention provides an intelligent monitoring system based on a digital twin reamer head of a well reversing drill, which comprises: the cutter head abrasion loss detection device comprises a data acquisition module, a digital twin body and a health detection module, wherein the data acquisition module is used for acquiring cutter head abrasion loss; the digital twins comprise visualized cutterhead twins; the health detection module is used for updating the cutter disc twin body in real time according to the cutter disc abrasion loss, so that the abrasion condition of the cutter disc is monitored. The intelligent monitoring system based on the digital twin reamer head of the anti-well drilling machine provided by the invention adopts the digital twin technology to adjust parameters of the reamer head in real time, so that the wear of the reamer head is reduced, and the accident rate is reduced.
Description
Technical Field
The invention belongs to the field of well drilling of a well, and particularly relates to an intelligent monitoring system of a reaming cutter head of a well drilling machine based on digital twinning.
Background
The digital twin is to fully utilize data such as a physical model, sensor update, operation history and the like, integrate simulation processes of multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities, and complete mapping in a virtual space so as to reflect the full life cycle process of corresponding entity equipment. The technology has subversion, namely, the technology can completely bypass a real object and directly simulate, simulate and predict through controlling a digital twin body.
The well reversing drilling machine is widely applied to engineering construction such as mine development and subway tunnel. Under the complex condition of the rock stratum, the cutter head of the well reversing drill is positioned in different geological layers and can be worn and vibrated to different degrees, when the composite stratum works, the surrounding rock of the cavity is different in property, the compressive strength of the rock is greatly different, and periodical unbalanced force and overturning moment are faced, so that the working environment of the large-diameter well reversing drill is further deteriorated, and even the eccentric posture of the cutter head is difficult to control when the condition is serious. In order to reduce abrasion and improve working efficiency, a worker needs to judge the geological environment of the cutter head in time and adjust parameters such as the weight on bit, the drilling speed and the like. However, at present, operators judge the geological environment by observing the mud components circulated to the earth surface, adjust parameters of the cutterhead by working experience, have poor instantaneity, finally cause serious abrasion of the cutterhead, damage drill bits and even cause accidents such as drill sticking.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an intelligent monitoring system of a reamer head of a well reversing drilling machine based on digital twinning, which adopts the digital twinning technology to adjust parameters of the reamer head in real time, thereby reducing the wear of the reamer head and reducing the accident rate.
The invention provides an intelligent monitoring system based on a digital twin reamer head of a well reversing drill, which comprises: a data acquisition module, a digital twin body and a health detection module,
the data acquisition module is used for acquiring the wear amount of the cutterhead;
the digital twin body comprises a visual cutterhead twin body;
the health detection module is used for updating the cutter disc twin body in real time according to the cutter disc abrasion loss, so that the abrasion condition of the cutter disc is monitored.
The intelligent monitoring system based on the digital twin reamer head of the anti-well drilling machine provided by the invention has the following working principle: the state of the cutterhead is monitored in real time through digital twin body visualization, and remote guiding personnel adjust parameters of the cutterhead in real time, so that abrasion of the cutterhead is reduced, and the accident rate is reduced.
According to an embodiment of the invention, the data acquisition module is further used for acquiring the weight on bit, the rotating speed and the torque of the cutterhead, and the health detection module can conduct simulation analysis on the abrasion condition of the cutterhead according to the weight on bit, the rotating speed and the torque, predict the abrasion speed of the cutterhead, adjust the weight on bit, the rotating speed and the torque of the cutterhead in real time and reduce the actual abrasion speed of the cutterhead.
According to an embodiment of the present invention, the digital twins further comprise visualized formation twins.
According to an embodiment of the present invention, the data obtaining module is further configured to obtain a position parameter of the cutterhead, and update a position of the cutterhead twins in the formation twins.
According to an embodiment of the present invention, the data acquisition module is further configured to obtain geological data of a current depth, and update a formation twins of a corresponding depth.
According to one embodiment of the present invention, the geological data required for constructing the formation twins is obtained by:
and installing a while-drilling sensor on the pilot hole drill bit, and synchronously obtaining geological data of continuous depth during pilot hole.
According to an embodiment of the present invention, the intelligent monitoring system further includes a formation database, wherein the formation database classifies formations according to geological data, and each type of formation corresponds to an applicable cutterhead.
According to an embodiment of the present invention, the formation database further groups each type of formation according to geological data, each group of formations corresponding to a set of applicable hob configurations.
According to an embodiment of the present invention, the step of constructing the formation twins includes:
a formation model is constructed from pre-obtained geological data,
classifying and grouping the formation models according to the formation database.
According to an embodiment of the present invention, the health detection module is further configured to perform risk assessment.
According to an embodiment of the present invention, the step of constructing a cutterhead twins includes:
step 1, establishing a physical model;
step 2, building a logic model according to the physical model built in the step 1;
and 3, establishing a cutter head twin body driven by the logic model.
Detailed Description
Embodiments of the technical scheme of the present invention will be described in detail below. The following examples are only for more clearly illustrating the technical aspects of the present invention, and thus are merely examples, and are not intended to limit the scope of the present invention.
It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.
The intelligent monitoring system based on digital twin reamer head of the well reversing drill provided by the embodiment comprises: the system comprises a data acquisition module, a digital twin body and a health detection module.
The data acquisition module is used for acquiring the wear amount of the cutterhead; the digital twins comprise visualized cutterhead twins; the health detection module can update the cutter disc twin body in real time according to the cutter disc abrasion loss, so that the abrasion condition of the cutter disc is monitored.
The state of the cutterhead is monitored in real time through digital twin body visualization, and remote guiding personnel adjust parameters of the cutterhead in real time, so that abrasion of the cutterhead is reduced, and the accident rate is reduced.
Specifically, the data acquisition module is also used for acquiring the bit pressure, the rotating speed and the torque of the cutterhead, the health detection module can carry out simulation analysis on the abrasion condition of the cutterhead according to the bit pressure, the rotating speed and the torque, predict the abrasion speed of the cutterhead, adjust the bit pressure, the rotating speed and the torque of the cutterhead in real time and reduce the actual abrasion speed of the cutterhead. The wear rate refers to the amount of wear of the cutterhead per unit length of drill. The cutter head is provided with a wear monitor and a while-drilling sensor, the wear monitor is used for obtaining the wear of the cutter head, and the while-drilling sensor is used for obtaining parameters such as weight on bit, rotating speed, torque and the like. And adjusting the working state of the cutterhead in real time according to the predicted cutterhead abrasion speed, so that the abrasion loss is reduced.
More specifically, the digital twins also include visual formation twins. And constructing a rock stratum twin body according to depth through the geological data obtained in advance.
More specifically, the data acquisition module is further used for acquiring position parameters of the cutterhead and updating the position of the cutterhead twins in the rock stratum twins. The position parameter is the current depth of the cutterhead.
More specifically, the data acquisition module is further configured to obtain geological data of a current depth and update a formation twins of a corresponding depth. Geological data is obtained by a while-drilling sensor, comprising: formation pressure and formation moisture.
More specifically, the geological data required to construct a formation twins is obtained by:
and installing a while-drilling sensor on the pilot hole drill bit, and synchronously obtaining geological data of continuous depth during pilot hole. The method for acquiring the geological parameters of the continuous depth comprises the following steps: when the drill is used for guiding holes, a while-drilling sensor is arranged on the drill bit of the guide holes and used for obtaining geological data such as depth, formation pressure, formation humidity and the like.
More specifically, the intelligent monitoring system further comprises a stratum database, the stratum database classifies strata according to geological data, each stratum corresponds to one applicable cutterhead, and the cutterhead is used for quickly selecting types.
More specifically, the formation database also groups each type of formation according to geological data, each group of formations corresponding to a set of applicable hob configurations. The method is used for quickly selecting the hob configuration of the cutterhead.
More specifically, the step of constructing a formation twins includes:
constructing a rock stratum model according to geological data obtained in advance; the formation models are classified and grouped according to a formation database. Classifying and grouping the rock stratum models according to the rock stratum database, displaying the rock stratum models in layers according to different colors, and selecting cutterhead types of each layer according to the rock stratum database.
More specifically, the health detection module is also used for risk assessment. The risk assessment content includes:
1. whether the abrasion loss of the cutter head reaches a threshold value or not, if so, reminding of replacing the hob;
judging the abrasion loss of the insert hob in reaming operation according to the data of the abrasion monitor, monitoring whether the insert hob is suitable for continuous operation or not on line, if the monitoring result shows that the abrasion loss reaches a safety limit, replacing the hob in time, and according to the cutter changing requirement, ensuring that the maximum abrasion loss of the front hob is not more than 20mm.
2. Predicting cutter disc abrasion loss according to current cutter disc state data and stratum geological data, judging whether the actual abrasion loss accords with the predicted abrasion loss, and if not, carrying out early warning;
the method for calculating the predicted wear amount is as follows:
wherein: l is the running distance of reaming; k (k) s Is the abrasion coefficient of the abrasive particles; sigma (sigma) c Is the compressive strength of the rock; d (D) 0 The diameter of the hob is; s is the distance between hob; t is the width of the hob cutting edge; r is R i The radius is set for the hob; h is penetration; sigma (sigma) s Is the yield strength of the hob blade. Compressive strength sigma of rock c The hob related data is obtained in advance according to the cutter head configuration through a sensor while drilling; the running distance L of the reamer is obtained by the drill rod drilling distance.
3. And according to geological data of the current depth obtained in real time, comparing the geological data with a rock stratum database, judging whether the current cutter head and hob configuration meets the requirements, and if not, sending out a prompt.
In the large-diameter reaming working surface, a stepped assembly structure is formed by a top-down type drill bit body, cutter tooth shapes are staggered and continuously arranged, hobbing cutters with different strengths are installed among an edge cutter, a positive cutter and a center cutter according to geological conditions, and on-line evaluation of the cutterhead is carried out according to the geological information of rock and soil monitored in a while-drilling sensor, so that the cutterhead with which strength is used in a certain range for judging the rock strength and humidity, and further the maximization of rock breaking efficiency is achieved.
The risk assessment content may further include: and (5) fault identification. In the multistage driving device, a motor drives a hydraulic cylinder to operate, whether the motor or the hydraulic cylinder is in a normal working state is judged according to data information of a hydraulic valve, an oil pressure sensor, a rotating speed sensor and the like, if a certain motor has fault information, the fault information is timely reported to a central processing unit, and meanwhile, compensation working instructions are carried out on other motors, so that the normal operation of a system is ensured.
More specifically, the step of constructing a cutterhead twins includes:
step 1, establishing a physical model;
step 2, building a logic model according to the physical model built in the step 1;
and 3, establishing a cutter head twin body driven by the logic model.
Establishing a physical model: and establishing a three-dimensional visual physical model of the physical entity according to the mechanical structure, the running state, the actually measured influence factors, the geometric features and the actually measured and historical data in the cloud database of the physical entity.
Establishing a controllable logic model: and (3) building a model by the physical model built in the step (1) through a certain logic form, building a connection between each component factor of the logic model through modularization and connection logic, so as to formally illustrate the organization structure and the operation mechanism of the model, and simultaneously feeding back the behaviors of each factor to the physical model to optimize the physical model.
Establishing a cutterhead twin body: and constructing a visualized simulation model. According to the gray prediction method derived by the gray system theory, random variables are treated as gray quantities which change within a certain range and are related to time, disordered original data are converted into a generation sequence showing a certain rule, and the twin object, the twin structure and the twin process of a physical entity are realized.
Here, it is to be noted that the functions, algorithms, methods, and the like, to which the present invention relates, are merely conventional adaptive applications of the prior art. The present invention is therefore an improvement over the prior art in that the connection between hardware is essentially not a function, algorithm, method itself, i.e. the present invention, although it relates to a point of function, algorithm, method, does not include the improvement proposed by the function, algorithm, method itself. The description of the functions, algorithms and methods of the present invention is presented in terms of a better understanding of the present invention.
In the description of the present application, it should be understood that the terms "upper," "lower," "front," "rear," "left," "right," "horizontal," "inner," "outer," and the like indicate orientations or positional relationships, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements being referred to must have a particular orientation, be configured and operated in a particular orientation, and thus should not be construed as limiting the present invention.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. In the description of the present invention, the meaning of "plurality" is two or more unless specifically defined otherwise.
In the description of the present invention, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
In the description of the present specification, a particular feature, structure, material, or characteristic may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention, and are intended to be included within the scope of the appended claims and description.
Claims (9)
1. Intelligent monitoring system of anti-well drilling machine reaming blade disc based on digit twin, its characterized in that includes: a data acquisition module, a digital twin body and a health detection module,
the data acquisition module is used for acquiring the wear amount of the cutterhead;
the digital twin body comprises a visual cutterhead twin body;
the health detection module is used for updating the cutter disc twin body in real time according to the cutter disc abrasion loss so as to monitor the abrasion condition of the cutter disc;
the health detection module is also used for performing risk assessment, and the risk assessment content comprises:
s1, reminding of replacing a hob if the abrasion loss of the cutterhead reaches a threshold value;
judging the abrasion loss of the insert hob in reaming work according to the data of the abrasion monitor, monitoring whether the insert hob is suitable for continuous work or not on line, and if the monitoring result shows that the abrasion loss reaches a safety limit, replacing the hob in time, wherein the maximum abrasion loss of the hob on the front face is not more than 20mm;
s2, predicting cutter disc abrasion loss according to current cutter disc state data and stratum geological data, judging whether the actual abrasion loss accords with the predicted abrasion loss, and if not, carrying out early warning;
the method for calculating the predicted wear amount is as follows:
wherein: l is the running distance of reaming; k (k) s Is the abrasion coefficient of the abrasive particles; sigma (sigma) c Is the compressive strength of the rock; d (D) 0 The diameter of the hob is; s is the distance between hob; t is the width of the hob cutting edge; r is R i The radius is set for the hob; h is penetration; sigma (sigma) s Yield strength of the hob blade; compressive strength sigma of rock c The hob related data is obtained in advance according to the cutter head configuration through a sensor while drilling; the reaming running distance L is obtained through the drilling distance of the drill pipe;
s3, according to geological data of the current depth obtained in real time, comparing with a rock stratum database, judging whether the current cutter head and hob configuration meets the requirements, and if not, sending out a prompt.
2. The intelligent monitoring system of the reamer head of the inverted well drilling machine based on the digital twinning of claim 1, wherein the data acquisition module is further used for acquiring the weight on bit, the rotating speed and the torque of the reamer head, and the health detection module can carry out simulation analysis on the abrasion condition of the reamer head according to the weight on bit, the rotating speed and the torque, predict the abrasion speed of the reamer head, adjust the weight on bit, the rotating speed and the torque of the reamer head in real time and reduce the actual abrasion speed of the reamer head.
3. The intelligent monitoring system of a digital twinning-based counter bore machine reamer head of claim 1, wherein the digital twinning body further comprises a visual formation twinning body.
4. The intelligent monitoring system of a reamer head of a twin-back drilling machine of claim 3, wherein the data acquisition module is further configured to acquire a position parameter of the cutter head and update a position of a twin body of the cutter head in the formation twin body.
5. The intelligent monitoring system of a reamer head of a well reversing drilling machine based on digital twinning of claim 4, wherein the data acquisition module is further configured to obtain geological data of a current depth and update a formation twinning body of a corresponding depth.
6. The intelligent monitoring system of a reamer head of a twin-well drilling rig of claim 3, wherein the geological data required for constructing the formation twin is obtained by:
and installing a while-drilling sensor on the pilot hole drill bit, and synchronously obtaining geological data of continuous depth during pilot hole.
7. The intelligent monitoring system of a reamer head of a twin-well drilling machine of claim 6, further comprising a formation database, the formation database classifying formations by geologic data, each type of formation corresponding to an applicable cutterhead.
8. The intelligent monitoring system of a reamer head of a twin-screw based drilling rig of claim 7, wherein the formation database further groups each type of formation according to geological data, each group of formations corresponding to a set of applicable hob configurations.
9. The intelligent monitoring system of a digital twinning-based blow-by drilling machine reamer head of claim 8, wherein the step of constructing the formation twins comprises:
a formation model is constructed from pre-obtained geological data,
classifying and grouping the formation models according to the formation database.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110823235.0A CN113586028B (en) | 2021-07-21 | 2021-07-21 | Intelligent monitoring system of counter bore cutter head of anti-well drilling machine based on digital twin |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110823235.0A CN113586028B (en) | 2021-07-21 | 2021-07-21 | Intelligent monitoring system of counter bore cutter head of anti-well drilling machine based on digital twin |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113586028A CN113586028A (en) | 2021-11-02 |
| CN113586028B true CN113586028B (en) | 2024-03-29 |
Family
ID=78248680
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110823235.0A Active CN113586028B (en) | 2021-07-21 | 2021-07-21 | Intelligent monitoring system of counter bore cutter head of anti-well drilling machine based on digital twin |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113586028B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113858146B (en) * | 2021-12-02 | 2022-05-13 | 徐州安普瑞特能源科技有限公司 | Workbench device |
| CN114491960B (en) * | 2021-12-29 | 2023-12-01 | 徐州圣邦机械有限公司 | Wear monitoring method for high-pressure internal gear pump |
| CN114897007B (en) * | 2022-04-26 | 2024-04-19 | 太原理工大学 | Drilling machine health condition assessment method of composite information hierarchical convolutional neural network |
| CN116662849B (en) * | 2023-04-21 | 2024-04-09 | 西南石油大学 | Intelligent stuck drill type identification method based on digital twinning and knowledge graph |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AU6359401A (en) * | 2000-08-28 | 2002-03-07 | Halliburton Energy Services, Inc. | Method and system for predicting performance of a drilling system of a given formation |
| US6386297B1 (en) * | 1999-02-24 | 2002-05-14 | Baker Hughes Incorporated | Method and apparatus for determining potential abrasivity in a wellbore |
| JP2005036388A (en) * | 2003-05-20 | 2005-02-10 | National Institute Of Advanced Industrial & Technology | Method for evaluating rock strength and abrasion state of bit in real time |
| WO2014066981A1 (en) * | 2012-10-31 | 2014-05-08 | Resource Energy Solutions Inc. | Methods and systems for improved drilling operations using real-time and historical drilling data |
| CN106570275A (en) * | 2016-11-07 | 2017-04-19 | 沈阳工业大学 | Method based on CAI value for predicting abrasion of TBM hobbing cutter |
| JP2018086712A (en) * | 2016-11-30 | 2018-06-07 | 株式会社日立製作所 | Tool wear prediction device and method therefor |
| CN108256168A (en) * | 2017-12-26 | 2018-07-06 | 上海交通大学 | A kind of compound stratum shield hob abrasion amount determines method |
| CN108710732A (en) * | 2018-05-02 | 2018-10-26 | 华中科技大学 | A kind of visualization assessment of shield cutter service phase abrasion and prediction technique |
| CN109307493A (en) * | 2018-09-12 | 2019-02-05 | 天津大学 | The real-time detection method of the normal section disk cutter wear condition of hard rock tunnel development machine |
| WO2019063024A1 (en) * | 2017-09-30 | 2019-04-04 | 中铁工程装备集团有限公司 | Smart decision making method and system for boring control parameters of hard rock tbm |
| CN110895640A (en) * | 2018-08-22 | 2020-03-20 | 苏州安能捷工具有限公司 | Well drilling simulation method based on well wall-drill column-drilling tool-drill bit-rock system |
| CN110900307A (en) * | 2019-11-22 | 2020-03-24 | 北京航空航天大学 | Numerical control machine tool cutter monitoring system driven by digital twin |
| CN111126735A (en) * | 2018-11-01 | 2020-05-08 | 中国石油化工股份有限公司 | Drilling digital twin system |
| CN210483736U (en) * | 2019-05-09 | 2020-05-08 | 中国电建集团铁路建设有限公司 | Real-time monitoring system for shield cutter abrasion |
| CN112651148A (en) * | 2020-10-10 | 2021-04-13 | 哈尔滨理工大学 | Three-dimensional visual cutter design system and method with optimization function |
| CN113128028A (en) * | 2021-03-25 | 2021-07-16 | 中国科学院武汉岩土力学研究所 | Digital twin model construction method of geotechnical structure coupling system |
| CN113126564A (en) * | 2021-04-23 | 2021-07-16 | 重庆大学 | Digital twin driven numerical control milling cutter abrasion on-line monitoring method |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7032689B2 (en) * | 1996-03-25 | 2006-04-25 | Halliburton Energy Services, Inc. | Method and system for predicting performance of a drilling system of a given formation |
| WO2018236373A1 (en) * | 2017-06-21 | 2018-12-27 | Halliburton Energy Services, Inc. | Prediction of cutting size and shape generated by a drill bit |
| WO2019068179A1 (en) * | 2017-10-02 | 2019-04-11 | The Royal Institution For The Advancement Of Learning/Mcgill University | Bit condition monitoring system and method |
| US11066917B2 (en) * | 2018-05-10 | 2021-07-20 | Baker Hughes Holdings Llc | Earth-boring tool rate of penetration and wear prediction system and related methods |
| US11675325B2 (en) * | 2019-04-04 | 2023-06-13 | Schlumberger Technology Corporation | Cutter/rock interaction modeling |
-
2021
- 2021-07-21 CN CN202110823235.0A patent/CN113586028B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6386297B1 (en) * | 1999-02-24 | 2002-05-14 | Baker Hughes Incorporated | Method and apparatus for determining potential abrasivity in a wellbore |
| AU6359401A (en) * | 2000-08-28 | 2002-03-07 | Halliburton Energy Services, Inc. | Method and system for predicting performance of a drilling system of a given formation |
| JP2005036388A (en) * | 2003-05-20 | 2005-02-10 | National Institute Of Advanced Industrial & Technology | Method for evaluating rock strength and abrasion state of bit in real time |
| WO2014066981A1 (en) * | 2012-10-31 | 2014-05-08 | Resource Energy Solutions Inc. | Methods and systems for improved drilling operations using real-time and historical drilling data |
| CN106570275A (en) * | 2016-11-07 | 2017-04-19 | 沈阳工业大学 | Method based on CAI value for predicting abrasion of TBM hobbing cutter |
| JP2018086712A (en) * | 2016-11-30 | 2018-06-07 | 株式会社日立製作所 | Tool wear prediction device and method therefor |
| WO2019063024A1 (en) * | 2017-09-30 | 2019-04-04 | 中铁工程装备集团有限公司 | Smart decision making method and system for boring control parameters of hard rock tbm |
| CN108256168A (en) * | 2017-12-26 | 2018-07-06 | 上海交通大学 | A kind of compound stratum shield hob abrasion amount determines method |
| CN108710732A (en) * | 2018-05-02 | 2018-10-26 | 华中科技大学 | A kind of visualization assessment of shield cutter service phase abrasion and prediction technique |
| CN110895640A (en) * | 2018-08-22 | 2020-03-20 | 苏州安能捷工具有限公司 | Well drilling simulation method based on well wall-drill column-drilling tool-drill bit-rock system |
| CN109307493A (en) * | 2018-09-12 | 2019-02-05 | 天津大学 | The real-time detection method of the normal section disk cutter wear condition of hard rock tunnel development machine |
| CN111126735A (en) * | 2018-11-01 | 2020-05-08 | 中国石油化工股份有限公司 | Drilling digital twin system |
| CN210483736U (en) * | 2019-05-09 | 2020-05-08 | 中国电建集团铁路建设有限公司 | Real-time monitoring system for shield cutter abrasion |
| CN110900307A (en) * | 2019-11-22 | 2020-03-24 | 北京航空航天大学 | Numerical control machine tool cutter monitoring system driven by digital twin |
| CN112651148A (en) * | 2020-10-10 | 2021-04-13 | 哈尔滨理工大学 | Three-dimensional visual cutter design system and method with optimization function |
| CN113128028A (en) * | 2021-03-25 | 2021-07-16 | 中国科学院武汉岩土力学研究所 | Digital twin model construction method of geotechnical structure coupling system |
| CN113126564A (en) * | 2021-04-23 | 2021-07-16 | 重庆大学 | Digital twin driven numerical control milling cutter abrasion on-line monitoring method |
Non-Patent Citations (6)
| Title |
|---|
| "复合式盾构机刀盘刀具的设计及选型分析";周骏，等;《公路》;第59卷(第6期);全文 * |
| "数字孪生技术研究";袁野，曹伟;《2021（第九届）中国水利信息化技术论坛论文集》;全文 * |
| "移动式上向反井钻机主机装配工艺";管凤花，陈云;《建井技术》;第39卷(第5期);全文 * |
| TBM滚刀磨损实时监测系统的研发;章勤飞;《中国优秀硕士论文全文库工程科技II辑》(第6期);全文 * |
| Yang Xie."Digital twin for cutting tool: Modeling, application and service strategy".《Journal of Manufacturing Systems》.2020,305-312. * |
| 复合式盾构机刀具数值模拟及布置方式研究;杨振波;《中国优秀硕士论文全文库工程科技II辑》(第4期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113586028A (en) | 2021-11-02 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113586028B (en) | Intelligent monitoring system of counter bore cutter head of anti-well drilling machine based on digital twin | |
| CN104806226B (en) | intelligent drilling expert system | |
| CN108984817B (en) | Real-time TBM cutter abrasion loss evaluation method | |
| Li et al. | Application and outlook of information and intelligence technology for safe and efficient TBM construction | |
| CN109883470A (en) | Cutter head of shield machine condition monitoring system and method | |
| CN103184887B (en) | Method for underground tunnel drilling construction and geological information inversing | |
| CN112182973B (en) | TBM (Tunnel boring machine) operation parameter optimization method considering cutter vibration and rock slag geometric information | |
| CN112262251B (en) | Shield machine and method for driving tunnel | |
| CN111878055B (en) | Control system and control method for drilling speed of drill bit | |
| CN103975125A (en) | Method for detecting and mitigating drilling inefficiencies | |
| CN104863604A (en) | Method for real-time estimation of tool abrasion condition of cutter head tunneling system of hard rock tunnel boring machine | |
| CN115081324A (en) | Performance prediction optimization and fault diagnosis system and method for underground engineering equipment | |
| CN114219211A (en) | Rock burst risk assessment method based on theory and data-driven fusion | |
| AU2021201406A1 (en) | Drill pipe segment life monitor | |
| US11448068B2 (en) | Optimization of boring by a tunnel boring machine as a function of ground/machine interactions | |
| CN116205064A (en) | Prediction method for abrasion loss of shield cutter in service period in complex stratum tunnel construction | |
| CN110671095B (en) | Intelligent while-drilling soft measurement method for formation pressure | |
| CN113505911B (en) | Cutter life prediction system based on automatic cruise and prediction method thereof | |
| Lin et al. | A novel domain adversarial time-varying conditions intervened neural network for drill bit wear monitoring of the jumbo drill under variable working conditions | |
| CN104727815A (en) | Real-time well drilling formation correction method and device | |
| CN203145832U (en) | Deviation prevention control system for rock drilling tool | |
| CN110806859A (en) | Modular drilling data monitoring and design system based on machine learning | |
| CN115774912A (en) | Mechanism and data combined driving TBM hob abrasion prediction method | |
| CN113158562B (en) | TBM rock machine mapping construction method and system based on physical constraint and data mining | |
| CN114483043A (en) | Detection control system for tunneling and detection method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Country or region after: China Address after: 030000 Yingze West Street, Taiyuan, Taiyuan, Shanxi Applicant after: Taiyuan University of Technology Applicant after: NINGXIA TIANDI BENNIU INDUSTRIAL GROUP Co.,Ltd. Applicant after: TAIYUAN University OF SCIENCE AND TECHNOLOGY Address before: 753000 No.1 Jingong Road, Dawukou District, Shizuishan City, Ningxia Hui Autonomous Region Applicant before: NINGXIA TIANDI BENNIU INDUSTRIAL GROUP Co.,Ltd. Country or region before: China Applicant before: Taiyuan University of Technology Applicant before: TAIYUAN University OF SCIENCE AND TECHNOLOGY |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |