CN110259433B - Digital monitoring method for solid drilling machine - Google Patents
Digital monitoring method for solid drilling machine Download PDFInfo
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- CN110259433B CN110259433B CN201910574682.XA CN201910574682A CN110259433B CN 110259433 B CN110259433 B CN 110259433B CN 201910574682 A CN201910574682 A CN 201910574682A CN 110259433 B CN110259433 B CN 110259433B
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- 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
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- 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
- E21B47/00—Survey of boreholes or wells
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a digital monitoring system of an entity drilling machine, which can be divided into 6 main units: the system comprises a field equipment monitoring unit, a field environment monitoring unit, a mathematical model, a real-time operation unit, a client and a storage unit. The real-time operation unit is used for logical calculation of the data and can directly output the calculation result of the simulation model, early warning exceeding a limit value, report printing, recommended operation and other clients for operators and technical service personnel to check the monitoring state of the system; the storage unit is used for archiving historical data, and can be located at a local server, a remote server or a cloud end.
Description
Technical Field
The invention belongs to the technical field of oil drilling equipment control, and relates to a digital monitoring method for an entity drilling machine.
Background
An oil rig belongs to continuous operation type mechanical equipment, and once drilling is started, the oil rig is not allowed to stop before drilling is finished. And a plurality of wearing parts in the mechanical system must be replaced regularly, otherwise unexpected shutdown can be caused by component failure, and huge economic loss can be caused in serious cases. At present, two methods for estimating the service life of a key loss part are provided: calculating running time and empirical judgment. Such as: the cylinder sleeve of the drilling pump generally adopts the running time to determine the replacement period; the winch brake block, the bearing and the like are judged whether to be replaced or not by depending on the experience of operators. The two methods are still lack of scientificity and accuracy although they are used until now. Because the effective service life of the part can be influenced by different equipment operating environments, load working condition changes, the defect of the part, and the like, the deviation is judged to be large only through time, unnecessary waste can be caused by early replacement, and economic loss or safety accidents can occur when the replacement is not in time. In addition, the accuracy of the judgment according to the experience is limited by the subjective consciousness of people, and the uncertainty factor is more, so that the misjudgment is easy to occur.
The two non-scientific methods are not beneficial to organizing large-scale and standardized production, and the equipment production party and the equipment use party cannot reasonably prepare accessories; timely maintenance of equipment is not facilitated; meanwhile, accurate operation data of the equipment is difficult to obtain, and an equipment problem improvement scheme cannot be effectively provided.
In summary, the two existing component life cycle estimation methods have great defects, and a scientific and reasonable problem solution is not available.
Disclosure of Invention
The invention aims to provide a digital monitoring method for an entity drilling machine, which solves the problem that the service life of a wearing part cannot be accurately judged in the prior art, realizes scientific calculation of the residual service life of running parts of equipment, avoids unplanned shutdown of the equipment, improves the accuracy of replacement time of the wearing part, and is beneficial to accurately and efficiently reserving accessories by a production party and a using party.
The invention adopts the technical scheme that a digital monitoring method for an entity drilling machine comprises the following specific steps:
and 3, observing the field equipment, setting parameters and carrying out early warning analysis by using the real-time state data of the field equipment obtained in the step 2.
The invention is also characterized in that:
the data acquisition system in the step 1 comprises a field device monitoring unit and a field environment monitoring unit, wherein the field device monitoring unit and the field environment monitoring unit are respectively connected with the input end of the operation unit;
wherein the internal input of real-time arithmetic unit has digital model, and digital model includes: the system comprises a solid drilling machine digital model, a structural member strength calculation model, a material fatigue calculation model, an environmental factor calculation model, a dynamics calculation model, a vibration-structure calculation model, a temperature-structure calculation model, a noise-structure calculation model, a mechanical simulation model and an expert data model;
the solid drilling machine digital model is a data model obtained by digitizing the physical components of the whole drilling machine;
the structural part strength calculation model is used for calculating the strength change of the monitored structural part in real time and generating a characteristic curve;
the material fatigue calculation model is used for calculating the fatigue property of a drill wear part, and then the residual service life of the structural part is predicted by combining the result of the structural part strength calculation model;
the environment factor calculation model archives the field environment data by reading the data in the field environment detection unit;
the dynamic calculation model is used for calculating the dynamic characteristics of the moving part of the drilling machine and predicting the residual service life of the part according to the load characteristic change;
the vibration-structure calculation model, the temperature-structure calculation model and the noise-structure calculation model are used for calculating the loss condition of the drilling machine structural part predicted by the changes of vibration, temperature and noise;
the mechanical simulation model comprises the material characteristics, the structural characteristics and the operating characteristics of all monitored components, and the residual service life of related drilling machine components is predicted by adopting a mechanical operation method;
the expert data model is data of the existing working parameters, the service life of key parts of the drilling machine and the characteristics of environmental change;
the on-site environment monitoring unit comprises an environment data acquisition unit which is respectively connected with a temperature sensor TSQ, a humidity sensor HSQ, an air pressure sensor PSQ and an air speed sensor WSQ;
the field device monitoring unit is a plurality of sensors of different types mounted on the device body, the field device monitoring unit is also connected with a field data acquisition unit, and the field data acquisition unit calculates the acquired device body parameters through filtering or digital sampling and then transmits the parameters to the real-time operation unit through a bus communication mode;
the output end of the real-time operation unit is also connected with a client and a storage unit, the client is used for observing field equipment, setting parameters and carrying out early warning analysis, and the storage unit is used for backing up real-time state data of the field equipment processed by the real-time operation unit;
the specific calculation in the real-time operation unit comprises the following steps: the implementation arithmetic unit includes a calculation unit including: the system comprises an entity drilling machine system structure matrix, an entity drilling machine operation parameter table, a field environment parameter table, a component physical characteristic table and an operation and operation historical data table;
the solid drilling machine system structure matrix is a digital display of a non-moving structural member of the drilling machine by combining a geological structure of a drilling machine operation place;
the values in the entity drilling machine operation parameter table are data fed back by the field equipment monitoring unit;
the values in the physical drilling machine operation parameter table are actual operation parameters of the driller;
the values in the field environment parameter table are data fed back by the field environment monitoring unit;
the physical characteristic list of the part stores the operating characteristics of the monitored part in the drilling machine in a model in the form of a digital table, and is used for analyzing the actual loss condition of the part;
the data in the operation and operation historical data table is historical data in a memory unit called by a real-time operation unit and used for updating the digital model characteristic parameters in other parameter tables;
wherein the step 3 specifically comprises: the client is also connected with a process data cache, the client acquires the calculation result of the operation unit in real time through the process data cache to obtain the data of the actual use condition of the drilling machine and the estimated remaining life data, then the drilling machine is adjusted, and the process data cache also sends all the data to the storage unit;
the invention has the advantages that
The digital monitoring method of the solid drilling machine, which is adopted by the invention, aims at key components which can be directly measured by a sensor, and can monitor the loss condition in real time and accurately predict the service life; for the component directly measured by the unavailable sensor, the loss condition and the residual service life are indirectly calculated through a digital simulation model; all modules of the system can be connected through remote wired or wireless communication, and data can be remotely managed on a cloud platform; the mathematical model and the arithmetic unit are mutually independent and can be stored in a local or remote place, and a hardware platform architecture can be flexibly established; a human-computer interface of the client directly displays a simulation calculation result, and the method is efficient and visual; the expert database system assists in operation, and accuracy of simulation calculation is further improved.
Drawings
FIG. 1 is a schematic diagram of a digital monitoring method for a solid-state drilling rig according to the present invention;
FIG. 2 is a schematic diagram of a field device monitoring unit in a method for digital monitoring of a solid state drilling rig in accordance with the present invention;
FIG. 3 is a schematic diagram of a site environment monitoring unit in a method for digitally monitoring a solid state drilling rig in accordance with the present invention;
FIG. 4 is a schematic diagram of a digital model in a method for digitally monitoring a solid state drilling rig in accordance with the present invention;
FIG. 5 is a schematic diagram of a real-time computing unit in the digital monitoring method of a solid-state drilling machine according to the present invention;
FIG. 6 is a diagram of a client side scenario in a method for digital monitoring of a physical drilling rig in accordance with the present invention;
fig. 7 is a schematic diagram of a memory cell in a digital monitoring method for a solid-state drilling rig according to the present invention.
In the figure, 1, a field device monitoring unit, 2, a field environment monitoring unit, 3, a digital model, 4, a real-time operation unit, 5, a client, 6, a storage unit, 7, a field level data acquisition unit, 8, an environment data acquisition unit, 9, a solid drilling machine digital model, 10, a structural member strength calculation model, 11, a material fatigue calculation model, 12, an environment factor calculation model, 13, a dynamic calculation model, 14, a vibration-structure calculation model, 15, a temperature-structure calculation model, 16, a noise-structure calculation model, 17, a mechanical simulation model, 18, an expert data model, 19, a calculation unit, 20, a solid drilling machine system structure matrix, 21, a solid drilling machine operation parameter table, 22, a solid drilling machine operation parameter table, 23, a field environment parameter table, 24, a component physical characteristic list, 25, an operation and operation historical data table, 26, a process data cache, 27, an actual use condition, 28, a predicted residual life, 29, a network management module, 30, a local client, 31, a client, 32, a remote storage and a cloud storage.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
The invention provides a digital monitoring method for an entity drilling machine, which comprises the following specific steps:
the field equipment monitoring unit 1 and the field environment monitoring unit 2 should be as close to the working position of the monitored component as possible, so that the integrated transportation of the equipment, the centralized processing of collected signals and the avoidance of electromagnetic interference are facilitated;
as shown in fig. 2, SQ01, SQ02, ·, SQmn respectively represent different types of sensors installed in the monitored device body, the sensors of different types send real-time measurement data to the field level data acquisition unit 7, and the field level data acquisition unit 7 performs certain local operations, such as: filtering, digital sampling and the like, and sending effective sensor data to the real-time operation unit 4 in a bus communication mode;
aiming at the number of monitored components and the working positions of the components in the solid drilling machine, a plurality of field level data acquisition units can be adopted, and each data acquisition unit is connected with one or more sensors to classify and process the monitoring data; such as: the field data acquisition unit positioned on the slurry pump can acquire the vibration, noise, main shaft temperature rise, stroke, flow and the like of the slurry pump; the field data acquisition unit positioned on the winch can acquire the vibration, bearing temperature rise, motor rotating speed and the like of the winch;
each data acquisition unit has a specific data address, a sensor of each field level data acquisition unit also has a specific signal channel address, and when the field device monitoring unit 1 sends data to the real-time operation unit 4, the data format comprises two addresses (the field level data acquisition unit address and the sensor address) so as to facilitate subsequent calculation, filing, report printing and the like;
the solid drilling machine digital model 9 is a data model obtained by digitizing the physical components of the whole drilling machine, and the model also comprises the correlation among the components during the operation of the system, so that the digital model can maximally reflect the real operation condition and the interaction relation among the components;
the structural part strength calculation model 10 is used for calculating the strength change of the monitored structural part in real time and generating a characteristic curve, and the real-time operation unit 4 is used for calling the model or combining other data in the solid drilling machine digital model 9 and the calculation unit 19;
the material fatigue calculation model 11 is used for calculating the fatigue property of a drill wear part, and then predicting the residual service life of the structural part by combining the result of the structural part strength calculation model 10;
the environment factor calculation model 12 archives the field environment data by reading the data in the field environment detection unit 2;
the dynamic calculation model 13 is used for calculating the dynamic characteristics of the moving parts of the drilling machine, and predicting the residual service life of the parts according to the load characteristic change, such as: current wear condition of the winch drum bearing;
the vibration-structure calculation model 14, the temperature-structure calculation model 15 and the noise-structure calculation model 16 are used for calculating the loss condition of the drilling machine structural part predicted by the change of vibration, temperature and noise, and relevant data in the calculation unit 19 are also combined in actual operation;
the mechanical simulation model 17 comprises the material characteristics, the structural characteristics and the operating characteristics of all monitored parts, and the residual service life of related drilling machine parts is predicted by adopting a mechanical operation method in combination with the digital model 9 of the solid drilling machine and other data in the calculation unit 19;
the expert data model 18 is data of the existing working parameters, the service lives of the key parts of the drilling machine and the environmental change characteristics, and reasonable suggestions are given to the current work from the experience perspective by the data of the working parameters, the service lives of the key parts, the environmental change characteristics and the like summarized by the long-time work of the former. Such as: in a certain operation block, the average working life of the mud pump cylinder sleeve is 80 hours, the service life of the drill bit is 55 hours when the well depth is 1000-1500 m, and the like;
the real-time operation unit 4 is communicated with other units through a bus, and can be in a wired or wireless mode; the real-time operation unit 4 can be installed in a device working place, a remote office or a cloud server; if the system is installed in the equipment working place and the far-end office and has certain computing capability, only computing software needs to be planned if the system is installed in a cloud server, and the cloud server is responsible for software operation;
as shown in fig. 5, the internal schematic diagram of the real-time arithmetic unit 4 is shown. The calculating unit 19 is called by the real-time calculating unit 4 as required to calculate the process data. The data of the sensor to which each component belongs in the calculation process has a specific number, and the number of the data passing through the calculation unit 4 is not changed at all, so that subsequent classification and filing are facilitated. The involved calculations include: the system structure matrix 20 of the entity drilling machine, the operation parameter table 21 of the entity drilling machine, the operation parameter table 22 of the entity drilling machine, the parameter table 23 of the field environment, the physical characteristic list 24 of the part, and the operation and operation historical data table 25.
The solid body drilling system structural matrix 20 is a digital representation of the non-mobile structural members (e.g., substructure, derrick, etc.) of the drilling rig in connection with the geological structure of the site in which the drilling rig is operating. The matrix reflects the integral structural strength, toughness and the like of the drilling machine, and the superiority and inferiority of the data of the matrix represent whether the bearing structural member can meet the rated load requirement, such as: whether the strength of the derrick can bear the reaction torque of top drive rotation, whether the strength of the base can bear the weight of a pipe column and the like.
The values in the physical drilling rig operational parameter table 21 are changed in real time, the contents of which are all from the field device monitoring unit 1. And the real-time operation unit 4 sends the data to the entity drilling machine operation parameter table 21 according to the specific address number and the position number for calling when other models are calculated.
The values in the physical drilling rig operating parameter table 22 are also changed in real time and are stored as driller operating parameters such as: winch speed, pump stroke, drill plate torque, etc. The real-time operation unit 4 sends the data to the entity drilling machine operation parameter table 22 according to the specific address number and the position number for calling when other models are calculated.
The values in the field environment parameter table 23 are changed in real time, the contents of the values all come from the field environment monitoring unit 2, and the real-time operation unit 4 sends the data to the field environment parameter table 23 according to the specific position numbers for calling when other models are calculated.
The part physical characteristic list 24 is a list of operating characteristics of monitored parts in the drilling machine stored in a model in the form of a digital table for analyzing actual wear of the parts. The parameters of the list will change continuously according to the current values of the physical drilling rig operational parameters table 21, the physical drilling rig operational parameters table 22, and the field environment parameters table 23. The numerical values of the three tables are combined with the mechanical simulation model 17, and the running loss and the predicted service life of a specific part can be calculated through the real-time operation unit 4.
The data in the operation and running history data table 25 is history data in the storage unit 6 called by the real-time arithmetic unit 4. This data is mainly used to update the digital model characteristic parameters in the other lists, namely: as the component wears, its operating characteristics may change, and if the characteristic parameter is a fixed value, a large operation error may be caused. The physical characteristics of the components can be adjusted according to real-time conditions by continuously updating the operational parameters, so that the digital model is adaptive to the characteristics of the physical object.
The current wear condition of the winch drum bearing is calculated through the dynamics calculation 14 according to data in the entity drilling machine system structure matrix 20, the entity drilling machine operation parameter table 21, the field environment parameter table 23, the physical component characteristic list 24 and the mechanics simulation model 17, the remaining service life under the future working condition is predicted by combining the entity drilling machine operation parameter table 22, the operation and operation historical data table 25 and the expert data model 18, if the data in the three tables do not participate in the calculation, the service life of the bearing can be predicted only according to the existing working condition load characteristic, the difference between the actual working condition and the actual working condition is large, therefore, the service life prediction accuracy can be effectively improved by combining the recorded real predicted future working condition parameters.
When the drilling machine completes one well in the area, the operation and running historical data table 25 in the digital monitoring system can count the loss condition of the monitored part in the operation period, so that the cost can be calculated, the operation period can be estimated, accessories can be prepared and the like by other equipment in the same area conveniently.
Aiming at key components, the loss condition and the residual service life of the key components are reasonably judged by combining the calculation. The results of the calculation unit 19 will be stored in the process data cache 26, and the process data cache 26 will store each calculation result in a regular sequence, which is classified into two types: actual usage 27 and estimated remaining life 28, while process data cache 26 also sends all data to storage unit 6 for archival of sensor measurement data, actual usage 27, and predicted remaining life 28.
The data in the actual usage 27 is sent to the mathematical model 3 for updating the computation constants, correction coefficients, characteristic parameters, and the like of the partial model. Such as: environmental data, operational parameters, etc.
And 3, observing the field equipment by using the real-time state data of the field equipment obtained in the step 2, setting parameters and carrying out early warning analysis: the client 5 obtains the calculation result of the implementation operation unit 4 in real time through process data cache to obtain data of the actual use condition of the drilling machine and estimate the residual life data, and then adjusts the drilling machine, as shown in fig. 6, the client 5 further comprises a network management module 29, a local client 30 and a remote client 31, the network management module 29 is connected to the real-time operation unit 4, the network management module 29 has various external connection modes, and can be a wired or wireless local area network, a metropolitan area network, a wide area network and the like, the local client is installed in a drilling machine operation place and used for on-site personnel to check the operation state of the drilling machine, and the remote client is connected with the network management module through a communication network and used for remote monitoring;
the actual usage 27 in the real-time operation unit 4 is used to display the operation status, the wear status, and the like of the monitored components in the form of graphs and real-time data in the local client 30 and the remote client 31. When the data in the actual usage 27 deviates significantly from the standard data in the expert data model 18, alarm prompt messages are popped up in the local client 30 and the remote client 31, giving possible problems and consequences. The estimated remaining life 28 data is also displayed on the local client 30 and the remote client 31 in real time, and the clients have maintenance report information such as replacement of parts, maintenance downtime, estimated cost, downtime, etc. before the estimated life is reached. It is convenient for users or equipment suppliers to account cost, prepare fittings, coordinate logistics, arrange maintenance service personnel and the like.
As shown in fig. 7, the principle of the storage unit includes a local storage 32 and a cloud storage 33; the local storage 32 is used for storing process data or a small amount of historical data, the cloud storage 33 is used for archiving historical data, all data of the cloud storage 33 come from the local storage 32, and a data structure of the cloud storage 33 can be NoSQL (non-relational database), hadoop (distributed parallel processing framework), bigtable (distributed storage system) or the like.
After the cloud data access authority is obtained, any digital monitoring system can access data in the cloud storage 33 and download the data to the local storage 32, so that the working characteristic parameters and the expert database of the existing drilling machine in the area can be read when a new drilling machine works for the first time, and the equipment parameters can be optimized conveniently. Such as: the drilling machine A acquires the operation data of a certain operation block and stores the operation data in the cloud, the drilling machine B downloads the cloud data of the drilling machine A to the local before the drilling machine B enters the first operation of the block, set parameters can be generated quickly, and the system automatically calculates guidance information such as the loss condition, the number of required spare parts, the replacement frequency and the like of each key part. The B well team can report the material demand plan according to the report, so that the production cost can be saved, the production allocation period can be shortened, the safe operation of equipment can be ensured, and abnormal shutdown can be avoided.
The invention provides a digital monitoring system of an entity drilling machine based on the technologies of sensors, digital simulation calculation, distributed storage and the like, and realizes the online monitoring of the running condition of key wearing parts in the working process of the drilling machine; and (4) performing simulation calculation on the digital model, and accurately predicting the residual service life of the component which cannot be directly measured. The method has the advantages of scientifically predicting the system downtime, preparing accessories in advance and improving the working efficiency.
Claims (3)
1. A digital monitoring method for an entity drilling machine is characterized by comprising the following specific steps:
step 1, acquiring parameters of field equipment and data of a field environment by using a data acquisition system, wherein the data acquisition system comprises a field equipment monitoring unit (1) and a field environment monitoring unit (2), and the field equipment monitoring unit (1) and the field environment monitoring unit (2) are respectively connected with the input end of an operation unit in the step 2;
the on-site environment monitoring unit (2) comprises an environment data acquisition unit (8), and the environment data acquisition unit (8) is respectively connected with a temperature sensor TSQ, a humidity sensor HSQ, an air pressure sensor PSQ and an air speed sensor WSQ; the field device monitoring unit (1) is provided with a plurality of sensors of different types, the field device monitoring unit (1) is also connected with a field data acquisition unit (7), and the field data acquisition unit (7) calculates the acquired device body parameters through filtering or digital sampling and then transmits the parameters to the real-time calculation unit (4) through a bus communication mode;
step 2, processing the parameters of the field equipment and the data of the field environment acquired in the step 1 through an operation unit to obtain the real-time state data of the field equipment, wherein the operation unit comprises a real-time operation unit (4), a digital model (3) is input into the real-time operation unit (4), and the digital model (3) comprises: the system comprises a solid drilling machine digital model (9), a structural part strength calculation model (10), a material fatigue calculation model (11), an environmental factor calculation model (12), a dynamics calculation model (13), a vibration-structure calculation model (14), a temperature-structure calculation model (15), a noise-structure calculation model (16), a mechanical simulation model (17) and an expert data model (18);
the solid drilling machine digital model (9) is a data model obtained by digitizing the physical components of the whole drilling machine;
the structural part strength calculation model (10) is used for calculating the strength change of the monitored structural part in real time and generating a characteristic curve;
the material fatigue calculation model (11) is used for calculating the fatigue characteristic of a drill wear part, and then the residual service life of the structural part is predicted by combining the result of the structural part strength calculation model (10);
the environment factor calculation model (12) archives the field environment data by reading the data in the field environment detection unit (2);
the dynamic calculation model (13) is used for calculating the dynamic characteristics of the moving parts of the drilling machine and predicting the residual service life of the parts according to the load characteristic change;
the vibration-structure calculation model (14), the temperature-structure calculation model (15) and the noise-structure calculation model (16) are used for calculating and predicting the loss condition of the drilling machine structural part through the changes of vibration, temperature and noise;
the mechanical simulation model (17) comprises the material characteristics, the structural characteristics and the operating characteristics of all monitored components, and the residual service life of related drilling machine components is predicted by adopting a mechanical operation method;
the expert data model (18) is data of the existing working parameters, the service life of key parts of the drilling machine and the environmental change characteristics;
and 3, observing the field equipment, setting parameters and carrying out early warning analysis by using the real-time state data of the field equipment obtained in the step 2, specifically, obtaining a calculation result of the operation unit (4) in real time by using a process data cache (26), obtaining data (27) of the actual service condition of the drilling machine and estimated remaining life data (28), then adjusting the drilling machine, and sending all the data to a storage unit (6) by using the process data cache (26).
2. The digital monitoring method for the solid drilling machine according to claim 1, characterized in that the output end of the real-time arithmetic unit (4) is further connected with a client (5) and a storage unit (6), the client (5) is used for observing, setting parameters and performing early warning analysis on the field equipment, and the storage unit (6) is used for backing up real-time state data of the field equipment processed by the real-time arithmetic unit (4);
the specific calculation in the real-time arithmetic unit (4) comprises: the real-time arithmetic unit (4) comprises a calculation unit (19), said calculation unit (19) comprising: the system comprises a physical drilling machine system structure matrix (20), a physical drilling machine operation parameter table (21), a physical drilling machine operation parameter table (22), a field environment parameter table (23), a component physical characteristic list (24) and an operation and operation historical data table (25).
3. The digital monitoring method for the entity drilling machine according to claim 2,
the solid drilling machine system structure matrix (20) is used for digitally displaying a non-moving structure of a drilling machine by combining a geological structure of a drilling machine operation place;
the values in the physical drilling machine operation parameter table (21) are data fed back by the field equipment monitoring unit (1);
the values in the physical drilling rig operating parameter table (22) are actual operating parameters of the driller;
the value in the field environment parameter table (23) is data fed back by the field environment monitoring unit (2);
the component physical characteristic list (24) is used for storing the operating characteristics of the monitored component in the drilling machine in a model in a digital table form and analyzing the actual loss condition of the component;
the data in the operation and operation historical data table (25) is the historical data in the storage unit (6) called by the real-time arithmetic unit (4) and used for updating the digital model characteristic parameters in other parameter tables.
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| CN111723536B (en) * | 2020-06-16 | 2022-10-04 | 岭南师范学院 | Multi-body dynamics analysis method of gas extraction drilling machine system |
| CN112012695B (en) * | 2020-09-27 | 2023-07-18 | 中油国家油气钻井装备工程技术研究中心有限公司 | Petroleum drilling machine auxiliary guiding equipment based on edge calculation and guiding method thereof |
| CN112595537B (en) * | 2020-12-17 | 2023-03-21 | 弥伦工业产品设计(上海)有限公司 | Equipment health state monitoring method and system based on signal analysis and storage medium |
| CN114636438A (en) * | 2022-01-25 | 2022-06-17 | 四川宏华电气有限责任公司 | Drilling machine online monitoring system based on AR |
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