Digital twin enabled intelligent industrial centralized control method and system

Abstract

The application relates to a kind of digital twin-enabled intelligent industrial centralized control method and system, wherein the method comprises: in response to mode switching instruction, control intelligent driller cockpit to switch between operating mode and virtual mode;In the case of virtual mode, activate digital twin link, and disconnect remote control link, so that the remote control system PLC sends the multi-source data of the rig area equipment obtained to the digital twin server, so that the digital twin server implements cooperative virtual debugging containing mechanical behavior and electrical logic based on the deployed equipment digital model and electrical behavior model;In the case of operating mode, activate remote control link, and disconnect digital twin link, so that the remote control system PLC performs remote multi-modal operation on rig area equipment.The application builds two links of remote operation and virtual debugging through reconfigurable communication topology, which significantly improves the safety and debugging control efficiency of drilling operation under the flexible switching of the two modes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial control, and in particular to an intelligent industrial centralized control method and system empowered by digital twinning. BACKGROUND

[0002] Currently, there are multiple single automated devices on an oil drilling platform. These devices are usually from different manufacturers, and the control logic relies on each independent device. In order to avoid problems such as unreasonable device operation process, low operation efficiency, and complex operation, at least one PLC is used to interact with the PLCs of each single device according to an agreed interface protocol, and drilling devices (such as drawworks, rotary tables, mud pumps, top drives, etc.) and tubular handling devices (such as pipe racking machines, rig floor manipulators, iron roughnecks, elevators, etc.) are integrated together to achieve unified control, which is called a centralized control system. The centralized control system of the oil drilling and production industry is usually deployed in the driller's house located on the rig floor. The centralized control system can be controlled through the driller's seat with an operating handle, an industrial touch screen, and an emergency stop button. Before formal drilling, a large amount of time is required for debugging in the well site due to the large number of interfaced single devices, and some single devices need to be positionally calibrated according to the actual situation of the rig floor.

[0003] At the same time, in the prior art, the driller's operation interface is usually located in the rig floor area within a straight-line distance of less than ten meters from the operating device, which causes the driller to face direct safety risks when handling device lifting and lowering failures or sudden operation accidents. In addition, since the debugging of the integrated system involves the collaborative logic verification of multiple heterogeneous devices, if there are potential logic defects in the control program or the operation personnel are not adequately trained, abnormal displacement trajectories may overlap during device linkage, thereby causing device collision and other secondary accidents. Such technical defects significantly restrict the safety and operation reliability of drilling operations. SUMMARY

[0004] (I) Technical problems to be solved

[0005] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present application provides an intelligent industrial centralized control method and system empowered by digital twinning, which solves the technical problems of long debugging cycle caused by integration of multiple source heterogeneous devices, safety hazards of the driller's physical proximity to the high-risk operation area, and device collision risks caused by insufficient collaborative verification of control logic in the prior art.

[0006] (II) Technical solutions

[0007] In order to achieve the above-mentioned purposes, the main technical solutions adopted by the present application include:

[0008] In a first aspect, the embodiments of the present application provide a digital twin enabled intelligent industrial control method, applied to a digital twin enabled intelligent industrial control system, the intelligent industrial control system comprising a remote control system PLC and a digital twin server located in an intelligent driller cabin, a digital twin link being established between the remote control system PLC and the digital twin server, and a remote control link being established between the remote control system PLC and drilling platform area equipment, the method comprising:

[0009] In response to a mode switching instruction, the intelligent driller cabin is controlled to switch between an operation mode and a virtual mode;

[0010] In a case where the intelligent driller cabin enters the virtual mode, the digital twin link is activated, and the remote control link is disconnected, so that the remote control system PLC sends the acquired multi-source data of the drilling platform area equipment to the digital twin server, and the digital twin server implements collaborative virtual debugging containing mechanical behavior and electrical logic based on the deployed device digital model and electrical behavior model;

[0011] In a case where the intelligent driller cabin enters the operation mode, the remote control link is activated, and the digital twin link is disconnected, so that the remote control system PLC performs remote multi-modal operation on the drilling platform area equipment.

[0012] Optionally, the mode switching instruction comprises a first switching instruction and a second switching instruction, wherein,

[0013] The first switching instruction comprises at least one of the following: a virtual debugging instruction from a touch interface / operation handle connected to the remote control system PLC, a trigger signal of a virtual node representing a logical breakpoint of a kinematic link of a drilling device in a digital twin environment parsed based on a pre-calibrated drilling process topology graph, and a trigger signal of a first type of target drilling device confirmation point, the first type of target drilling device confirmation point being a verification node representing that a kinematic constraint of a drilling device in the drilling platform area equipment meets a standard in a virtual debugging environment;

[0014] The second switching instruction comprises at least one of the following: a device remote control instruction from the touch interface / operation handle, a trigger signal of a physical node representing a mechanical breakpoint of device linkage in an actual drilling operation parsed based on the drilling process topology graph, and a trigger signal of a second type of target drilling device confirmation point, the second type of target drilling device confirmation point being a verification node representing that a safety operation boundary condition of a drilling device in the drilling platform area equipment is established in a physical operation environment.

[0015] Optionally, the digital twin server implements collaborative virtual debugging containing mechanical behavior and electrical logic based on the deployed device digital model and electrical behavior model, comprising:

[0016] The obtained mechanical motion parameters and electrical control signals of the drilling floor area equipment are subjected to multi-layer heterogeneous data verification including equipment state self-checking, transmission link integrity checking and data logic threshold checking, and the verified data is output;

[0017] The sampling time of the verified data by the PLC hardware clock is aligned with the start time of the digital twin server simulation cycle, and based on the alignment result, an interpolation operation is performed to compensate for the timing deviation caused by network transmission jitter, generating a time-domain continuous data stream;

[0018] Based on the pre-deployed equipment digital model and electrical behavior model, the mechanical motion trajectory and electrical control timing are cooperatively virtually debugged according to the time-domain continuous data stream;

[0019] The cooperative virtual debugging includes dynamic position matching of the equipment motion trajectory and the equipment digital model, verification of the timing response of the received equipment operation signal in the electrical behavior model, and generation of visual correction suggestions when mechanical interference or electrical parameter exceeds the limit.

[0020] Optionally, based on the pre-deployed equipment digital model and electrical behavior model, the mechanical motion trajectory and electrical control timing are cooperatively virtually debugged according to the time-domain continuous data stream, including:

[0021] The pre-deployed equipment digital model in the digital twin server is called to perform kinematic calculation on the mechanical motion parameters in the data stream, generate point cloud data of the motion transmission components of the drilling equipment in the drilling floor area equipment, and map the point cloud data to the trajectory reference of the mechanical action;

[0022] The Hausdorff distance between the point cloud data of the motion transmission components and the preset reference trajectory template is calculated to generate a position matching deviation value;

[0023] In the electrical behavior model pre-deployed in the digital twin server, the electrical control signals in the data stream are loaded, the electrical logic state in the electrical control signals is analyzed and the electrical phase is marked, and the electrical event sequence with phase markers is obtained;

[0024] Based on the electrical event sequence, the phase relationship of the remote control system PLC control cycle is reconstructed by timestamp alignment and cycle division, and the signal transmission delay, valve response delay and mechanical inertia delay are coupled to construct a timing simulator;

[0025] Based on the output of the timing simulator, the independent contribution values of the signal transmission delay, valve response delay and mechanical inertia delay are analyzed;

[0026] According to the independent contribution values of the signal transmission delay, the valve body response delay and the mechanical inertia delay, the phase offset between the electrical control signal response delay and the starting time of the trajectory reference of the corresponding mechanical action is calculated by superimposing dynamic weights;

[0027] When the position matching deviation value exceeds the preset spatial threshold or the phase offset exceeds the preset timing tolerance range, a visual data including a three-dimensional space deviation heat map, an electrical phase offset curve and a stiffness correction parameter is generated, and a corresponding correction instruction is provided for the visual data and packaged as a virtual correction instruction package.

[0028] Optionally, a protocol conversion middleware is independently configured between the remote control system PLC and the digital twin server. In the activated state of the digital twin link, the protocol conversion middleware implements at least one of the following semantic consistency works:

[0029] A mapping relationship table between the remote control system PLC and the digital twin server is constructed and maintained;

[0030] A debugging instruction stream from the remote control system PLC is received, and a debugging instruction semantic is extracted, which is mapped to a simulation excitation signal based on the mapping relationship table. The timestamp of the simulation excitation signal is kept integer multiple synchronized with the PLC scanning period;

[0031] The virtual correction semantic of the virtual correction instruction package output by the digital twin server is parsed, and the correction semantic is converted to a physical debugging signal based on the mapping relationship table and the pre-defined PLC electrical coding rule;

[0032] When it is detected that the virtual correction semantic conflicts with the pre-set PLC hardware protocol constraint, the conflict instruction segment is located based on the mapping relationship table and a semantic isolation mark is applied, and a pre-stored PLC historical control instruction template is called to replace the instruction segment with the semantic isolation mark;

[0033] The bit alignment consistency of the protocol control word bit field of the remote control system PLC and the state variable of the digital twin server is verified bit by bit, the matching degree of the dimensionless parameter unit value of the simulation excitation signal and the linear transformation coefficient of the physical debugging signal range is verified, and the integer multiple synchronization of the timestamp of the simulation excitation signal and the PLC scanning period is verified;

[0034] If any of the above verifications fails, the semantic consistency deviation value is recorded according to the pre-set weight assignment rule according to the deviation type, and is updated to the log;

[0035] When the cumulative value of the semantic consistency deviation recorded in the log exceeds the pre-set threshold, a hybrid control instruction set is generated based on the pre-set fuzzy logic rule base, written to the pre-execution buffer queue of the remote control system PLC, and feedback to the remote control system PLC with an instruction reconstruction request.

[0036] Optionally, the remote control system PLC performs remote multi-modal operations on the drilling platform area equipment, including:

[0037] A video network server connected to the remote control system PLC and the camera in the drilling platform area equipment respectively generates drilling area video stream data by dynamically selecting a video decoding protocol and resolution scaling strategy according to the obtained camera deployment parameters and drilling scene features of the drilling area.

[0038] Real-time tracking of at least one of the drilling equipment motion trajectory, the drilling process preset node, and the trigger signal of the drilling equipment confirmation point, and constructing a dynamic layout topology of the video picture according to the drilling area video stream data.

[0039] Establishing a semantic interaction channel between the voice instruction set and the remote control system PLC control instruction to convert the voice instruction into an executable instruction of the remote control system PLC, or convert the state data fed back by the PLC into voice broadcast information.

[0040] In response to the voice instruction or the input instruction from the touch interface / operation handle connected to the remote control system PLC, the corresponding instruction is issued to the drilling platform area equipment and / or the cockpit smart home equipment through a pre-constructed communication protocol cluster, wherein the user voice instruction needs to be converted into an executable instruction of the remote control system PLC based on the semantic interaction channel before being issued, and the control instruction of the drilling platform area equipment has a higher channel priority than the control instruction of the cockpit smart home equipment.

[0041] Optionally, a video network server connected to the remote control system PLC and the camera in the drilling platform area equipment respectively generates drilling area video stream data by dynamically selecting a video decoding protocol and resolution scaling strategy according to the obtained camera deployment parameters and drilling scene features of the drilling area, including:

[0042] Obtaining the deployment parameters of the camera in the drilling area, including hardware constraint parameters and transmission constraint parameters;

[0043] Based on the obtained sensor data and equipment log of the drilling platform area equipment, identifying the drilling scene features including the operation mode parameters and the environmental interference parameters;

[0044] If the hardware constraint parameter exists a camera type supporting hardware acceleration and the network bandwidth in the transmission constraint parameter is lower than a preset bandwidth threshold, applying GPU hardware accelerated decoding to the pre-designated equipment area video stream, and using dynamic code rate for adaptive decoding to the non-pre-designated equipment area to obtain the decoded video stream;

[0045] If the environmental interference parameter meets the preset low-light condition, forcibly turning on the camera night vision mode, and using a histogram to equalize the decoded video stream;

[0046] The device motion trajectory density distribution heat map is obtained by optical flow analysis of the video stream after equalization processing, the peak region in the heat map is subjected to local cropping at original resolution, and the non-peak region in the heat map is subjected to edge-preserving down-sampling operation to obtain a differentially processed video stream.

[0047] When the job mode parameter is at the user-specified or preset destination process node stage, the differentially processed video stream corresponding to the camera associated with the destination process node is output at the highest resolution, and the video stream of the non-associated camera is uniformly down-sampled to the reference resolution for output.

[0048] Optionally, at least one of the information of real-time tracking of the drilling equipment motion trajectory, the drilling process preset node, and the trigger signal of the drilling equipment confirmation point is constructed into a dynamic layout topology of the video picture according to the drilling area video stream data, including:

[0049] A grid-based global monitoring mode is enabled in the video display module of the video network server.

[0050] When the trigger signal of the drilling process preset node and / or the equipment confirmation point is detected, the grid-based global monitoring mode is switched to a single-channel full-screen focus mode, the associated camera picture is displayed full screen in the main grid area, the non-associated picture is shrunk to the edge grid, and is marked as a semi-transparent picture display with a preset low frame rate;

[0051] When the device motion trajectory deviates from the preset path, the device tracking mode is activated, a tracking sub-picture is inserted in the grid-based global monitoring mode, and the device deviation vector is identified in real time;

[0052] In the single-channel full-screen focus mode and the device tracking picture-in-picture mode, at least one of the device pose deviation warning box, the operation guide arrow, and the voice broadcast is superimposed;

[0053] Among them,

[0054] The grid-based global monitoring mode is configured to divide the screen into N×M grids, N and M are both ≥3, the main grid area is the central grid, and the edge grid is distributed in a ring level for parallel monitoring of multiple camera video streams.

[0055] The single-channel full-screen focus mode is configured to expand the main grid area to full screen and hide or compress the edge grid area to a side floating bar.

[0056] The device tracking mode is configured to fixedly display a global picture in the main grid area and dynamically insert a tracking sub-window in the edge grid area for real-time tracking following the moving trajectory of the target device.

[0057] Optionally, a semantic interaction channel of the voice instruction set and the PLC control instruction of the remote control system is established to convert the voice instruction into an executable instruction of the PLC of the remote control system, or convert the state data fed back by the PLC into voice broadcast information, comprising:

[0058] A semantic interaction channel of the voice instruction set and the PLC control instruction of the remote control system is established by using a voice recognition module and a TTS engine of a video network server;

[0059] The received voice instruction is converted into a text command through the semantic interaction channel, and the text command is subjected to field adaptive noise reduction processing and drilling terminology keyword extraction;

[0060] The extracted drilling terminology keyword is subjected to fuzzy matching with a predefined device operation semantic tree, and when the matching is successful, a device type code and an operation action code bound to the matching result are generated;

[0061] The multi-parameters in the noise-reduced text command are subjected to timing alignment processing to generate a parameter value sequence bound to the operation action code;

[0062] Based on the device type code, the operation action code and the parameter value sequence, a control word containing a function code and a register address sequence is generated, and the control word is issued to the drilling floor area device and a response monitoring thread is simultaneously created;

[0063] When the response monitoring thread captures the device state signal fed back by the drilling device, the device state signal is analyzed, the analysis result is matched with a preset fault level dictionary to obtain a fault matching level;

[0064] By using the fault matching level, a TTS engine is called to generate voice broadcast content with different emotional tones and play the voice broadcast content.

[0065] In a second aspect, the embodiment of the present application provides a digital twin enabled intelligent drilling industrial centralized control system, comprising: drilling floor area devices including drilling devices, drilling floor area PLCs, cameras and switches; an intelligent driller cabin, the intelligent driller cabin applies the method as described above, and the intelligent driller cabin comprises: a remote control system PLC, a digital twin server, a video network server, a display screen and a switch;

[0066] The remote control system PLC is connected with the drilling equipment and the drilling platform area PLC respectively through a switch, the remote control system PLC and the drilling platform area PLC are externally connected with a touch screen and / or an operating handle, the digital twin server is connected with the remote control system PLC and a display screen respectively, a video network server is connected with the remote control system PLC and a drilling platform area camera respectively through the switch, the remote control system PLC, the digital twin server and the display screen form a digital twin link, the remote control system PLC forms an equipment remote control link with the drilling equipment and the drilling platform area PLC by using the switch, the remote control system PLC forms a video monitoring link with the camera by using the switch and the video network server, and the equipment remote control link and the video monitoring link jointly constitute a remote control link.

[0067] (Three) beneficial effects

[0068] The beneficial effects of the present application are: the present application constructs two links of remote operation and virtual debugging through a reconfigurable communication topology, which significantly improves the safety and debugging control efficiency of drilling operations. In the virtual mode, based on the real-time synchronization and simulation modeling capability of the digital twin link to the multi-source data of the equipment, the isomorphic digital twin server performs collaborative virtual debugging of mechanical behavior and electrical logic, and personnel operation training can also be completed, without starting the real equipment throughout, thereby avoiding safety accidents caused by physical equipment misoperation or debugging logic conflict. In the operation mode, by activating the remote control link and integrating video adaptive analysis, natural language interaction and multi-protocol cluster control functions, the monitoring picture of the focused equipment or process node can be generated remotely, and the voice instruction can be converted into accurate control signals in real time, so that the operation personnel can complete the equipment start-stop, speed regulation and positioning control without approaching the high-risk area of the drilling platform, thereby essentially eliminating the possibility of personnel exposure to the risk of downhole operation.

[0069] Further, the seamless switching mechanism of the two modes solves the problem of long debugging cycle caused by the integration of multi-source heterogeneous equipment: the virtual debugging stage can directly verify the coordination of control logic and equipment behavior, avoiding the risk of equipment collision caused by protocol adaptation or logic conflict, greatly shortening the field debugging cycle; and in the remote operation stage, through the unified scheduling of video, voice and multi-protocol signals by the multi-modal fusion control link, the dependence on artificial inspection and manual operation is further reduced, realizing the reduction of staff and the increase of efficiency. In addition, the deep embedding of digital twin and artificial intelligence technology not only improves the decision-making autonomy of the local control system, but also provides a compatibility basis for subsequent extension of data to the cloud and remote collaborative operation, promoting the upgrading of traditional drilling control to intelligent and service-oriented. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 The system hardware architecture schematic diagram provided for the embodiments of the present application;

[0071] Figure 2A flowchart of the method provided by the embodiment of the present application is shown in the figure;

[0072] Figure 3 A schematic diagram of the digital twin link of the method provided by the embodiment of the present application is shown in the figure;

[0073] Figure 4 A specific flowchart of step S2 of the method provided by the embodiment of the present application is shown in the figure;

[0074] Figure 5 A specific flowchart of step S23 of the method provided by the embodiment of the present application is shown in the figure;

[0075] Figure 6 A schematic diagram of the remote control link of the method provided by the embodiment of the present application is shown in the figure;

[0076] Figure 7 A specific flowchart of step S3 of the method provided by the embodiment of the present application is shown in the figure;

[0077] Figure 8 A specific flowchart of step S31 of the method provided by the embodiment of the present application is shown in the figure;

[0078] Figure 9 A specific flowchart of step S32 of the method provided by the embodiment of the present application is shown in the figure;

[0079] Figure 10 A specific flowchart of step S33 of the method provided by the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0080] In order to better explain the present application, so as to be understood, the present application is described in detail by specific embodiments, combined with the accompanying drawings.

[0081] As Figure 1 and Figure 2As shown, the digital twin enabled intelligent drilling industry centralized control method proposed by the embodiment of the application is applied to a digital twin enabled intelligent industry centralized control system, the intelligent industry centralized control system includes a remote control system PLC and a digital twin server located in an intelligent driller cabin, a digital twin link is established between the remote control system PLC and the digital twin server, and a remote control link is established between the remote control system PLC and the drilling platform area equipment, and the method comprises the following steps: in response to a mode switching instruction, the intelligent driller cabin is controlled to switch between an operation mode and a virtual mode; in the case that the intelligent driller cabin enters the virtual mode, the digital twin link is activated, and the remote control link is disconnected, so that the remote control system PLC sends the obtained multi-source data of the drilling platform area equipment to the digital twin server, and the digital twin server performs collaborative virtual debugging of mechanical behavior and electrical logic based on the deployed equipment digital model and electrical behavior model; in the case that the intelligent driller cabin enters the operation mode, the remote control link is activated, and the digital twin link is disconnected, so that the remote control system PLC performs remote multi-modal operation on the drilling platform area equipment.

[0082] The application constructs two links of remote operation and virtual debugging through a reconfigurable communication topology, significantly improves the safety and collaborative control efficiency of drilling operations. In the virtual mode, based on the real-time synchronization and simulation modeling capability of the digital twin link for equipment multi-source data, the isomorphic digital twin server performs collaborative virtual debugging of mechanical behavior and electrical logic, and personnel operation training can also be completed, without starting the real equipment throughout, thereby avoiding safety accidents caused by physical equipment misoperation or debugging logic conflict. In the operation mode, by activating the remote control link and integrating video adaptive analysis, natural language interaction and multi-protocol cluster control functions, the monitoring picture of the focused equipment or process node can be remotely generated, and the voice instruction can be converted into accurate control signals in real time, so that the operation personnel can complete the equipment start-stop, speed regulation and positioning control without approaching the high-risk area of the drilling platform, thereby essentially eliminating the possibility of personnel exposure to downhole operation risks.

[0083] Further, the seamless switching mechanism of the two modes solves the problem of long debugging period caused by the integration of multi-source heterogeneous equipment: the virtual debugging stage can directly verify the collaboration of control logic and equipment behavior, avoid the risk of equipment collision caused by protocol adaptation or logic conflict, and greatly shorten the field debugging period; and in the remote operation stage, through the unified scheduling of video, voice and multi-protocol signals by the multi-modal fusion control link, the dependence on artificial inspection and manual operation is further reduced, realizing the reduction of staff and the increase of efficiency. In addition, the deep embedding of digital twin and artificial intelligence technology not only improves the decision-making autonomy of the local control system, but also provides a compatibility basis for subsequent extension of data to the cloud and remote collaborative operation, promoting the upgrading of traditional drilling control to intelligent and service-oriented direction.

[0084] For a better understanding of the above technical solutions, the exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more clearly, thoroughly understood and the scope of the present application can be completely conveyed to those skilled in the art.

[0085] Specifically, the present application provides a digital twin enabled intelligent drilling industry centralized control method, which comprises:

[0086] S1, in response to a mode switching instruction, controlling the intelligent driller cockpit to switch between an operating mode and a virtual mode.

[0087] It should be emphasized that the mode switching instruction includes a first switching instruction and a second switching instruction, wherein the first switching instruction includes at least one of the following: a virtual debugging instruction from a touch interface / operation handle connected to a remote control system PLC, a trigger signal of a virtual node representing a logical breakpoint of a kinematic link of a drilling equipment in a digital twin environment parsed based on a pre-calibrated drilling process topology graph, and a trigger signal of a first type of target drilling equipment confirmation point; the second switching instruction includes at least one of the following: a device remote control instruction from the touch interface / operation handle, a trigger signal of a physical node representing a mechanical breakpoint of equipment linkage in actual drilling operation parsed based on the drilling process topology graph, and a trigger signal of a second type of target drilling equipment confirmation point. The first type of target drilling equipment confirmation point is a verification node representing that the kinematic constraint of the drilling equipment in the drilling platform area equipment meets the standard in the virtual debugging environment, and the second type of target drilling equipment confirmation point is a verification node representing that the safety operation boundary condition of the drilling equipment in the drilling platform area equipment is established in the physical operation environment.

[0088] S2, in the case that the intelligent driller cockpit enters the virtual mode, activating the digital twin link and disconnecting the remote control link, so that the remote control system PLC sends the multi-source data of the drilling platform area equipment obtained to the digital twin server, so that the digital twin server implements cooperative virtual debugging containing mechanical behavior and electrical logic based on the deployed equipment digital model and electrical behavior model.

[0089] In the virtual mode of the intelligent driller cockpit, the system realizes directional switching of hardware connection and data flow through a reconfigurable communication topology. As shown in Figure 3 The remote control link between the remote control system PLC and the drilling platform area switch is disconnected, and a dedicated communication channel with the digital twin server is activated at the same time. The external touch screen and operation handle are connected to the remote control system PLC as a local debugging interface, the link from the video server to the display screen is cut off for real-time video stream transmission, and it is ensured that the display screen only displays the digital twin simulation picture.

[0090] Further, as shown in Figure 4 the digital twin server in step S2 implements a collaborative virtual debugging containing mechanical behavior and electrical logic based on the deployed equipment digital model and electrical behavior model, including:

[0091] S21, perform multi-layer heterogeneous data verification containing equipment state self-checking, transmission link integrity checking and data logic threshold checking on the acquired mechanical motion parameters and electrical control signals of the drilling floor area equipment, and output the verified data. Among them, the equipment state self-checking is to verify the sensor data validity based on the IO module state register value of the PLC; the transmission link integrity checking is to confirm the communication channel reliability by comparing redundant data packets; the data logic threshold checking is to filter out abnormal sampling values beyond the physical limit of the equipment.

[0092] S22, align the sampling time of the verified data with the starting time of the digital twin server simulation period by calling the PLC hardware clock, and based on the obtained alignment result, implement interpolation operation to compensate the timing deviation caused by network transmission jitter, and generate a time-domain continuous data stream.

[0093] S23, based on the pre-deployed equipment digital model and electrical behavior model, perform collaborative virtual debugging of mechanical motion trajectory and electrical control timing according to the time-domain continuous data stream. Among them, the collaborative virtual debugging includes dynamic position matching of equipment motion trajectory and equipment digital model, verification of timing response of received equipment operation signal in the electrical behavior model, and generation of visual correction suggestion when mechanical interference or electrical parameter exceeds the limit.

[0094] In the above steps, a self-developed software system is running in the digital twin server, which is divided into three modules: (1) communication module: communicate with the remote control system PLC, receive the trigger signal of the key nodes of the drilling process (such as equipment start and stop, positioning completion), and synchronously acquire the motion state parameters (speed, displacement, pressure) and electrical control signals (valve position instruction, motor speed) of the drilling floor area equipment (such as pipe rack, iron roughneck, top drive, catwalk machine, etc.) from the field PLC (such as Figure 1 the PLC of the pipe rack, the PLC of the iron roughneck, the PLC of the top drive, etc. as shown) of the remote control system PLC; (2) voice broadcast module: according to the key nodes of the drilling process and the equipment confirmation points, play voice to provide real-time guidance for the driller operation, which supports multi-language switching; (3) digital twin module: pre-import the models of each equipment, realize collaborative virtual debugging and play simulation animation according to the data transmitted by the PLC, which includes dynamic position matching of equipment motion trajectory and equipment digital model, verification of timing response of received equipment operation signal in the electrical behavior model, and generation of visual correction suggestion when mechanical interference or electrical parameter exceeds the limit.

[0095] Through the above architecture and process, the hardware isolation in virtual mode and software cooperation effectively guarantee the safety of debugging and training, and the system reproduces the real work scene through high-fidelity models and multi-modal interaction (vision + voice), which not only avoids the risk of personnel contacting high-risk areas, but also provides a reliable environment for pre-validation of control logic.

[0096] Further, as shown in Figure 5 Step S23 includes:

[0097] S231, call the device digital model pre-deployed in the NX MCD module of the digital twin server, perform kinematics calculation on the mechanical motion parameters in the time-domain continuous data stream, generate three-dimensional coordinate point cloud data of the motion transmission assembly of the drilling equipment in the drilling platform area equipment, and map the three-dimensional coordinate point cloud data to the trajectory reference of the mechanical action.

[0098] S232, calculate the Hausdorff distance between the three-dimensional coordinate point cloud data of the motion transmission assembly and the preset reference trajectory template to generate a position matching deviation value.

[0099] Through the digital twin module to analyze the mechanical motion parameters (including the translation speed of the catwalk machine P, the clamping force of the buffer hand, the rotation speed of the top drive, the pipe laying trajectory of the pipe laying machine, etc.) transmitted by the remote control system PLC, call the pre-defined high-fidelity device digital model in the Siemens NX MCD module to perform kinematics calculation, based on the rigid body dynamics equation: . Wherein, T is the joint torque, J(θ) is the Jacobian matrix, θ is the joint angle, τ is the driver output torque, for a mechanical system with n degrees of freedom, the dimension of the Jacobian matrix J(θ) is 6×n, which is derived from the geometric kinematics relationship. Its column is the contribution of each joint speed to the linear speed and angular speed of the end effector:

[0100] ;

[0101] In the formula, v is the linear speed of the end effector; ω is the angular speed of the end effector; θ i is the motion speed (rotation or translation) of the i-th joint. According to the Newton-Euler equation, the joint torque T is the mapping result of the driver output torque τ through the Jacobian matrix.

[0102] Generate three-dimensional coordinate point cloud data of the transmission assembly of the drilling platform equipment (such as the iron driller gear box and the elevator lifting mechanism), and accurately represent its dynamic pose.

[0103] Subsequently, by calculating the Hausdorff distance between the generated point cloud data and the preset reference trajectory template, the position matching deviation value is quantified, and the abnormal area where the mechanical motion trajectory deviates from the design target is identified. Wherein, the position matching deviation value is:

[0104] ;

[0105] In the formula, A is the measured point cloud set, B is the reference trajectory point cloud set, d(a, b) is the Euclidean distance, is the maximum value of the minimum distance of each point in the actual point cloud to the reference trajectory template, is the maximum value of the minimum distance of each point in the reference trajectory template to the actual point cloud, and the deviation value exceeds the preset spatial threshold (such as ±5mm) to determine the abnormality.

[0106] S233, in the electrical behavior model constructed by the SIMIT module pre-deployed in the digital twin server, load the electrical control signals in the time domain continuous data stream, analyze the electrical logic state in the electrical control signals and mark the electrical phase, and obtain the electrical event sequence with phase marking.

[0107] S234, based on the electrical event sequence with phase marking, reconstruct the phase relationship of the PLC control cycle of the remote control system through timestamp alignment and cycle division, and couple the signal transmission delay, valve body response delay and mechanical inertia delay, to construct a time sequence simulator representing the valve control execution timing window and the displacement amount of the actuator.

[0108] S235, based on the output of the time sequence simulator, analyze the independent contribution values of the signal transmission delay, valve body response delay and mechanical inertia delay.

[0109] S236, according to the independent contribution values of the signal transmission delay, valve body response delay and mechanical inertia delay, calculate the phase offset of the starting time of the electrical control signal response delay and the corresponding mechanical action trajectory reference through dynamic weight superposition; wherein the signal transmission delay is based on the network communication protocol feature calibration, the valve body response delay is calibrated through the step response experiment, and the mechanical inertia delay is generated according to the equipment digital model simulation. Preferably, the load dynamics delay is generated according to the mass-spring-damping digital twin model simulation.

[0110] Further, load the electrical control signals (such as hydraulic station valve group switch instructions, slip locking signals) in the SIMIT module of the digital twin module, reconstruct the PLC control cycle phase through timestamp alignment, and couple the following delay factors to construct a time sequence simulator: signal transmission delay (Δt net ): based on the Modbus TCP protocol feature calibration as a fixed value (such as 20ms); valve body response delay (Δt valve ): calibrated through the step response experiment (such as solenoid valve opening and closing delay 50ms); mechanical inertia delay (Δt mech): generated according to the dynamic simulation of the equipment digital model (e.g. winch inertia delay 100 ms). The timing simulator outputs the valve control execution window: effective time (t e = t c + Δt net + Δt valve ), and the trajectory mapping relationship of the actuator displacement varying with time generated in combination with the mechanical inertia delay (Δt mech ), wherein t e is the effective time of the actual action of the actuator, t c is the initial time of the control instruction sent by the PLC, and the actuator displacement is calculated and generated in combination with Δt mech by the dynamic simulation of the equipment digital model.

[0111] Next, the dynamic weight superposition model is used to calculate the phase offset between the electrical signal response and the mechanical action: , the weights w1 = 0.3, w2 = 0.5, and w3 = 0.2 (according to the sensitivity distribution of the actual system). If the phase offset exceeds the preset timing tolerance (e.g. ±10 ms), it is determined that the timing is mismatched.

[0112] S237, when the position matching deviation value exceeds the preset spatial threshold or the phase offset exceeds the preset timing tolerance range, a visual data including a three-dimensional space deviation heat map, an electrical phase offset curve, and a stiffness correction parameter is generated, and a corresponding correction instruction is provided for the visual data and packaged as a virtual correction instruction package.

[0113] When the dynamic position deviation or the phase offset is out of limit, the visual correction data is generated by the digital twin module: the three-dimensional space deviation heat map: the interference area is marked with a color gradient (e.g. red represents the risk of collision between the drill pipe and the well wall); the electrical phase offset curve: shows the cumulative trend of signal delay (e.g. valve control instruction lag leads to top drive start delay); stiffness correction parameter: recommends the mechanical structure optimization value (e.g. "increase the buffer hand, hydraulic cylinder stiffness to 200 kN / m"); the correction instruction is packaged as a virtual instruction package (JSON format), which is fed back to the PLC debugging interface through the communication module, and the voice broadcast module plays a multilingual prompt (e.g. "adjust the pipe conveyor speed of the pipe conveyor to 1.2 m / s").

[0114] Specifically, a protocol conversion middleware is independently configured between the remote control system PLC and the digital twin server to realize seamless semantic adaptation of physical control and virtual simulation. The middleware is independently deployed in the communication link between the two, and focuses on eliminating the semantic conflicts between the hardware protocol and the simulation logic. When the digital twin link is activated, the protocol conversion middleware implements at least one of the following semantic consistency works:

[0115] (1) Construct and maintain the mapping table between the remote control system PLC and the digital twin server.

[0116] (2) Real-time receive the debugging instruction stream from the remote control system PLC, and extract the debugging instruction semantics, and map the debugging instruction semantics to the simulation excitation signal that can be parsed by the digital twin server; wherein the timestamp of the simulation excitation signal is integer multiple synchronized with the PLC scanning period. The middleware receives the debugging instruction stream (such as "start hydraulic station" and "adjust top drive speed") sent by the remote control system PLC in real time, analyzes its operation semantics, and converts it into a simulation excitation signal that can be recognized by the digital twin server. It is worth mentioning that the PLC control system executes logic operation and signal update in a fixed scanning cycle. If the timestamp of the simulation excitation signal is not integer multiple synchronized with the PLC scanning period, it may cause the signal to arrive outside the PLC scanning window, resulting in signal misplacement or response delay accumulation. For example, the PLC may not capture the simulation signal in the first scanning period, and needs to wait for subsequent processing, which destroys the real-time nature of virtual-real synchronization. Integer multiple synchronization ensures that the triggering time of the simulation signal is always aligned with the start point of the PLC scanning period. For example, if the PLC scanning period is 100 ms, the simulation signal interval is set to 200 ms (2 times relationship), then each simulation update is precisely embedded in the execution gap of the PLC control logic, avoiding signal competition caused by random arrival of multiple signals.

[0117] (3) Reverse analyze the virtual correction semantics of the virtual correction instruction package output by the digital twin server, and convert the correction semantics into physical debugging signals that can be recognized by the remote control system PLC according to the pre-defined PLC electrical coding rules. When the digital twin server generates a virtual correction instruction package (such as "compensate for the delay of the clamp locking" and "optimize the pipe conveying trajectory of the pipe rack machine"), the middleware reversely analyzes its correction intention, and converts it into physical debugging signals executable by the PLC according to the PLC's electrical coding rules containing signal types, address mapping, etc.

[0118] (4) When it is detected that the virtual correction semantics conflict with the pre-set PLC hardware protocol constraints, locate the conflict instruction segment based on the mapping table and apply a semantic isolation marker, and at the same time call the pre-stored PLC historical control instruction template to replace the instruction segment with the semantic isolation marker. In subsequent instruction conversion, skip the instruction segment with the semantic isolation marker, and only pass the replaced historical control instruction to the PLC

[0119] (5) Bit by bit verify the bit alignment consistency of the protocol control word bit field of the remote control system PLC and the state variable of the digital twin server, verify the matching degree of the dimensionless parameter unit value of the simulation excitation signal and the linear transformation coefficient of the physical debugging signal range, and verify the integer multiple synchronization of the timestamp of the simulation excitation signal and the PLC scanning period.

[0120] It needs to be understood that the middleware built-in mapping table records the corresponding rules of PLC control instructions and digital twin simulation signals (for example, "PLC address 0x1011" corresponds to "virtual top drive rotating speed"). If it is detected that the virtual correction semantics conflict with the PLC hardware protocol, the conflict instruction segment is automatically marked as "isolation zone", and the history control template of the last period effective instruction is called to replace the isolation content to prevent illegal signal injection.

[0121] Then, by comparing PLC control words (such as status flag bits, fault codes) with digital twin state variables (such as simulation device running mode, alarm state) bit by bit, it is ensured that the bit meanings of the two are strictly aligned. At the same time, the linear relationship between the simulation parameter unit value and the physical range and the timestamp synchronization (for example, the simulation period is an integer multiple of the PLC period) are verified.

[0122] It needs to be emphasized that if any of the above verifications fails, the semantic consistency deviation value is recorded according to the preset weight assignment rule based on the deviation type, and is updated to the log; when the cumulative value of the semantic consistency deviation recorded in the log exceeds the preset threshold, a hybrid control instruction set compatible with the remote control system PLC physical protocol and the virtual debugging target is generated based on the preset fuzzy logic rule base, the hybrid control instruction set is sorted according to the safety level, and then written to the pre-execution buffer queue of the remote control system PLC, and the instruction reconstruction request is fed back to the remote control system PLC.

[0123] Specifically, according to the deviation type recorded in the log, the dominant conflict type is determined, and the following deviation corresponding table is referred to:

[0124] Table 1 Deviation Corresponding Table

[0125]

[0126] Then, the conflict resolution strategy predefined in the fuzzy logic rule base is called:

[0127] Rule 1: If the timing deviation is dominant and involves the target device, the physical protocol constraints are prioritized, and the virtual correction amplitude is limited.

[0128] Rule 2: If the parameter unit value mismatch occurs but the device is in a non-emergency state, dynamic scaling of the correction parameter within the range is allowed.

[0129] Then, the virtual correction target is combined with the PLC physical protocol limit (such as the maximum rotating speed set value of the PLC register is 1000 rpm) to generate a compromise instruction (such as "stage-by-stage increase rotating speed: current 800 rpm→next period 950 rpm→final 1000 rpm").

[0130] According to the instruction influence range, the security level is divided: high-risk instruction (red): operation directly affecting personnel safety or equipment integrity (such as emergency stop signal, overpressure protection); medium-risk instruction (yellow): operation involving key processes but allowing temporary delay (such as drill rod posture adjustment); low-risk instruction (green): parameter fine-tuning or non-real-time operation (such as log recording period modification).

[0131] The sorted mixed instruction set is packaged into a PLC-resolvable communication frame, and the security level identifier of each instruction is marked. The instructions are written into the pre-execution buffer queue of the PLC, that is, a temporary storage area independent of the real-time control cycle, to avoid directly overwriting the current execution logic of the PLC, an interrupt request signal is sent to the PLC to trigger it to load new instructions from the buffer queue at the beginning of the next scanning period, and the middleware monitors the PLC response state, and if the timeout is not confirmed, a rollback mechanism is started.

[0132] S3, in the case that the intelligent driller cabin enters the operation mode, activating the remote control link and disconnecting the digital twin link, so that the remote control system PLC performs remote multi-modal operation on the drilling rig area equipment.

[0133] As shown in Figure 6 , in response to the first switching signal, switching to the equipment remote control mode of the intelligent driller cabin, establishing the control link between the remote control system PLC and the drilling equipment, drilling rig area PLC, video network server, and drilling rig area camera, restoring the real-time control capability of the drilling equipment, cutting off the communication between the remote control system PLC and the digital twin server, and stopping the simulation data interaction and debugging. valve After switching, the display screen switches to the drilling rig area camera picture, and the driller can directly remotely control the drilling rig equipment through the touch screen and the operation handle.

[0135] It should be understood that the software system of the video network server has seven functional modules built-in, among which the communication module: interacts with the remote control system PLC and receives the drilling process node trigger signal sent by the PLC; the video analysis module: dynamically selects the decoding protocol and resolution scaling strategy according to the camera parameters and scene characteristics; the video display module: displays all camera pictures in a dynamic layout containing a nine-square or sixteen-square layout, and automatically switches to full-screen display of the corresponding channel according to the drilling node; the video storage module: stores all camera data for up to half a year; the voice broadcast module: plays multi-language prompt voice according to the drilling node; the voice recognition module: receives the driller's voice command to control video switching, full-screen operation, and smart home adjustment; the smart home module: controls air conditioning, television, light on / off, and state adjustment through WiFi / Zigbee protocol.

[0136] Further, as shown in Figure 7 , step S3 includes:

[0137] S31, by connecting the video network server of the remote control system PLC and the camera in the drilling platform area equipment respectively, according to the camera deployment parameters and drilling scene features of the obtained drilling area, dynamically selecting the video decoding protocol and resolution scaling strategy, and generating the drilling area video stream data.

[0138] Further, as shown in the step S31 includes: Figure 8

[0139] S311, obtain the deployment parameters of the camera in the drilling area, which include hardware constraint parameters and transmission constraint parameters. The hardware constraint parameters include camera type, optical zoom ratio, etc., and the transmission constraint parameters include installation angle, network bandwidth, etc.

[0140] S312, based on the obtained sensor data and device log of the drilling platform area equipment, identify the drilling scene features including operation mode parameters and environmental interference parameters. The operation mode parameters include operation stage attributes, device density, etc., and the environmental interference parameters include lighting conditions, etc.

[0141] S313, if the hardware constraint parameters exist camera types supporting hardware acceleration and the network bandwidth in the transmission constraint parameters is lower than the preset bandwidth threshold, apply GPU hardware accelerated decoding to the pre-labeled device area video stream, and use adaptive decoding with dynamic code rate to the non-pre-labeled device area to obtain the decoded video stream.

[0142] Specifically, if the camera type supports GPU hardware decoding and the network bandwidth is ≤20Mbps, apply GPU hardware accelerated decoding to the pre-labeled device area video stream, with fixed resolution (such as 1080p@30fps), and switch to adaptive decoding with dynamic code rate (such as H.265+B frame dynamic discard) for non-labeled area, with the upper limit of code rate being 80% of the bandwidth. The pre-labeled device area refers to the monitoring area in the drilling operation process that meets at least one of the following conditions: there is a direct operation association with the operation link labeled as a key node of the process (such as drill bit posture sensor docking area, pressure monitoring point); it is in the preset safe and high-risk monitoring list of device operation range (such as real-time operation area of rotary top drive device).

[0143] S314, if the environmental interference parameters meet the preset low-light condition, based on the decoding mechanism of multi-frame cumulative noise reduction and infrared image sensor data fusion, forcibly enable the night vision mode of the camera and use dynamic histogram to equalize the decoded video stream. In low-light environment, the camera automatically switches to night vision mode and outputs an enhanced picture with clear details, significantly improving the visualization quality of the drilling platform equipment monitoring video.

[0144] ​S315, obtain the device motion trajectory density distribution heat map by optical flow analysis of the equalization processed video stream, perform original resolution local cropping on the peak value area of the heat map, and perform edge-preserving down-sampling operation on the non-peak value area of the heat map to obtain the differentiated processed video stream. In this step, by optical flow analysis of the equalization processed video stream, the device motion trajectory density distribution heat map is obtained, the peak value area (density ≥ 85%) of the heat map is cropped at the original resolution (such as 1080p→1080p), and the low-density area (density < 85%) is down-sampled with edge preservation (such as 1080p→720p), avoiding the sawtooth effect.

[0145] S316, when the job mode parameter is at the user-specified or preset destination flow node stage, output the differentiated processed video stream corresponding to the camera associated with the destination flow node at the highest resolution, and uniformly down-sample the video stream of the non-associated camera to the reference resolution. When the job mode is at the preset node (such as "drill down to the target layer"), lock the associated camera, for the associated camera, maintain the highest resolution output, and for the non-associated camera, uniformly down-sample to the reference resolution. Finally, generate optimized video stream data by applying the selected decoding protocol and resolution strategy, and when the hardware resource occupation of the protocol selection rule and the resolution adjustment logic conflicts, the execution of the resolution adjustment logic is prioritized, specifically, part of the non-critical decoding thread is suspended, the resolution of the heat map peak value area is prioritized, and the decoding protocol of the non-designated area is downgraded from H.265 to H.264 to release resources.

[0146] S32, real-time tracking at least one of the drilling equipment motion trajectory, the drilling flow preset node and the trigger signal of the drilling equipment confirmation point, and constructing a dynamic layout topology of a video picture according to the drilling area video stream data.

[0147] Further, as shown in Figure 9 S32 includes:

[0148] S321, enable the grid global monitoring mode in the video display module of the video network server, and the division granularity of the grid global monitoring mode is positively correlated with the device displacement speed. First, the video analysis module calls the SDK to analyze the drilling area video stream data code stream to obtain the original video data of each camera in real time. Then, the video display module dynamically enables the grid global monitoring mode in combination with the real-time change data of the device pose (such as the top drive coordinates). It needs to be understood that the grid global monitoring mode is configured to divide the screen into NXM grids, N and M are both greater than or equal to 3, and the division granularity is positively correlated with the device displacement speed (the higher the speed, the finer the division, for example, low-speed device (<1m / s): 3x3 basic grid division; high-speed device (≥1m / s): switch to 5x5 fine division to capture fast motion details); the main grid area is the central grid (such as the central grid of a 3x3 layout or the 3rd row and 3rd column of a 5x5 layout), and the edge grid is distributed in a ring level for parallel monitoring of multi-camera video streams.

[0149] S322, when the trigger signal of the drilling process preset node and / or the device confirmation point is detected, switch from the grid global monitoring mode to the single-channel full-screen focus mode, display the associated camera picture in the main grid area, and display the non-associated picture in the edge grid in a semi-transparent manner with a preset low frame rate. The single-channel full-screen focus mode is configured to expand the main grid area to full screen, and hide or compress the edge grid area to a side floating bar for single picture monitoring.

[0150] S323, when the device motion trajectory deviates from the preset path is recognized, the device tracking mode is activated, the tracking sub-picture is inserted in the grid global monitoring mode, and the device offset vector is calibrated in real time. The device tracking mode is configured to fixedly display the global picture in the main grid area, and dynamically insert the tracking sub-window in the edge grid area to follow the moving trajectory of the target device for real-time tracking.

[0151] S324, in the single-channel full-screen focus mode and the device tracking picture-in-picture mode, at least one of the device pose deviation alarm box, the operation guide arrow, and the voice broadcast is superimposed.

[0152] S33, a semantic interaction channel of the voice instruction set and the PLC control instruction of the remote control system is established to convert the voice instruction into an executable instruction of the PLC of the remote control system, or convert the state data fed back by the PLC into voice broadcast information.

[0153] Further, as shown in Figure 10 , step S33 comprises:

[0154] S331, a semantic interaction channel of the voice instruction set and the PLC control instruction of the remote control system is established by using the voice recognition module and the TTS engine of the video network server.

[0155] S332, convert the received voice instruction into a text command through a semantic interaction channel, and perform domain adaptive noise reduction processing and drilling terminology keyword extraction on the text command. The voice recognition module calls a cloud API, such as an Ali Cloud voice recognition engine, to convert the voice instruction input by the operator into a raw text command; the text is subjected to drilling domain-specific noise reduction, non-essential or redundant words such as "uh" and "this" are filtered out, and drilling terminology keywords are extracted.

[0156] S333, fuzzy match the extracted drilling terminology keywords with the predefined device operation semantic tree, and generate device type encoding and operation action encoding bound to the matching result when the matching is successful. Fuzzy match the keywords with the predefined device operation semantic tree, such as mapping the keywords "top drive" and "rotational speed" to the semantic tree node "top drive-rotational speed control"; after successful matching, bind the device type encoding (such as DT-101 representing top drive) and the operation action encoding (such as OP-202 representing rotational speed adjustment).

[0157] S334, perform time sequence alignment processing on the multi-parameters in the noise-reduced text command, and generate a parameter value sequence bound to the operation action encoding.

[0158] S335, based on the device type encoding, operation action encoding and parameter value sequence, generate a control word containing a function code and a register address sequence, and issue the control word to the drilling floor area device and simultaneously create a response monitoring thread. According to the device type encoding and operation action encoding, match the predefined function code (such as Modbus function code 06) and register address (such as 0x0003 representing the top drive rotational speed register) in the PLC protocol. Encapsulate it into a control word according to the protocol format, and issue it to the drilling floor area PLC for execution through industrial Ethernet. The control word bit field encoding rule table is as follows:

[0159] Table 2 Control word bit field encoding rule table

[0160]

[0161] S336, when the response monitoring thread captures the device state signal feedback by the drilling equipment, analyze the device state signal, match the analysis result with the preset fault level dictionary, and obtain the fault matching level.

[0162] S337, use the fault matching level to call the TTS engine to generate voice broadcast content with different emotional tones and play it back. When the PLC returns the device state, analyze the signal and match the preset fault level dictionary to determine the fault level, call the TTS engine according to the fault level, generate voice broadcast content with emotional tones such as urgent tone and smooth tone, and inject it into the voice broadcast module of the video network server for playback.

[0163] S34, in response to voice instructions or input instructions from a touch interface / operating handle connected to the remote control system PLC, the corresponding instructions are issued to the drilling floor area equipment and / or the cabin smart home equipment through the pre-constructed communication protocol cluster. In addition to connecting and controlling the drilling floor area equipment through Zigbee, WiFi, etc. Communication protocol cluster, the following cabin smart home equipment is also controlled: air conditioning subsystem, television subsystem and lighting subsystem. It needs to be clear that user voice instructions need to be converted into instructions executable by the remote control system PLC based on semantic interaction channel before being issued, and the channel priority of the control instructions of the drilling floor area equipment is higher than that of the control instructions of the cabin smart home equipment.

[0164] In another aspect, the embodiments of the present application provide a digital twin enabled intelligent drilling industry centralized control system, referring again to Figure 1 , comprising: drilling floor area equipment, including drilling equipment, drilling floor area PLC, camera and switch; intelligent driller cabin, applied to the method as described above, the intelligent driller cabin comprises: remote control system PLC, digital twin server, video network server, display screen and switch.

[0165] Among them, the remote control system PLC is connected with the drilling equipment and the drilling floor area PLC through the switch respectively, and the remote control system PLC and the drilling floor area PLC are externally connected with the touch screen and / or the operating handle; the digital twin server is connected with the remote control system PLC and the display screen respectively; the video network server is connected with the remote control system PLC and the drilling floor area camera through the switch respectively; the remote control system PLC, the digital twin server and the display screen form a digital twin link; the remote control system PLC forms an equipment remote control link with the drilling equipment and the drilling floor area PLC by using the switch, and forms a video monitoring link with the drilling floor area camera by using the switch and the video network server, and the equipment remote control link and the video monitoring link jointly constitute a remote control link.

[0166] The centralized control system has two working modes. In the virtual mode, technicians and rig driller can debug and train through the platform respectively, and in this process, the real equipment does not need to be started, reducing the possibility of accidents; in the operation mode, each device is controlled by the intelligent driller cabin on the ground, and the operating personnel are away from the dangerous area of the drilling floor, which ensures the safety of personnel. In addition, the operation of each device can be remotely monitored on the ground, realizing the efficiency of drilling operation with less staff. The deployment of artificial intelligence related technology in the intelligent driller cabin also realizes the fusion of traditional electric control technology and artificial intelligence technology, which is conducive to the subsequent realization of cloud expansion of data and other more extensive applications.

[0167] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer-readable program code.

[0168] The present application is described in reference to the flowchart and / or block diagrams of the method, apparatus (system) and computer program product according to embodiments of the present application. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a computer, special purpose computer, or a data processor or

[0169] Although preferred embodiments of the application have been described herein, additional modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the application. Accordingly, it is intended that all such modifications and changes be included within the scope of the application as set forth in the following claims.

[0170] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims, the application can be practiced otherwise than as specifically described herein.

Claims

1. A digital twin-enabled intelligent industrial centralized control method, characterized in that, An intelligent industrial centralized control system enabled by digital twins is provided. The system includes a remote control system PLC and a digital twin server located in the intelligent driller's cab. A digital twin link is established between the remote control system PLC and the digital twin server, and a remote control link is established with equipment in the drilling rig area. The method includes: In response to mode switching commands, the intelligent driller's cab is controlled to switch between operating mode and virtual mode; When the intelligent driller's cab enters virtual mode, the digital twin link is activated and the remote control link is disconnected so that the remote control system PLC can send the multi-source data of the equipment in the drilling rig area to the digital twin server, enabling the digital twin server to perform collaborative virtual debugging, including mechanical behavior and electrical logic, based on the deployed equipment digital model and electrical behavior model. When the intelligent driller's cab enters the operation mode, the remote control link is activated and the digital twin link is disconnected so that the remote control system PLC can perform remote multimodal operations on the equipment in the drilling rig area. The digital twin server performs collaborative virtual debugging based on the deployed equipment digital model and electrical behavior model, including mechanical behavior and electrical logic. This includes: performing multi-layer heterogeneous data verification on the acquired mechanical motion parameters and electrical control signals of the drilling platform area equipment, including equipment status self-check verification, transmission link integrity verification, and data logic threshold verification, and outputting the verified data; calling the PLC hardware clock to align the sampling time of the verified data with the start time of the digital twin server simulation cycle, and performing interpolation based on the alignment result to compensate for timing deviations caused by network transmission jitter, generating a continuous time-domain data stream; and performing collaborative virtual debugging of mechanical motion trajectory and electrical control timing based on the pre-deployed equipment digital model and electrical behavior model according to the continuous time-domain data stream. The collaborative virtual debugging includes dynamic position matching of the equipment motion trajectory and the equipment digital model, verification of the timing response of received equipment operation signals in the electrical behavior model, and generation of visual correction suggestions when mechanical interference or electrical parameter deviations occur. Based on a continuous time-domain data stream, collaborative virtual debugging of mechanical motion trajectories and electrical control timing is performed using pre-deployed equipment digital models and electrical behavior models. This includes: calling the equipment digital model pre-deployed in a digital twin server; performing kinematic calculations on the mechanical motion parameters in the data stream; generating point cloud data of the motion transmission components of the drilling equipment in the drilling rig area; mapping the point cloud data to a trajectory reference for mechanical actions; calculating the Hausdorff distance between the point cloud data of the motion transmission components and a preset reference trajectory template to generate a position matching deviation value; loading electrical control signals from the data stream into the pre-deployed electrical behavior model in the digital twin server; parsing the electrical logic states in the electrical control signals and marking the electrical phases to obtain a phase-marked electrical event sequence; and based on the electrical event sequence... The phase relationship of the PLC control cycle in the remote control system is reconstructed by timestamp alignment and period segmentation, and signal transmission delay, valve body response delay and mechanical inertia delay are coupled to construct a timing simulator. Based on the output of the timing simulator, the independent contribution values ​​of signal transmission delay, valve body response delay and mechanical inertia delay are analyzed. According to the independent contribution values ​​of signal transmission delay, valve body response delay and mechanical inertia delay, the phase offset between the electrical control signal response delay and the starting time of the trajectory reference of the corresponding mechanical action is calculated by dynamic weight superposition. When the position matching deviation value exceeds the preset spatial threshold or the phase offset exceeds the preset timing tolerance range, visualization data including a three-dimensional spatial deviation heat map, electrical phase offset curve and stiffness correction parameters is generated. Then, corresponding correction instructions are provided for the visualization data and encapsulated into a virtual correction instruction package.

2. The intelligent industrial centralized control method empowered by digital twins as described in claim 1, characterized in that, The mode switching instructions include a first switching instruction and a second switching instruction, wherein, The first switching instruction includes at least one of the following: a virtual debugging instruction from a touch interface / operating handle connected to the remote control system PLC, a trigger signal for a virtual node representing a logical breakpoint of the kinematic link of the drilling equipment in the digital twin environment, which is parsed from a pre-calibrated drilling process topology diagram, and a trigger signal for a first-type target drilling equipment confirmation point, wherein the first-type target drilling equipment confirmation point is a verification node representing the kinematic constraint compliance of the drilling equipment in the drilling platform area equipment in the virtual debugging environment; The second switching instruction includes at least one of the following: a device remote control instruction from the touch interface / operating handle, a trigger signal of a physical node representing a mechanical breakpoint of equipment linkage in actual drilling operations, which is parsed from the drilling process topology diagram, and a trigger signal of a second type of target drilling equipment confirmation point. The second type of target drilling equipment confirmation point is a verification node representing the establishment of safe operation boundary conditions for drilling equipment in the drilling platform area under physical operating conditions.

3. The intelligent industrial centralized control method empowered by digital twins as described in claim 1, characterized in that, A protocol conversion middleware is independently configured between the remote control system PLC and the digital twin server. When the digital twin link is active, the protocol conversion middleware performs at least one of the following semantic consistency operations: Build and maintain a mapping table between the remote control system PLC and the digital twin server; The system receives debugging instruction streams from the remote control system PLC, extracts the semantics of the debugging instructions, and maps the semantics of the debugging instructions to simulation excitation signals based on the mapping table; wherein, the timestamp of the simulation excitation signal is synchronized with the PLC scan cycle as an integer multiple. The virtual correction semantics of the virtual correction instruction packets output by the digital twin server are parsed, and the correction semantics are converted into physical debugging signals based on the mapping table and predefined PLC electrical coding rules. When a conflict is detected between the virtual correction semantics and the preset PLC hardware protocol constraints, the conflicting instruction segment is located based on the mapping table and a semantic isolation mark is applied. At the same time, the pre-stored PLC historical control instruction template is called to replace the instruction segment with the semantic isolation mark. The bit-by-bit verification of the bit alignment consistency between the protocol control word bit field of the remote control system PLC and the state variables of the digital twin server is performed. The matching degree of the dimensionless parameter per unit value of the simulation excitation signal and the linear transformation coefficient of the physical debugging signal range is verified. The synchronization of the timestamp of the simulation excitation signal and the integer multiple of the PLC scan cycle is also verified. If any of the above verifications fails, the semantic consistency deviation value is recorded according to the deviation type and the preset weight assignment rules, and updated to the log. When the cumulative value of semantic consistency deviation recorded in the log exceeds the preset threshold, a hybrid control instruction set is generated based on the preset fuzzy logic rule base, written into the pre-execution buffer queue of the remote control system PLC, and a request for instruction reconstruction is sent back to the remote control system PLC.

4. The intelligent industrial centralized control method empowered by digital twins as described in any one of claims 1-3, characterized in that, The remote control system PLC performs remote multimodal operations on the equipment in the drilling rig area, including: By connecting the remote control system PLC and the cameras in the drilling area equipment to the video network server, the video decoding protocol and resolution scaling strategy are dynamically selected based on the obtained camera deployment parameters and drilling scene characteristics in the drilling area to generate video stream data of the drilling area. Real-time tracking of at least one of the following information: drilling equipment movement trajectory, preset nodes of the drilling process, and trigger signals of drilling equipment confirmation points; and construction of a dynamic layout topology of the video screen based on video stream data of the drilling area. Establish a semantic interaction channel between the voice command set and the control commands of the remote control system PLC, so as to convert the voice commands into commands that can be executed by the remote control system PLC, or convert the status data fed back by the PLC into voice broadcast information; In response to voice commands or input commands from a touch interface / operating handle connected to the remote control system PLC, corresponding commands are sent to the drilling platform area equipment and / or the cockpit smart home equipment through a pre-built communication protocol cluster. Among them, user voice commands need to be converted into commands executable by the remote control system PLC based on the semantic interaction channel before being sent. The channel priority of the control commands of the drilling platform area equipment is higher than that of the control commands of the cockpit smart home equipment.

5. The intelligent industrial centralized control method empowered by digital twins as described in claim 4, characterized in that, By connecting the remote control system PLC to the cameras in the drilling rig area via a video network server, the system dynamically selects the video decoding protocol and resolution scaling strategy based on the acquired camera deployment parameters and drilling scene characteristics to generate drilling area video stream data, including: The deployment parameters of the cameras in the drilling area, including hardware and transmission constraints, are obtained. Based on the sensor data and equipment logs of the equipment in the drilling rig area, the drilling scenario characteristics, including operation mode parameters and environmental interference parameters, are identified. If the hardware constraint parameters include camera types that support hardware acceleration and the network bandwidth in the transmission constraint parameters is lower than the preset bandwidth threshold, GPU hardware acceleration decoding is applied to the video stream of the pre-calibrated device area, and dynamic bitrate adaptive decoding is used for the non-pre-calibrated device area to obtain the decoded video stream. If the environmental interference parameters meet the preset low light conditions, the camera's night vision mode will be forcibly activated, and the decoded video stream will be equalized using histograms. By analyzing the optical flow of the equalized video stream, a heatmap of the device motion trajectory density distribution is obtained. The peak areas in the heatmap are locally cropped at the original resolution, and the non-peak areas in the heatmap are subjected to edge-preserving downsampling to obtain a differentiated video stream. When the operation mode parameters are at the user-specified or preset target process node stage, the video stream corresponding to the camera associated with the target process node will be output at the highest resolution, and the video streams of unassociated cameras will be uniformly downsampled to the reference resolution for output.

6. The intelligent industrial centralized control method empowered by digital twins as described in claim 4, characterized in that, Real-time tracking of at least one of the following information: drilling equipment movement trajectory, preset nodes in the drilling process, and trigger signals of drilling equipment confirmation points; constructing a dynamic layout topology of the video frame based on the drilling area video stream data, including: Enable grid-based global monitoring mode in the video display module of the video network server; When a trigger signal is detected at a preset node in the drilling process and / or an equipment confirmation point, the system switches from the grid-based global monitoring mode to the single-channel full-screen focus mode. The associated camera images are displayed in full screen in the main grid area, while the non-associated images are shrunk to the edge grid and marked as semi-transparent while maintaining a preset low frame rate display. When the device's movement trajectory is detected to deviate from the preset path, the device tracking mode is activated, a tracking sub-screen is inserted into the grid-based global monitoring mode, and the device offset vector is marked in real time. In single-channel full-screen focus mode and device tracking picture-in-picture mode, at least one of the following information is superimposed: device pose deviation alarm box, operation guidance arrow and voice broadcast; in, The grid-based global monitoring mode is configured to divide the screen into N×M grids, where N and M are both ≥3. The main grid area is the central grid, and the edge grids are distributed in a ring-shaped hierarchy for parallel monitoring of multiple camera video streams. In the single-channel full-screen focus mode, the main grid area is expanded to the full screen, while the edge grid areas are hidden or compressed into a side floating bar. The device tracking mode is configured to display the global view in a fixed position within the main grid area, while tracking sub-windows are dynamically inserted into the edge grid areas to track the target device's movement trajectory in real time.

7. The intelligent industrial centralized control method empowered by digital twins as described in claim 4, characterized in that, Establish a semantic interaction channel between the voice command set and the remote control system PLC control commands to convert voice commands into commands executable by the remote control system PLC, or to convert the status data fed back by the PLC into voice broadcast information, including: A semantic interaction channel between the voice command set and the PLC control command of the remote control system is established by using the voice recognition module of the video network server and the TTS engine. The received voice commands are converted into text commands through a semantic interaction channel, and the text commands are then subjected to domain-adaptive noise reduction and drilling terminology keyword extraction. The extracted drilling terminology keywords are fuzzily matched with a predefined equipment operation semantic tree. When a match is successful, an equipment type code and an operation action code bound to the matching result are generated. The multiple parameters in the denoised text command are time-aligned to generate a sequence of parameter values ​​bound to the operation action code; Based on the equipment type code, operation action code and parameter value sequence, a control word containing function code and register address sequence is generated, and the control word is sent to the equipment in the drilling rig area and a response listening thread is created simultaneously. When the response listening thread captures the device status signal fed back by the drilling equipment, it parses the device status signal, matches the parsing result with the preset fault level dictionary, and obtains the fault matching level. By utilizing fault matching levels, the TTS engine is invoked to generate and play voice broadcast content with different emotional tones.

8. A digital twin-enabled intelligent drilling industrial control system, characterized in that, include: Equipment in the drilling rig area includes drilling equipment, drilling rig area PLC, cameras, and switches; The intelligent driller's cab, which applies the method described in any one of claims 1-7, includes: a remote control system PLC, a digital twin server, a video network server, a display screen, and a switch; in, The remote control system PLC is connected to the drilling equipment and the drilling platform area PLC via switches. Both the remote control system PLC and the drilling platform area PLC have external touch screens and / or operating handles. The digital twin server is connected to the remote control system PLC and the display screen. The video network server is connected to the remote control system PLC and the drilling platform area camera via switches. The remote control system PLC, digital twin server, and display screen form a digital twin link; The remote control system PLC uses a switch to form a remote control link with the drilling equipment and the PLC in the drilling platform area. The remote control system PLC uses a switch and a video network server to form a video monitoring link with the camera. The equipment remote control link and the video monitoring link together form the remote control link.

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