Automatic remote control method and system for port machinery

Abstract

The invention discloses an automatic remote control method and system for a port machine, and relates to the technical field of automation, and the method comprises the steps: front-end processing equipment is connected with a lifting appliance positioning sensor and a motor driver, generates an equipment topological graph, is connected with a plurality of port machine PLC networks through a Profibus-DP coupler, and outputs a network state report; meanwhile, a dual-redundancy operation platform interface is configured and a state identification signal is output; based on the state identification signal, constructing an all-optical link and generating an optical fiber path topology, performing layered transmission on a lifting appliance control instruction and a path instruction, establishing a heartbeat detection mechanism and triggering a state confirmation signal; receiving a state confirmation signal and the wavelength allocation table, and acquiring laser radar point cloud data through a dedicated channel to execute lifting appliance obstacle avoidance correction; and based on the operation control authority and the new optimal path sequence, constructing a digital twin, and generating a scheduling report through an LSTM model. According to the method, the special channel and the shared channel are constructed, so that instruction blocking is eliminated.

Description

Technical Field

[0001] The present invention relates to the field of automation technology, and in particular to a port machinery automation remote control method and system. Background Art

[0002] In the field of port machinery (HVM) automation, existing technologies primarily utilize industrial buses for communication between the equipment layer and the control center, combined with PLC controllers to execute remote commands. This architecture typically relies on a wired network to connect sensors, actuators, and a central control server, with a centralized path planning algorithm generating spreader motion trajectories. Furthermore, risk response mechanisms rely on preset safety thresholds to trigger emergency stops, while energy consumption management utilizes statistical analysis of historical data to achieve load scheduling. This type of solution has been widely adopted in container terminal automation systems and demonstrates maturity in terms of standardized equipment interconnection and solidified control logic.

[0003] However, existing technologies have significant defects: First, the real-time performance of multi-device collaboration is insufficient: the industrial bus transmits mixed instructions on a single channel, resulting in command blocking in high-concurrency scenarios, resulting in high delays in the spreader's obstacle avoidance response, and the fixed delay compensation ignores the dynamic attenuation characteristics of the optical fiber; second, the dynamic risk response is delayed: collision detection only relies on static obstacle distance calculation, and does not integrate wind speed mutations and load inertia parameters, resulting in a high misjudgment rate. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a port machinery automation remote control method and system to solve the problems of lack of real-time performance and delayed dynamic risk response in the collaborative control of multiple devices under the industrial bus architecture.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a port machinery automation remote control method, comprising: The front-end processing equipment connects to the spreader positioning sensor and motor driver, generates the equipment topology diagram, interconnects multiple port machinery PLC networks through Profibus-DP couplers and outputs network status reports. It also configures a dual-redundant operation console interface and outputs status identification signals. Based on the status identification signal, an all-optical link is constructed and a fiber path topology is generated. The spreader control instructions and path instructions are transmitted in layers, and a heartbeat detection mechanism is established to trigger a status confirmation signal. Receive status confirmation signals and wavelength allocation tables, obtain lidar point cloud data through the λ1 dedicated channel to perform spreader obstacle avoidance correction, generate a global path sequence through the λ2 shared channel, and output the spreader perspective image at the same time; Calculate the collision risk factor in real time. When the collision risk safety threshold is exceeded, the spreader action is suspended and a voice alarm is sent. The remote control room is dynamically bound and the operation control authority is output. Based on the operation control authority and the new optimal path sequence, a digital twin is constructed, and a scheduling report is generated through the LSTM model.

[0007] As a preferred solution of the port machinery automation remote control method of the present invention, the output status identification signal includes the following steps: Laying network connection cables between the front-end processing equipment of multiple port machinery and recording network signal attenuation values; Configure the communication parameters of the Profibus-DP coupler unit and obtain the node information list; Analyze network signal attenuation values ​​and node information lists to generate network status reports; Extract the device serial number field and network topology path diagram of each node in the network status report and write them into the initial device database according to the record; The device status parameters of the initial device database are simultaneously output to the computer host screen display device and the touch screen display device to generate a status identification signal.

[0008] As a preferred solution of the port machinery automation remote control method of the present invention, the hierarchical transmission of the spreader control instructions and the path instructions includes the following steps: Create dedicated channel binding spreader control instructions and shared channel binding path instructions; Send a test data packet with a spreader control instruction to the dedicated channel to detect the received signal strength of filter 1 of the ONU device. At the same time, send a test data packet with a path instruction to the λ2 shared channel to detect the received signal strength of filter 2 of the ONU device and generate a wavelength configuration verification report. After confirming that the packet loss rates of all wavelength channels in the wavelength configuration verification report have converged to a stable level, activate the shared channel time division multiplexing mechanism, set the timeslot frame period, and create the timeslot allocation table; Send the time slot allocation table to the time synchronization unit of each ONU device to calibrate the clock deviation between OLT and ONU devices; After calibration is completed, a test data packet is sent to the ONU device to detect the data packet reception delay of each ONU device and generate a wavelength allocation table.

[0009] As a preferred solution of the port machinery automation remote control method of the present invention, the establishment of a heartbeat detection mechanism and triggering of a status confirmation signal includes the following steps: Extract the dedicated channel parameters in the wavelength allocation table as the heartbeat data packet transmission channel and configure the front-end PLC timer; Transmit the heartbeat data packet through the dedicated channel of the ONU device to form a heartbeat record data set; The shared backend server cluster receives the heartbeat record data set, stores and records the time intervals of continuous heartbeat packets in groups, triggers the sound and light alarm signal of the operation console, and generates a status confirmation signal.

[0010] As a preferred solution of the port machinery automation remote control method of the present invention, the execution of spreader obstacle avoidance correction includes the following steps: Receive original point cloud data, 3D coordinates of the target container center, and actual transmission delay value; Based on the difference between the timestamp of the original point cloud data and the actual transmission delay value, the original point cloud data is calibrated and the timestamp of the three-dimensional coordinates of the target container center is aligned. Then, the spreader obstacle avoidance correction is performed and the spreader posture adjustment amount is calculated. When the status confirmation signal is in the ready state, the posture adjustment amount is converted into a standard analog output voltage and the posture adjustment action is executed; When the status confirmation signal is in the safe standby state, the sling posture adjustment amount is written into the path optimization instruction ring buffer for continuous detection.

[0011] As a preferred solution of the port machinery automation remote control method of the present invention, the output operation control authority includes the following steps: The back-end shared server continuously receives path calculation request data packets through the shared channel, extracts the target endpoint coordinates, real-time motor power, and continuous operation time, and simultaneously reads the real-time 3D coordinates of the target container center as the current position; Apply the actual transmission delay value to compensate the current position and obtain the compensated starting point coordinates; Based on the compensated starting point coordinates, target end point coordinates, real-time motor power and continuous operation time, the optimal path sequence is obtained through the path cost function; Calculate the wind speed impact factor and multiply it by the original path point spacing of the optimal path sequence to obtain the optimized path sequence; Adjustment of spreader maximum speed using optimized path sequence and load weight; Calculate the collision risk factor, make collision risk assessments, and correct the fiber distance; Based on the fiber distance corrected for wind resistance, the binding priority value of each remote control room is calculated in combination with the real-time CPU load rate and network quality level of each remote control room. The remote control room with the smallest priority value is selected as the binding target, and the operation control authority is output.

[0012] As a preferred solution of the port machinery automation remote control method of the present invention, the generating of the dispatch report includes the following steps: Execute operations and new optimal path sequences based on the remote control room's operational control authority, and initialize the three-dimensional spatial coordinate system framework of the port machinery dynamics digital twin; Obtain the execution status data, meteorological data, and energy consumption pulse signal of the current optimal path sequence, input them into the LSTM model, output the energy consumption prediction value, and generate the energy consumption distribution curve; Extract the peak and valley moments of the energy consumption distribution curve, synchronously analyze the temperature parameter time series in the meteorological data, and generate a scheduling report.

[0013] In a second aspect, the present invention provides a port machinery automation remote control system, comprising: The networking module, the front-end processing equipment connects to the spreader positioning sensor and motor driver, generates the equipment topology diagram, interconnects multiple port machinery PLC networks through Profibus-DP couplers and outputs network status reports, and configures dual redundant operation console interfaces and outputs status identification signals; The optical communication module builds an all-optical link and generates a fiber path topology based on the status identification signal, transmits the spreader control instructions and path instructions in layers, establishes a heartbeat detection mechanism, and triggers a status confirmation signal; The obstacle avoidance navigation module receives the status confirmation signal and wavelength allocation table, obtains the lidar point cloud data through the λ1 dedicated channel to perform spreader obstacle avoidance correction, generates a global path sequence through the λ2 shared channel, and outputs the spreader perspective image at the same time; The emergency response module calculates the collision risk factor in real time. When the collision risk safety threshold is exceeded, the spreader action is suspended and a voice alarm is sent. The module is dynamically bound to the remote control room and outputs the operation control authority. The twin scheduling module builds a digital twin based on operation control authority and the new optimal path sequence, and generates a scheduling report through the LSTM model.

[0014] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the port machinery automation remote control method as described in the first aspect of the present invention is implemented.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the port machinery automation remote control method as described in the first aspect of the present invention is implemented.

[0016] The beneficial effects of the present invention are: constructing a dual physical isolation layer of dedicated channels and shared channels to eliminate command blocking and reduce obstacle avoidance response delay; the heartbeat detection mechanism triggers a three-level alarm to ensure the reliability of the control link; the wind speed and load inertia parameters are integrated based on the collision factor to reduce the misjudgment rate; the energy consumption distribution curve is matched with the temperature period to generate load adjustment instructions, thereby improving the overall energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 This is a flow chart of the port machinery automation remote control method.

[0019] Figure 2 Schematic diagram that identifies the signal for the output state.

[0020] Figure 3 Schematic diagram of the hierarchical transmission of spreader control instructions and path instructions.

[0021] Figure 4 A schematic diagram of establishing a heartbeat detection mechanism and triggering a status confirmation signal. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0023] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0024] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0025] Reference Figure 1 , is an embodiment of the present invention, which provides a port machinery automation remote control method, comprising the following steps: S1, the front-end processing equipment connects to the spreader positioning sensor and motor driver, generates the equipment topology diagram, interconnects multiple port machinery PLC networks through Profibus-DP couplers and outputs network status reports, and configures dual redundant operation console interfaces and outputs status identification signals.

[0026] See also Figure 2 , locate the installation position of the port machinery spreader area, fix the front-end processing equipment (embedded PLC) to the load-bearing surface of the port machinery steel structure, and use bolt fasteners to complete the physical installation of the front-end processing equipment; lay the spreader positioning sensor cable, connect one end of the cable to the digital input port of the front-end processing equipment, and the other end to the signal output interface of the spreader positioning sensor. Use a multimeter to test the cable continuity and record the continuity test results of each port; Lay the motor drive control cable, connect one end of the cable to the analog output port of the front-end processing device, and the other end to the control signal input interface of the motor drive. Use a megohmmeter to test the insulation resistance of the cable and record the insulation resistance value. Activate the power supply of the front-end processing equipment, execute the hardware self-test program, detect the communication status between the digital input port and the spreader positioning sensor, detect the communication status between the analog output port and the motor driver, and generate a self-test result report; Based on the on-off detection results, insulation resistance values ​​and self-test result reports of each port, a device topology diagram is generated that includes the physical coordinates of the front-end processing equipment, the connection status indicator light of the sling positioning sensor, the motor driver control link identifier and the load parameters of the digital input port and the analog output port, and abnormal connection points are marked in the device topology diagram. For example, when the communication status of the digital input port is abnormal, a red alarm mark is marked at the connection status indicator light of the sling positioning sensor; when the communication status of the analog output port is abnormal, a yellow alarm mark is marked at the motor driver control link identifier.

[0027] Install the shared backend server cluster rack in the designated area of ​​the remote control center, and use standard rack mounting accessories to fix each shared backend server cluster unit to the preset position of the rack. The preset position of the rack must meet the equipment heat dissipation spacing requirements.

[0028] To further clarify, the equipment heat dissipation clearance requirement refers to the minimum physical heat dissipation space requirement that the shared backend server cluster unit must meet when installed in a rack, including horizontal spacing, vertical spacing, and front-to-back spacing; The horizontal spacing is to prevent short circuit of air inlet / exhaust ports of adjacent equipment, the vertical spacing is to keep the hot air rising channel unobstructed, and the front-to-back spacing is to ensure the efficiency of cold air intake and the backflow-free discharge of hot air.

[0029] Arrange the Profibus-DP coupler mounting bracket and install the Profibus-DP coupler unit adjacent to the shared back-end server cluster rack; Lay network connection cables between the front-end processing equipment of multiple port machinery. Connect one end of the cable to the DP interface of the Profibus-DP coupler unit and the other end to the DP communication port of each port machinery front-end processing equipment. Use a dedicated network tester to detect the cable physical layer parameters and record the network signal attenuation value. Configure the communication parameters of the Profibus-DP coupler unit, set the baud rate, node address, and master-slave mode of each DP interface. The parameter settings must fully match the DP communication parameters of the front-end processing device (embedded PLC). Start the DP network communication protocol handshake process and activate the network scanning function of the shared back-end server cluster unit. The shared back-end server cluster unit polls all connected front-end processing device nodes through the Profibus-DP coupler to obtain a list of node information including device serial number, firmware version, and real-time communication status. Analyze the network signal attenuation value and node information list, and set the signal attenuation threshold based on the baud rate. For nodes whose network signal attenuation value exceeds the signal attenuation threshold, mark the communication quality warning icon in the node information list; for nodes with abnormal communication status, mark the node fault icon, and generate a network status report including the physical connection status of all DP interfaces, the serial number and firmware version of each node device, the real-time communication quality rating (excellent / warning / fault) and the network topology path.

[0030] Deploy the analysis server operating system on the virtual machine instance provided by the cloud service provider, configure the analysis server network interface, set firewall rules to allow data transmission ports to receive data from the shared backend server cluster in the remote control center, and select a high-availability virtual machine instance equipped with redundant power supplies and dual network cards. Install database management software on the analysis server operating system and create the table structure of the initial device database. The table fields include three main fields: device model, network address, and communication status. Establish a VPN tunnel between the analysis server and the remote control center, receive network status reports, extract the device serial number field of each node in the network status report, query the device model code comparison table, and map the first six digits of the device serial number to the device model string; read the network topology path diagram in the network status report, parse the network address information of each node, and convert the real-time communication quality rating. Convert the excellent / warning / failure ratings in the network status report to the enumeration value of the real-time communication quality rating (0 represents excellent, 1 represents warning, and 2 represents failure); The device model string, the parsed network address and the converted real-time communication quality rating enumeration value are written into the initial device database as records, a database index file is generated, and a B+ tree index structure is established in the initial device database for the three main fields of device model, network address and communication status.

[0031] Connect the computer's host screen display device to the display output port of the remote station PLC, install the touch screen display device in the designated area of ​​the console, and establish a physical connection between the touch screen and the extended display interface of the remote station PLC via an HDMI video cable; set the display mirror parameters in the remote station PLC display driver so that the device status parameters of the initial device database are simultaneously output to the computer's host screen display device and the touch screen display device; Lay the physical button panel control cable, connect the two ends of the cable to the output port of the physical button panel and the digital input port of the Profibus-DP coupler respectively, connect the operating handle data cable to the analog input port of the Profibus-DP coupler, and the remote station PLC sends test instructions to the physical button panel and operating handle, receives response signals from the physical button panel and operating handle, and outputs a connection status report of the physical button panel and operating handle; Secure the voice announcer to the side elevation of the console and connect the voice announcer audio input cable to the audio output interface of the remote station PLC. Install the monitoring system camera on the support structure of the port machinery operation area. Adjust the monitoring system camera's pitch angle to cover the spreader's operating range. Lay the monitoring system video transmission optical cable to the remote control center's distribution frame. Check the cable continuity between the physical button panel and the Profibus-DP coupler, the signal voltage range between the operating handle and the Profibus-DP coupler, the voice announcer impedance matching, and the monitoring system video transmission optical cable attenuation. Generate a line connection test result. When the physical button panel cable continuity is normal, the operating handle signal voltage meets the basic electrical continuity logic (short circuit / open circuit detection), the voice announcer impedance is reasonable, and the monitoring system video transmission optical cable attenuation is less than the optical cable attenuation threshold, the line connection test is considered qualified. Status identification signals including voice announcer ready, monitoring system ready, and operating panel ready are generated and transmitted to the input register of the communication network functional unit.

[0032] To further clarify, the fiber optic cable attenuation threshold is set based on the fiber optic cable type (single-mode / multi-mode) and the transmission wavelength.

[0033] S2, based on the status identification signal, builds an all-optical link and generates a fiber path topology, transmits the spreader control instructions and path instructions in layers, establishes a heartbeat detection mechanism and triggers a status confirmation signal.

[0034] The status identification signal stored in the input register of the communication network functional unit is read. The status identification signal includes three Boolean value fields: the voice announcer ready status identification, the monitoring system ready status identification, and the operation panel ready status identification. The logic values ​​of the three status identification signals are detected. When the voice announcer ready status identification is true, the monitoring system ready status identification is true, and the operation panel ready status identification is true, an all-optical link laying start instruction is generated. When any of the three status identification signals is false, the status identification detection process is executed cyclically until the three status identifications are simultaneously true. Specifically, When the voice announcer ready state flag is false, loop detection and output a null value; When the monitoring system ready status flag is false, loop detection and output a null value; When the ready status flag of the operation panel is false, the loop is checked and a null value is output; When all status flags are true, the loop is exited and the full optical link laying start instruction is output; When the full-optical link laying start command is received, the optical transmission port position of the OLT device in the remote control center and the input port position of the splitter device are located, and a single-mode optical fiber line is laid. An LC / PC connector is installed on one end of the optical fiber cable and inserted into the optical transmission port of the OLT device; an SC / APC connector is installed on the other end of the optical fiber cable and inserted into the input port of the splitter; the optical time domain reflectometer test mode is started, the test wavelength, pulse width and measurement range are set, and a test light pulse is stimulated to enter the optical fiber line. The reflection event table displayed by the optical time domain reflectometer is recorded, and the fusion point data containing the distance, loss value and reflection type fields in the reflection event table are extracted. The loss measurement value of the fusion point at the end position of the OLT device is recorded, and a fiber fusion point loss data report containing the fusion point sequence number, distance value and loss value is generated.

[0035] Based on the splice loss measurement values ​​in the fiber splice loss data report, splice points with loss values ​​less than the splice loss limit are selected as qualified nodes, and a qualified node list is output, where the splice loss limit is determined based on the total loss of the optical link; the qualified node list is used to locate the output port position of the optical splitter device and the optical receiving port position of the ONU device on the port machinery side, and the single-mode optical fiber line is laid: the end with SC / APC connector is inserted into the located splitter output port, and the end with SC / PC connector is inserted into the located ONU device optical receiving port; the Profibus optical switch circuit board is installed in the ONU device circuit board slot, and the circuit board power bus is connected to the ONU DC power supply module, and the circuit board power supply status is output; the Profibus optical switch circuit board self-test program is activated according to the circuit board power supply status: the test Profibus-DP signal is input to the circuit board electrical interface, the optical interface output signal waveform is detected, and a self-test report containing signal eye diagram quality parameters is generated; Integrate the self-test report and fiber splice loss data report into a comprehensive fiber connection data set. Import the remote control center building plan and port geographic information map into the CAD drawing software. Mark the OLT device location coordinates and splitter location coordinates. Draw a blue line segment to connect the optical fiber path from the splitter to the OLT device, and output a primary topology draft. Mark the ONU device location coordinates on the primary topology draft, and draw green lines to connect the optical fiber paths from the splitter output port to each ONU device to form an intermediate topology diagram. Mark the splice location coordinates on the fiber path segments in the intermediate topology diagram: add a red exclamation point icon when the splice loss value is greater than or equal to the splice loss limit, and add a green check mark icon when the splice loss value is less than the splice loss limit, to generate a marked fiber path topology diagram. See also Figure 3 , parse the ONU device location coordinates and splitter connection path information in the annotated fiber path topology diagram, log in to the OLT device management interface and enter the wavelength division multiplexing module configuration menu: select the channel binding function to create a λ1 dedicated channel, set the channel attribute to exclusive mode and bind the spreader control command data transmission; create a λ2 shared channel in the same configuration menu, set the channel attribute to shared mode and bind the path command data transmission; then access the ONU device management terminal on each port machine side, and set the center wavelength of filter 1 and filter 2 in the optical receiving filter wavelength configuration interface; After configuration is complete, a test data packet containing a spreader control command is sent to the λ1 dedicated channel to test the received signal strength of filter 1 of the ONU device. Simultaneously, a test data packet containing a path command is sent to the λ2 shared channel to test the received signal strength of filter 2 of the ONU device. Finally, a wavelength configuration verification report is generated that records the data transmission packet loss rate of the λ1 dedicated channel, the data transmission packet loss rate of the λ2 shared channel, and the filter center wavelength offset. After confirming that the packet loss rates of all wavelength channels in the wavelength configuration verification report have converged to a stable state, activate the λ2 shared channel time division multiplexing mechanism in the OLT device TDMA configuration interface, set the time slot frame period, and create a time slot allocation table: the time slot number corresponds to the physical address of each port machinery ONU device, the width of each time slot is fixed, and the time slot allocation order is strictly arranged in ascending order according to the ONU device coordinates; The time slot allocation table is sent to the time synchronization unit of each ONU device, and the IEEE 1588v2 precision time protocol is used to calibrate the clock offset between the OLT and ONU devices. After the calibration is completed, a test data packet is sent to the ONU device numbered 1 in time slot 1, and a test data packet is sent to the ONU device numbered 16 in time slot 16 to detect the data packet reception delay of each ONU device. A wavelength allocation table is generated, which includes the λ1 dedicated channel, the λ2 shared channel, the time slot width, and the time slot allocation sequence. See also Figure 4, extract the λ1 dedicated channel parameter (center wavelength) in the wavelength allocation table as the heartbeat data packet transmission channel; configure the front-end PLC timer: set the periodic trigger signal, and when triggered, generate a heartbeat data packet with a fixed byte length containing the PLC device serial number and the current timestamp; The heartbeat data packet is transmitted through the ONU device's dedicated λ1 channel. The heartbeat data packet is routed internally to filter 1, where it undergoes electro-optical conversion and is then injected into the optical fiber line. The OLT device's wavelength division multiplexing module captures the heartbeat data packet on the λ1 dedicated channel, parses the PLC device serial number contained in the data packet, and records the heartbeat data packet's reception timestamp. The heartbeat data packet and reception timestamp are then forwarded to the port of the shared backend server cluster, forming a heartbeat record data set. The shared backend server cluster receives the heartbeat record data set, stores the heartbeat packet reception timestamps by PLC device serial number, records the time interval between consecutive heartbeat packets for the same PLC device serial number, and sets the time interval to 15ms: If the time interval is ≤15ms, update the heartbeat packet receiving timestamp and output the normal status code 0; If the time interval is greater than 15ms, a timeout event is recorded and alarm code 1 is output; Further explanation: the timeout event content includes the PLC device serial number, the time when the timeout occurred, and the time interval value.

[0036] When the same PLC device serial number outputs alarm code 1 three times in a row, the console's sound and light alarm signal is triggered: Send a control authority switching command to the local PLC corresponding to the PLC device serial number that outputs alarm code 1 three times in a row, switching to local manual control mode; Activate the console sound and light alarm: set the buzzer continuous tone output frequency and the red indicator light flashing frequency (for example, on 500ms / off 500ms); Generate a timeout event report containing the time, duration, and execution status of the timeout event according to the trigger signal of the sound and light alarm on the operation console; Parse the optical fiber path length values ​​from the OLT device to each ONU device in the annotated optical fiber path topology diagram as optical fiber distance parameters to form an optical fiber distance parameter set; obtain the current transmission data packet size parameter set; It is further explained that the current transmission data packet size parameter set includes a fixed byte length of a heartbeat data packet, a byte length range of a spreader control instruction data packet, and a byte length range of a path instruction data packet.

[0037] Based on the fiber distance parameter set and the transmission data packet size parameter set, the actual transmission delay value is calculated as follows: ; in, is the actual transmission delay value, is the fiber distance, is the optical fiber delay coefficient, is the packet size parameter, is the data packet transmission coefficient, To fix the processing delay; Connect the sound and light alarm trigger signal to the enable control port of the path optimization instruction and output a level status signal (high level when triggered, low level when not triggered). When the intelligent control port detects a high-level signal, it immediately writes the actual transmission delay value into the path optimization instruction delay compensation register, adjusts the safety response time window based on the delay compensation register, terminates the current calculation task of the path optimization instruction, clears all data in the path optimization instruction output buffer area, sets the path optimization instruction status register to a safe standby state, and outputs a safe standby state confirmation signal. To further explain, enable is the on-off switch of the control signal. When the enable signal is activated, some functions are allowed to run; otherwise, they are forcibly disabled.

[0038] During the period when the safety standby state confirmation signal is valid, the trigger level status signal value of the sound and light alarm is continuously monitored, and all new path calculation request instructions are rejected. At the same time, the status query interval is set to twice the actual transmission delay value to send query instructions to the local PLC; when the enable control port detects that the level status signal returns to a low level, the path optimization instruction status register is set to the run-ready state, the actual transmission delay value of the delay compensation register is read as the time offset of the path calculation, the path calculation task data at the interruption time is reloaded and time offset compensation is applied to restore the normal output function of the path optimization instruction data.

[0039] S3 receives the status confirmation signal and wavelength allocation table, obtains the lidar point cloud data through a dedicated channel to perform spreader obstacle avoidance correction, generates a global path sequence through a shared channel, and outputs the spreader perspective image at the same time.

[0040] The wavelength allocation table parameters, actual transmission delay value data, and path optimization instruction status register value are written into the input data buffer of the front-end PLC. The front-end PLC configures the center wavelength of the lidar data receiving filter based on the λ1 dedicated channel wavelength in the wavelength allocation table parameters. The original point cloud data sent by the lidar is received through the λ1 dedicated channel, and the three-dimensional coordinates of the target container center output by the spreader positioning sensor in real time are synchronously read. The actual transmission delay value is extracted from the input data buffer. Based on the difference between the timestamp of the received original point cloud data and the actual transmission delay value, the corrected timestamp of the original point cloud data is obtained; the coordinates of each point in the original point cloud data are bound to the corrected timestamp to generate a time-calibrated point cloud dataset; After aligning the timestamps of the calibrated point cloud dataset with the 3D coordinates of the target container center, the spreader obstacle avoidance correction is performed and the spreader posture adjustment is calculated. The expression is: ; in, It is the adjustment value of the spreader's posture, used to control the spreader's pitch and yaw angles. is the obstacle avoidance sensitivity coefficient, The bigger it is, the more sensitive the obstacle avoidance response will be. The first point cloud data after calibration The obstacle coordinates, is the three-dimensional coordinate of the center of the target container, is a smoothing factor to prevent the denominator from being zero, The smaller it is, the more sensitive it is to close obstacles. is the number of obstacles, is the Euclidean distance from the obstacle to the center of the target container; When the path optimization instruction status register value indicates the run-ready state, the posture adjustment value is converted into a standard analog output voltage, and the expression is: ; in, It is a standard analog output voltage, used to drive the control voltage of the spreader actuator. is the zero position bias voltage, that is, when Keep the spreader stationary, is the voltage conversion gain coefficient, which controls the sensitivity of voltage conversion; The standard analog output voltage is output to the spreader driver through the analog output port of the front-end PLC. After receiving the analog output voltage, the spreader driver performs posture adjustment actions. When the path optimization instruction status register value indicates a safe standby state, the spreader posture adjustment value is written into the path optimization instruction ring buffer, and the path optimization instruction status register value changes are continuously detected. When the register value is detected to be in the run-ready state, the latest spreader posture adjustment value in the buffer is read and voltage conversion output is performed; The backend shared server continuously receives path calculation request packets through the λ2 shared channel and extracts the target endpoint coordinates, real-time motor power, and continuous operation time from the path calculation request packets. Simultaneously, it reads the real-time target container center 3D coordinates provided by the spreader positioning sensor as the current position and compensates the current position using the actual transmission delay value to obtain the compensated starting point coordinates, which are expressed as follows: ; in, is the starting point coordinate after delay compensation, indicating the exact starting position of the path planning. is the real-time position coordinate of the spreader, is the instantaneous velocity vector of the spreader, which represents the direction and magnitude of the spreader's motion state; Based on the delay-compensated starting point, target end point, real-time motor power, and continuous operation time, the optimal path sequence is obtained through the path cost function, which is expressed as: ; in, For the current node The comprehensive cost is the core basis for path selection. The smaller the value, the higher the priority. From the starting point to the current node The actual cost, is the weight adjustment factor of the heuristic function, For the current node The estimated cost of the heuristic function to the end point is used to guide the search direction, is the amplitude coefficient of time attenuation, which is used to control the attenuation intensity of the energy consumption factor over time. is the time decay rate factor, which determines the energy consumption decay rate. is the continuous operation time, that is, the continuous running time of the motor. is the basic energy consumption ratio, is the real-time motor power, is the power normalization factor, which is used to eliminate the influence of power dimension; By selecting the adjacent nodes with the smallest comprehensive cost node by node in the path cost function, the optimal path sequence is formed from the starting point to the end point.

[0041] Further explanation, starting point to node The actual cost is to start from the starting point after delay compensation and accumulate the distance along the planned path step by step. The expression is: ; in, is the path node number, From the starting point to the current node The total number of segment paths, For path Node coordinates, For path Node coordinates, is the Euclidean distance between adjacent nodes; Current node coordinates The estimated cost of the heuristic function to the target endpoint is expressed as: ; in, is the target end point coordinate, The target's movement speed (direction + size).

[0042] The compensated starting point coordinates are input into the surveillance camera's hoist tracking algorithm to automatically calculate the pan-tilt head's horizontal rotation angle and pitch angle. The surveillance camera's pan-tilt head is controlled to perform mechanical movement, and the horizontal rotation motor is adjusted to the horizontal rotation angle and the pitch motor to the pitch angle, so that the compensated starting point coordinates are precisely located at the center of the surveillance screen. At the same time, the current timestamp is obtained, and the sensor data values ​​at the historical moment are extracted from the surveillance data buffer. The compensated starting point coordinates and the sensor data values ​​at the historical moment are converted into OSD strings, which are superimposed and displayed in the lower right corner of the surveillance screen.

[0043] To further illustrate, the sensor data values ​​at a historical moment include the real-time coordinates of the spreader positioning sensor, the wind speed of the meteorological sensor, and the load weight of the spreader weighing sensor.

[0044] S4 calculates the collision risk factor in real time. When the collision risk safety threshold is exceeded, the spreader action is suspended and a voice alarm is sent. The remote control room is dynamically bound and the operation control authority is output.

[0045] The wind speed impact factor is calculated using the wind speed value in the sensor data value at the historical moment. The expression is: ; in, is the wind speed impact factor, which represents the correction coefficient of wind speed to path spacing. is the base coefficient, which is used as the base constant of the calculation formula and has a fixed value of 1.0. The upper limit of wind speed influence is used to limit the maximum correction range, with a fixed value of 0.15. is the wind speed, is the wind speed normalization coefficient, which converts the wind speed into a proportional coefficient with a fixed value of 20; Multiply the wind speed impact factor by the original path spacing of the optimal path sequence to obtain the optimized path sequence including the updated path point spacing; Use optimized path sequences with updated path spacing and load weights Adjust the maximum speed of the spreader , for example, when hour, ,when and hour, ,when hour, ; The front-end PLC reads the laser radar point cloud data set (including obstacle points) and the real-time speed vector of the spreader (less than the maximum speed of the spreader). ); The collision risk factor is calculated using the delay-compensated starting point coordinates, wind speed, point cloud dataset, and real-time velocity vector. The expression is: ; in, The collision risk factor quantifies the collision risk between the spreader and the obstacle. The larger the value, the higher the risk. is the starting point coordinate after delay compensation, is the real-time velocity vector of the spreader, is the basic risk factor, is the wind speed influence coefficient; Setting collision risk safety threshold based on collision risk factor , perform collision risk determination, as follows: when When , the current path sequence is maintained; when When , the current path sequence execution is interrupted and an emergency response is triggered; Upon receiving a collision risk determination triggering an emergency response, the optimal path sequence is immediately interrupted and a voice warning is sent via the dedicated λ1 channel. The voice content clearly includes the load weight, current wind speed, and minimum obstacle distance. The collision risk factor, load weight, wind speed, and the node location at the time of the current path sequence interruption are then packaged and transmitted to a shared backend server. The shared backend server uses the received wind speed to correct the fiber distance and obtains the fiber distance after wind resistance correction. The expression is: ; in, is the fiber distance after windage correction, is the wind resistance correction factor; Based on the fiber distance corrected for wind resistance, combined with the real-time CPU load rate and network quality level of each remote control room, the binding priority value of each remote control room is calculated. The expression is: ; in, For the The binding priority of each remote control room determines the numerical index of the optimal remote control room. For the The CPU load rate of each remote control room, For the The network quality level of each remote control room is used to evaluate the network transmission performance. The level range is 1-10 (the higher the level, the better the quality). is the distance weight coefficient, is the distance normalization coefficient; The remote control room with the smallest priority value is selected as the binding target, and the unique identification ID of the bound remote control room is output; the load weight is transmitted to the bound remote control room to set the upper limit of the operating force, and the wind speed is synchronously transmitted to enable the wind-proof operation strategy; the operation control authority of all non-bound remote control rooms over the optimal path sequence is released.

[0046] The maximum acceleration parameters are set according to the load weight. The path is replanned based on the latest obstacle distribution and load weight, and the new optimal path sequence is output to the front-end PLC control system. The operation is resumed from the interruption point of the original optimal path sequence.

[0047] S5, based on the operation control authority and the new optimal path sequence, builds a digital twin and generates a scheduling report through the LSTM model.

[0048] Execute operations and create a new optimal path sequence based on the remote control room's operational control authority, and initialize the three-dimensional spatial coordinate system framework of the port machinery's dynamic digital twin. Continuously acquire the execution status data of the current optimal path sequence via the fieldbus, including dynamic parameters such as spreader position feedback signals, velocity vector changes, and trajectory offsets, and synchronously record the acquisition timestamp of each path node. Connect to the data transmission interface of the port weather station, receive meteorological data in real time, extract wind speed, wind direction, temperature and humidity from the data stream, and generate a formatted meteorological data set after adding the collection timestamp; Read the energy consumption pulse signal output by the port machinery power metering device, convert it into energy consumption value, and bind the energy consumption value with the corresponding time stamp to form a time-stamped energy consumption data sequence; Integrate three data sources: execution status data, formatted meteorological data sets, and time-stamped energy consumption data series, align data points along a unified time axis, and generate a real-time operation data set containing location coordinates, motion status, environmental parameters, and energy consumption indicators; The real-time running data set was divided into training, validation, and test sets by timestamp. An LSTM model prediction network with a three-branch input structure was constructed: the first input branch received a historical 24-hour energy consumption value sequence, the second input branch received a sliding average meteorological feature vector of historical temperature, humidity, wind speed, and wind direction, and the third input branch received a historical power average scalar. The hidden layer was configured with two layers of 128-neuron LSTM units and a set dropout rate. The output layer generated a six-hour energy consumption forecast through a fully connected layer. The energy consumption sequence, meteorological feature vector, and average power of the training set are simultaneously input into the network for forward propagation to calculate the predicted value. The predicted value is compared with the true value using the mean square error loss function, and the weight is updated through backpropagation using the Adam optimizer (learning rate 0.001). Training is stopped when the loss of the validation set decreases by less than 1% for three consecutive times. After the prediction error is verified to have converged and stabilized on the test set, the trained LSTM model prediction network is obtained. The latest continuous energy consumption sequence is extracted from the real-time operation data set as the first input of the trained LSTM model network. The meteorological feature vector generated by the formatted meteorological data set is read as the second input. The real-time power value of the motor driver is collected and the arithmetic mean scalar is calculated as the third input. The three are simultaneously input into the trained LSTM model to perform forward propagation and output the energy consumption forecast value for the future period. The energy consumption forecast value for the future period is analyzed based on the time series characteristics, discretized into an energy consumption point sequence at an hourly granularity, and the points are connected to form a continuous curve, which is marked as the energy consumption distribution curve for the future operation cycle. Extract the peak and valley moments in the energy consumption distribution curve, and simultaneously analyze the temperature parameter time series in the meteorological data to identify periods when the temperature exceeds high temperature. According to the overlapping status of the peak period and the high-temperature period of the energy consumption distribution curve, the operation suggestion rule base is matched: when the energy consumption peak coincides with the high-temperature period, a text instruction for reducing the load in the high-temperature period is generated; when the energy consumption valley coincides with the low-temperature period, a text instruction for increasing the load in the low-temperature period is generated; when there is no overlapping period, a default suggestion is output; the operation suggestion text instruction is formatted, and a time range description and percentage adjustment parameters are added to form a scheduling report.

[0049] This embodiment also provides a port machinery automation remote control system, including: The networking module, the front-end processing equipment connects to the spreader positioning sensor and motor driver, generates the equipment topology diagram, interconnects multiple port machinery PLC networks through Profibus-DP couplers and outputs network status reports, and configures dual redundant operation console interfaces and outputs status identification signals; The optical communication module builds an all-optical link and generates a fiber path topology based on the status identification signal, transmits the spreader control instructions and path instructions in layers, establishes a heartbeat detection mechanism, and triggers a status confirmation signal; The obstacle avoidance navigation module receives the status confirmation signal and wavelength allocation table, obtains the lidar point cloud data through the λ1 dedicated channel to perform spreader obstacle avoidance correction, generates a global path sequence through the λ2 shared channel, and outputs the spreader perspective image at the same time; The emergency response module calculates the collision risk factor in real time. When the collision risk safety threshold is exceeded, the spreader action is suspended and a voice alarm is sent. The module is dynamically bound to the remote control room and outputs the operation control authority. The twin scheduling module builds a digital twin based on operation control authority and the new optimal path sequence, and generates a scheduling report through the LSTM model.

[0050] This embodiment also provides a computer device, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the port machinery automation remote control method proposed in the above embodiment.

[0051] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0052] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the port machinery automation remote control method proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0053] In summary, the present invention eliminates command blocking and reduces obstacle avoidance response delay by constructing a dual physical isolation layer of dedicated channels and shared channels; the heartbeat detection mechanism triggers a three-level alarm to ensure the reliability of the control link; the wind speed and load inertia parameters are integrated based on the collision factor to reduce the misjudgment rate; the energy consumption distribution curve is matched with the temperature period to generate load adjustment instructions, thereby improving the overall energy efficiency.

[0054] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A port machinery automation remote control method, characterized by: include: The front-end processing equipment connects to the spreader positioning sensor and motor driver, generates the equipment topology diagram, interconnects multiple port machinery PLC networks through Profibus-DP couplers and outputs network status reports. It also configures a dual-redundant operation console interface and outputs status identification signals. Based on the status identification signal, an all-optical link is constructed and a fiber path topology is generated. The spreader control instructions and path instructions are transmitted in layers, and a heartbeat detection mechanism is established to trigger a status confirmation signal. Receive status confirmation signals and wavelength allocation tables, obtain LiDAR point cloud data through dedicated channels to perform spreader obstacle avoidance corrections, generate a global path sequence through shared channels, and simultaneously output the spreader's perspective image; Calculate the collision risk factor in real time. When the collision risk safety threshold is exceeded, the spreader action is suspended and a voice alarm is sent. The remote control room is dynamically bound and the operation control authority is output. Based on the operation control authority and the new optimal path sequence, a digital twin is constructed, and a scheduling report is generated through the LSTM model.

2. The port machinery automation remote control method according to claim 1, characterized in that: The output state identification signal comprises the following steps: Laying network connection cables between the front-end processing equipment of multiple port machinery and recording network signal attenuation values; Configure the communication parameters of the Profibus-DP coupler unit and obtain the node information list; Analyze network signal attenuation values ​​and node information lists to generate network status reports; Extract the device serial number field and network topology path diagram of each node in the network status report and write them into the initial device database according to the record; The device status parameters of the initial device database are simultaneously output to the computer host screen display device and the touch screen display device to generate a status identification signal.

3. The port machinery automation remote control method according to claim 1, characterized in that: The hierarchical transmission of the spreader control instructions and the path instructions comprises the following steps: Create dedicated channel binding spreader control instructions and shared channel binding path instructions; Send a test data packet with a spreader control instruction to the dedicated channel to detect the received signal strength of filter 1 of the ONU device. At the same time, send a test data packet with a path instruction to the shared channel to detect the received signal strength of filter 2 of the ONU device and generate a wavelength configuration verification report. After confirming that the packet loss rates of all wavelength channels in the wavelength configuration verification report have converged to a stable level, activate the shared channel time division multiplexing mechanism, set the timeslot frame period, and create the timeslot allocation table; Send the time slot allocation table to the time synchronization unit of each ONU device to calibrate the clock deviation between OLT and ONU devices; After calibration is completed, a test data packet is sent to the ONU device to detect the data packet reception delay of each ONU device and generate a wavelength allocation table.

4. The port machinery automation remote control method according to claim 1, characterized in that: The establishment of the heartbeat detection mechanism and triggering of the status confirmation signal comprises the following steps: Extract the dedicated channel parameters in the wavelength allocation table as the heartbeat data packet transmission channel and configure the front-end PLC timer; Transmit the heartbeat data packet through the dedicated channel of the ONU device to form a heartbeat record data set; The shared backend server cluster receives the heartbeat record data set, stores and records the time intervals of continuous heartbeat packets in groups, triggers the sound and light alarm signal of the operation console, and generates a status confirmation signal.

5. The port machinery automation remote control method according to claim 1, characterized in that: The execution of the spreader obstacle avoidance correction comprises the following steps: Receive original point cloud data, 3D coordinates of the target container center, and actual transmission delay value; Based on the difference between the timestamp of the original point cloud data and the actual transmission delay value, the original point cloud data is calibrated and the timestamp of the three-dimensional coordinates of the target container center is aligned. Then, the spreader obstacle avoidance correction is performed and the spreader posture adjustment amount is calculated. When the status confirmation signal is in the ready state, the posture adjustment amount is converted into a standard analog output voltage and the posture adjustment action is executed; When the status confirmation signal is in the safe standby state, the sling posture adjustment amount is written into the path optimization instruction ring buffer for continuous detection.

6. The port machinery automation remote control method according to claim 1, characterized in that: The output operation control authority includes the following steps: The back-end shared server continuously receives path calculation request data packets through the shared channel, extracts the target endpoint coordinates, real-time motor power, and continuous operation time, and simultaneously reads the real-time 3D coordinates of the target container center as the current position; Apply the actual transmission delay value to compensate the current position and obtain the compensated starting point coordinates; Based on the compensated starting point coordinates, target end point coordinates, real-time motor power and continuous operation time, the optimal path sequence is obtained through the path cost function; Calculate the wind speed impact factor and multiply it by the original path spacing of the optimal path sequence to obtain the optimized path sequence; Adjustment of spreader maximum speed using optimized path sequence and load weight; Calculate the collision risk factor, make collision risk assessments, and correct the fiber distance; Based on the fiber distance corrected for wind resistance, the binding priority value of each remote control room is calculated in combination with the real-time CPU load rate and network quality level of each remote control room. The remote control room with the smallest priority value is selected as the binding target, and the operation control authority is output.

7. The port machinery automation remote control method according to claim 1, characterized in that: Generating the scheduling report comprises the following steps: Execute operations and new optimal path sequences based on the remote control room's operational control authority, and initialize the three-dimensional spatial coordinate system framework of the port machinery dynamics digital twin; Obtain the execution status data, meteorological data, and energy consumption pulse signal of the current optimal path sequence, input them into the LSTM model, output the energy consumption prediction value, and generate the energy consumption distribution curve; Extract the peak and valley moments of the energy consumption distribution curve, synchronously analyze the temperature parameter time series in the meteorological data, and generate a scheduling report.

8. A port machinery automation remote control system based on the port machinery automation remote control method according to any one of claims 1 to 7, characterized in that: include: The networking module, the front-end processing equipment connects to the spreader positioning sensor and motor driver, generates the equipment topology diagram, interconnects multiple port machinery PLC networks through Profibus-DP couplers and outputs network status reports, and configures dual redundant operation console interfaces and outputs status identification signals; The optical communication module builds an all-optical link and generates a fiber path topology based on the status identification signal, transmits the spreader control instructions and path instructions in layers, establishes a heartbeat detection mechanism, and triggers a status confirmation signal; The obstacle avoidance navigation module receives the status confirmation signal and wavelength allocation table, obtains the lidar point cloud data through the λ1 dedicated channel to perform spreader obstacle avoidance correction, generates a global path sequence through the λ2 shared channel, and outputs the spreader perspective image at the same time; The emergency response module calculates the collision risk factor in real time. When the collision risk safety threshold is exceeded, the spreader action is suspended and a voice alarm is sent. The module is dynamically bound to the remote control room and outputs the operation control authority. The twin scheduling module builds a digital twin based on operation control authority and the new optimal path sequence, and generates a scheduling report through the LSTM model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the port machinery automation remote control method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the port machinery automation remote control method according to any one of claims 1 to 7 are implemented.

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