Portal crane and gantry crane anti-collision system based on analytical method

Abstract

The invention provides a portal crane and gantry crane anti-collision system based on an analytical method. An absolute value encoder, an RFID setting device, a rotation angle sensor and a variable amplitude angle sensor are used for monitoring the position and angle of a crane. The absolute value encoder comprises a cart encoder and a trolley encoder and is used for acquiring the position information of the cart and the trolley of the crane. The RFID device determines the position of the crane on the track. Sensor data are transmitted through the PLC communication module and processed by the collision detection and early warning control module to generate real-time coordinate data and evaluate the collision risk, and finally an early warning signal is output to the control system to achieve the anti-collision function.

Description

Technical Field

[0001] The present invention relates to the field of safety monitoring of lifting machinery, and more specifically, the present invention relates to an anti-collision system for gantry and portal cranes based on an analytical method. Background Art

[0002] Lifting machinery plays an important role in ports, construction sites, and industrial production, and is used for hoisting and transporting heavy objects. However, due to the complex and changeable operating environment of lifting machinery, combined with possible misoperations by operators, there is a risk of collision during the operation of lifting machinery. Traditional anti-collision systems mostly rely on the experience and intuition of operators, lack real-time performance and accuracy, and are difficult to meet the growing safety requirements.

[0003] In the existing technology, although some lifting machinery is equipped with basic safety devices, such as limit switches and emergency stop buttons, these devices usually only come into play when a collision is about to occur or has already occurred, and cannot give early warnings and prevent collisions. In addition, some systems use simple sensors for distance detection, but these sensors can often only provide limited information, such as distance and speed, and cannot provide comprehensive data on the motion state of lifting machinery, such as acceleration and variable acceleration, thus limiting the accuracy and timeliness of collision warnings.

[0004] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the existing technology: The existing anti-collision system lacks comprehensive monitoring and analysis of the motion state of lifting machinery, resulting in inaccurate generation of warning signals and inability to effectively prevent potential collision risks; at the same time, the existing system has problems with low efficiency in data processing and communication, and cannot achieve real-time and fast data processing and response, thus affecting the overall performance and reliability of the anti-collision system. Summary of the Invention

[0005] The present invention provides an anti-collision system for gantry and portal cranes based on an analytical method, including: Absolute encoders, RFID positioning devices, slewing angle sensors and luffing angle sensors. Among them, the absolute encoders include trolley encoders and crab encoders. The RFID positioning device is used to determine the position of the crane on the track. The slewing angle sensor is used to monitor the slewing angle of the portal crane. The luffing angle sensor is used to monitor the angle of the luffing mechanism. The trolley encoder is used to encode the running position of the trolley of the gantry crane to obtain trolley position information and transmit it to the PLC of the gantry crane. The PLC communicates with the PLC of the portal crane through a communication module, including a collision detection module and a warning control module. The collision detection module generates real-time coordinate data based on the received crane position information and angle information and stores it in the database. The warning control module generates a warning signal through collision risk assessment based on the real-time coordinate data and outputs it to the control system to control the operation of the crane.

[0006] Further, the PLC includes a data processing unit and a communication interface. The data processing unit is used to convert the signals of the encoders and sensors into digital signals and transmit them to the communication interface. The communication interface outputs the digital signals to the control system.

[0007] Further, the warning control module includes a warning signal generator and a control actuator. The warning signal generator receives the real-time coordinate data of the collision detection module, generates a warning signal through collision risk assessment. The control actuator receives the warning signal and outputs a control instruction to the actuator of the crane.

[0008] Further, the collision detection module receives the following data for generating real-time coordinate data: the position error of the crane, and the distance and speed of the track data sent by the upper computer. It includes the following steps: Correct the position error sent by the upper computer to obtain the corrected position. Segment the corrected position and distance by time interval. Construct a third-order polynomial model of the distance and position of each segment of data. Fit each segment of data to obtain speed, acceleration and jerk. Construct a three-level accumulator, and calculate the recurrence parameters of one clock cycle according to speed, acceleration and jerk. According to the recurrence parameters and the three-level accumulator, cascade to generate the acceleration, speed and position of any number of clock cycles.

[0009] Furthermore, the warning control module generates a warning signal based on the input real-time coordinate data and the evaluation result of the collision detection module, including: processing the real-time coordinate data to obtain a complex baseband signal; capturing and tracking the complex baseband signal through a fast Fourier transform and a phase-locked loop to obtain the frequency of the complex baseband signal; obtaining the warning signal frequency based on the complex baseband signal frequency and the Doppler frequency in the evaluation result of the collision detection module, and generating a warning signal based on the warning signal frequency.

[0010] Furthermore, a third-order polynomial model of distance and location is constructed by the following formula: in, Represents the initial distance of each segment of data, Indicates the initial time of each data segment, Indicates the speed of each segment of data, Represents the acceleration of each segment of data, Indicates the variable acceleration of each segment of data, Represents any time of each piece of data, Indicates the period of data sent by the host computer.

[0011] Furthermore, the step size and output of each stage of the three-stage accumulator are obtained by: The step length of each stage accumulator in one clock cycle is calculated in turn according to the recursive parameters of each stage accumulator in one clock cycle and the output of the previous stage accumulator; Each stage of the accumulator accumulates the same number of clock cycles according to its own step size, calculates the output of each stage of the accumulator, and passes it to the next stage of the accumulator.

[0012] Furthermore, the recursive parameters of each stage accumulator in one clock cycle include: obtaining the recursive parameters of the variable acceleration of the first stage accumulator in one clock cycle, the recursive parameters of the acceleration of the second stage accumulator in one clock cycle, and the recursive parameters of the speed of the third stage accumulator in one clock cycle according to the speed, acceleration and variable acceleration of each segment of data.

[0013] Furthermore, the recursive parameters of one clock cycle and the three-stage accumulator are cascaded to generate the acceleration, velocity and position of any number of clock cycles, including: The recursive parameter of the variable acceleration of one clock cycle is used as the step length of one clock cycle of the first-stage accumulator. After accumulating any number of clock cycles according to the step length, the acceleration output by the first-stage accumulator is obtained. The recursive parameter of the acceleration of one clock cycle is added to the output of the first-stage accumulator as the step length of one clock cycle of the second-stage accumulator. After accumulating the same number of clock cycles according to the step length, the speed of the output of the second-stage accumulator is obtained. Add the recurrence parameter of the speed of one clock cycle to the output of the second - stage accumulator as the step size of the third - stage accumulator for one clock cycle. After accumulating the same number of clock cycles according to the step size, add it to the initial distance of each segment of track data to obtain the position output by the third - stage accumulator.

[0014] Furthermore, the PLC further includes a clock management unit for receiving an external clock signal and performing differential conversion, and then inputting it to the clock interface of the FPGA, the interfaces of the A / D module and the D / A module respectively through a clock drive circuit.

[0015] According to the above - mentioned embodiments of the present invention, it has at least the following beneficial effects: By adopting an absolute encoder, an RFID setting device, a slewing angle sensor and a luffing angle sensor, the anti - collision system for gantry and portal cranes of the present invention can accurately monitor the real - time position and motion state of the crane. The absolute encoder can provide the position information of the trolley and the gantry, while the RFID device ensures the accurate positioning of the crane on the track. The slewing angle sensor and the luffing angle sensor respectively monitor the slewing angle of the portal crane and the angle of the luffing mechanism. These information are transmitted to the PLC and communicate with the PLC of the portal crane through a communication module. The collision detection module and the early warning control module work together to realize the real - time processing of the position information and angle information of the crane and the collision risk assessment, so as to generate an early warning signal in time and output it to the control system, effectively controlling the operation of the crane and avoiding the occurrence of collision accidents.

[0016] In addition, the early warning control module of the present invention can accurately capture and track the frequency of the complex baseband signal by processing real - time coordinate data and using the fast Fourier transform and phase - locked loop technology, and then generate an accurate early warning signal according to the signal frequency and Doppler frequency. This way of generating the early warning signal can improve the accuracy and reliability of the early warning, enabling the crane operator to receive the early warning information in time and take corresponding preventive measures. At the same time, by constructing a three - stage accumulator and a third - order polynomial model, the system can accurately calculate the speed, acceleration and position of the crane at any time, which can further improve the prediction ability and response speed of the anti - collision system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] By reading the following detailed description with reference to the drawings, the above - mentioned and other objects, features and advantages of the exemplary embodiments of the present invention will become easy to understand. In the drawings, several embodiments of the present invention are shown in an exemplary rather than restrictive way, where: Figure 1 FIG. is a schematic structural diagram of an anti - collision system for gantry and portal cranes based on the analytical method provided by an embodiment of the present invention.

[0018] Reference Signs: 100. Gantry and portal crane anti-collision system based on the analytical method; 101. Absolute encoder; 102. RFID setting device; 103. Slewing angle sensor; 104. Luffing angle sensor. Detailed implementation manners

[0019] The principles and spirit of the present invention will be described below with reference to several exemplary implementation manners. It should be understood that these implementation manners are provided only to enable those skilled in the art to better understand and then implement the present invention, rather than limiting the scope of the present invention in any way. On the contrary, these implementation manners are provided to make the present invention more thorough and complete, and to be able to convey the scope of the present invention completely to those skilled in the art.

[0020] Those skilled in the art know that the implementation manners of the present invention can be realized as a system, a device, an equipment, a method or a computer program product. Therefore, the present invention can be specifically realized in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0021] It should be noted that the quantity of any element in the drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0022] Reference is made below to Figure 1 , Figure 1 which is a schematic structural diagram of a gantry and portal crane anti-collision system based on the analytical method provided in an embodiment of the present invention. As Figure 1 shown, a gantry and portal crane anti-collision system 100 based on the analytical method includes: An absolute encoder 101, an RFID setting device 102, a slewing angle sensor 103 and a luffing angle sensor 104. Among them, the absolute encoder 101 includes a trolley encoder and a hoist encoder. The RFID setting device 102 is used to determine the position of the crane on the track. The slewing angle sensor 103 is used to monitor the slewing angle of the portal crane. The luffing angle sensor 104 is used to monitor the angle of the luffing mechanism. The trolley encoder is used to encode the running position of the trolley of the gantry crane to obtain trolley position information and transmit it to the PLC of the gantry crane. The hoist encoder is used to encode the running position of the hoist of the gantry crane to obtain hoist position information and transmit it to the PLC of the gantry crane. The PLC communicates with the PLC of the portal crane through a communication module, including a collision detection module and a warning control module. The collision detection module generates real-time coordinate data according to the received crane position information and angle information, stores it in the database. The warning control module generates a warning signal through collision risk assessment according to the real-time coordinate data and outputs it to the control system to control the operation of the crane.

[0023] It should be noted that by integrating a variety of sensors and encoders, this system can achieve real-time monitoring of the position and motion state of the crane. The absolute encoder 101 is responsible for capturing the position information of the trolley and the crab, while the RFID positioning device 102 is used to determine the precise position of the crane on the track. The slewing angle sensor 103 and the luffing angle sensor 104 respectively monitor the slewing angle of the portal crane and the angle of the luffing mechanism, ensuring that the system can comprehensively grasp the operating state of the crane.

[0024] Specifically, the absolute encoder 101 includes a trolley encoder and a crab encoder, which are respectively installed on the trolley and crab components of the crane. Through high-precision coding technology, they output position information in real time. The RFID positioning device 102 updates the position of the crane on the track in real time through radio frequency identification technology. The sensors include the slewing angle sensor 103 and the luffing angle sensor 104, which are respectively installed on the slewing part and the luffing mechanism of the crane and can accurately capture the dynamic changes of the crane.

[0025] Preferably, the PLC internally integrates a data processing unit and a communication interface. The data processing unit is responsible for converting the analog signals of the encoders and sensors into digital signals and outputting them to the control system through the communication interface. The early warning control module is further refined into an early warning signal generator and a control actuator. The early warning signal generator conducts a collision risk assessment based on the real-time coordinate data provided by the collision detection module and generates an early warning signal.

[0026] More specifically, after receiving the early warning signal, the control actuator can quickly output a control instruction to the actuator of the crane to achieve effective control of the crane operation.

[0027] Furthermore, the system can also selectively add other types of sensors, such as a wind speed sensor or a load sensor, according to the needs of the actual application scenario to further improve the monitoring ability and early warning accuracy of the system.

[0028] In some embodiments, the PLC includes a data processing unit and a communication interface. The data processing unit is used to convert the signals of the encoders and sensors into digital signals and transmit them into the communication interface, and the communication interface outputs the digital signals to the control system.

[0029] It should be noted that the PLC, as the core control unit of the system, is responsible for processing the signals from the encoders and sensors and converting them into digital signals for further processing and communication. The data processing unit is a key component inside the PLC, which is responsible for converting the received analog signals into digital signals, while the communication interface is responsible for transmitting these digital signals to the control system of the crane.

[0030] Specifically, the data processing unit converts the analog signals of the encoder and the sensor into digital signals through an analog-to-digital converter (ADC). These signals include the position information of the trolley and the crane encoders, the position data of the RFID device, and the angle data of the slewing angle sensor 103 and the luffing angle sensor 104.

[0031] More specifically, the converted digital signals are sent to the internal processing unit of the PLC for further processing. The communication interface may include an Ethernet, serial communication, or wireless communication module for sending the processed data to the control system of the crane or other related devices.

[0032] Preferably, the data processing unit of the PLC can use a high-performance microprocessor to ensure the speed and accuracy of signal processing. The communication interface can select different communication protocols according to the actual industrial environment and communication requirements, such as Modbus, Profibus, or CANopen.

[0033] Furthermore, to improve the reliability and anti-interference ability of the system, the communication interface can use fiber optic communication or wireless communication and be equipped with corresponding signal enhancement and filtering technologies. In addition, the PLC can also integrate diagnostic and self-check functions for easy fault detection and maintenance.

[0034] Even further, in some application scenarios, the PLC can also be integrated with other automation systems or enterprise resource planning (ERP) systems to achieve more advanced automation control and data management.

[0035] In some embodiments, the warning control module includes a warning signal generator and a control actuator. The warning signal generator receives the real-time coordinate data from the collision detection module, generates a warning signal through collision risk assessment, and the control actuator receives the warning signal and outputs a control instruction to the actuator of the crane.

[0036] It should be noted that the warning control module is a key component of the system. It is responsible for receiving the real-time coordinate data from the collision detection module, performing collision risk assessment based on these data, and finally generating a warning signal. The warning signal generator and the control actuator are two main components of the warning control module, and they work together to ensure the safety of crane operation.

[0037] Specifically, the warning signal generator receives the real-time coordinate data from the collision detection module, which includes information such as the position, speed, and acceleration of the crane. By analyzing and processing these data, the warning signal generator can evaluate whether there is a collision risk in the operating state of the crane.

[0038] More specifically, the control actuator outputs corresponding control instructions to the actuators of the crane, such as the braking system or the steering system, according to the evaluation result of the early warning signal generator, so as to avoid collisions.

[0039] Preferably, the early warning signal generator can adopt advanced algorithms and models, such as machine learning or artificial intelligence technologies, to improve the accuracy of collision risk assessment. The response time of the control actuator can be optimized to ensure that actions can be taken promptly when a collision risk is detected.

[0040] Furthermore, the system can also integrate an adaptive control strategy to dynamically adjust the early warning threshold and control strategy according to the actual operating conditions of the crane and environmental changes. To improve the flexibility and scalability of the system, the early warning control module can also be designed in a modular structure, which is convenient for adding or replacing different early warning algorithms and control strategies as needed.

[0041] In some embodiments, the collision detection module receives the following data for generating real-time coordinate data: the position error of the crane, and the distance and speed of the track data sent by the host computer; including the following steps: Correct the position error sent by the host computer to obtain the corrected position; Segment the corrected position and distance by time intervals; Construct a third-order polynomial model of the distance and position of each segment of data; Fit each segment of data to obtain the speed, acceleration, and jerk; Construct a three-level accumulator, and calculate the recurrence parameters of one clock cycle according to the speed, acceleration, and jerk; Generate the acceleration, speed, and position of any number of clock cycles in cascade according to the recurrence parameters and the three-level accumulator.

[0042] It should be noted that the collision detection module is the core part of the system. It is responsible for receiving and processing the position error, distance, and speed data of the crane to generate real-time coordinate data. These data are used to construct the real-time motion model of the crane, and then predict possible collisions.

[0043] Specifically, the data received by the collision detection module includes the position error of the crane, which is sent by the host computer, and the distance and speed of the track data. The position error refers to the deviation between the actual position and the expected position of the crane. The distance and speed data provide the motion state of the crane on the track.

[0044] More specifically, the module first corrects the position error sent by the host computer to obtain the corrected position. Then, it segments the corrected position and distance by time intervals and constructs a third-order polynomial model of the distance and position of each segment of data.

[0045] Preferably, the collision detection module can adopt more advanced data processing techniques, such as Kalman filtering or particle filtering, to improve the accuracy of position correction. The parameters of the third-order polynomial model can be adjusted according to the actual motion characteristics of the crane to more accurately describe its motion trajectory.

[0046] Furthermore, the module can also be designed to support the simultaneous processing of multiple segments of data to improve the processing speed and real-time performance. To adapt to different operating environments and requirements, the module can also integrate environmental perception functions, such as wind speed and temperature monitoring, to more comprehensively evaluate the collision risk.

[0047] In some embodiments, the warning control module generates a warning signal based on the input real-time coordinate data and the evaluation result of the collision detection module, including: processing the real-time coordinate data to obtain a complex baseband signal; capturing and tracking the complex baseband signal through fast Fourier transform and phase-locked loop to obtain the frequency of the complex baseband signal; obtaining the warning signal frequency based on the frequency of the complex baseband signal and the Doppler frequency in the evaluation result of the collision detection module, and generating a warning signal according to the warning signal frequency.

[0048] It should be noted that the warning control module generates a warning signal by processing the real-time coordinate data and the evaluation result of the collision detection module. This process involves signal processing and frequency analysis techniques to ensure the accuracy and timeliness of the warning signal.

[0049] Specifically, the warning control module first processes the real-time coordinate data to obtain a complex baseband signal. The complex baseband signal is a signal containing position and velocity information, and it can be captured and tracked through fast Fourier transform (FFT) and phase-locked loop (PLL) techniques. Through these techniques, the frequency of the complex baseband signal can be obtained, and then, based on the frequency of the complex baseband signal and the Doppler frequency in the evaluation result of the collision detection module, the warning signal frequency can be calculated.

[0050] Preferably, the warning control module can adopt digital signal processing (DSP) technology to improve the speed and accuracy of signal processing. On the basis of FFT and PLL, an adaptive filter can be further introduced to adapt to the dynamically changing signal characteristics and environmental conditions.

[0051] Furthermore, various algorithms, such as wavelet transform or neural network, can be adopted for the generation of the warning signal to improve the accuracy and robustness of the warning signal. To improve the flexibility of the system, the warning control module can also be designed to be configurable, allowing users to select different signal processing algorithms and parameter settings according to different application scenarios.

[0052] In some embodiments, a third-order polynomial model of distance and position is constructed by the following formula: Where, Represents the initial distance of each segment of data, Represents the initial time of each segment of data, Represents the speed of each segment of data, Represents the acceleration of each segment of data, Represents the jerk of each segment of data, Represents any time of each segment of data, Represents the data period issued by the host computer.

[0053] It should be noted that the construction of the third-order polynomial model of distance and position is to accurately describe the motion state of the crane on the track, including its position, speed, acceleration and jerk. Such a model can provide accurate prediction of the crane's motion, thus providing the necessary data support for collision detection.

[0054] Preferably, the parameters of the third-order polynomial model can be dynamically adjusted according to the actual operating conditions of the crane. For example, if the crane operates under different load conditions, the values of the initial speed, acceleration and jerk may be different.

[0055] Furthermore, the model can be further refined to consider the influence of environmental factors such as wind speed and temperature. To improve the adaptability and accuracy of the model, machine learning algorithms can be used to optimize the parameter estimation. In some cases, higher-order polynomial models or other mathematical models, such as exponential models or logarithmic models, can also be considered to more accurately describe the motion characteristics of the crane.

[0056] In some embodiments, the step size and output of each stage accumulator in the three-stage accumulator are obtained in the following manner: Successively calculate the step size of each stage accumulator in one clock cycle according to the recurrence parameter of each stage accumulator in one clock cycle and the output of the previous stage accumulator; Each stage accumulator accumulates the same number of clock cycles according to its own step size, calculates the output of each stage accumulator, and passes it to the next stage accumulator.

[0057] It should be noted that the design of the three-stage accumulator is to achieve accurate calculation of the crane's motion state. It continuously updates the position, speed and acceleration of the crane through recurrence parameters and accumulation operations. This method can provide continuous tracking of the crane's motion, which is crucial for the real-time performance and accuracy of the anti-collision system.

[0058] Specifically, each level of the three - level accumulator is responsible for calculating a specific motion parameter. The first - level accumulator calculates the variable acceleration, the second - level accumulator calculates the acceleration based on the result of the first level, and the third - level accumulator calculates the velocity based on the result of the second level. The step size and output of each level of the accumulator are determined according to the recurrence parameters within a clock cycle and the output of the previous - level accumulator. For example, the step size of the first - level accumulator may be based on the recurrence parameters of the variable acceleration, while the step size of the second - level accumulator may be based on the recurrence parameters of the acceleration.

[0059] Preferably, the implementation of the three - level accumulator can be accomplished using digital logic circuits or software algorithms. In hardware implementation, FPGA or ASIC can be used to design the accumulator to achieve high - speed and high - precision calculations. In software implementation, efficient numerical calculation libraries can be utilized to optimize the calculation process.

[0060] Furthermore, to improve the flexibility and adaptability of the calculation, a parameter configuration interface can be designed to allow the operator to adjust the step size and calculation period of the accumulator according to the specific operating conditions of the crane. It is also possible to consider introducing an adaptive control algorithm so that the system can automatically adjust the parameters of the accumulator according to real - time feedback to adapt to different operating environments and load conditions.

[0061] In some embodiments, the recurrence parameters of each level of the accumulator within a clock cycle include: obtaining the recurrence parameter of the variable acceleration of the first - level accumulator within a clock cycle according to the velocity, acceleration, and variable acceleration of each segment of data, the recurrence parameter of the acceleration of the second - level accumulator within a clock cycle, and the recurrence parameter of the velocity of the third - level accumulator within a clock cycle.

[0062] It should be noted that the recurrence parameters of each level of the accumulator within a clock cycle are key data for calculating the motion state of the crane. These parameters include the recurrence values of variable acceleration, acceleration, and velocity, which allow the system to update the position and motion state of the crane within each clock cycle.

[0063] Specifically, the calculation of the recurrence parameters depends on the motion data of the crane in the previous clock cycle. For example, the recurrence parameter of the variable acceleration of the first - level accumulator can be calculated from the acceleration data of the current and the previous clock cycles.

[0064] More specifically, the recurrence parameter of the acceleration of the second - level accumulator can be calculated from the velocity data of the current and the previous clock cycles. The recurrence parameter of the velocity of the third - level accumulator is directly based on the variable acceleration data. The calculation formulas for these parameters can be difference equations or formulas based on physical motion laws.

[0065] Preferably, various numerical methods can be used to calculate the recurrence parameters to improve accuracy and efficiency. For example, the Runge-Kutta method or other numerical integration techniques can be used to approximate the solution of differential equations.

[0066] Furthermore, to adapt to different operating conditions, the system can be designed to automatically adjust the calculation parameters, such as the sampling frequency and the numerical integration step size. In some cases, an adaptive filter can also be considered to optimize the parameter estimation. To improve the robustness of the system, an anomaly detection mechanism can be introduced to identify and handle possible sensor errors or data loss situations.

[0067] In some embodiments, cascading to generate the acceleration, velocity, and position for any number of clock cycles based on the recurrence parameters and the three-level accumulator for one clock cycle includes: Taking the recurrence parameter of the variable acceleration for one clock cycle as the step size of the first-level accumulator for one clock cycle, and after accumulating for any number of clock cycles according to the step size, obtaining the acceleration output by the first-level accumulator; Adding the recurrence parameter of the acceleration for one clock cycle to the output of the first-level accumulator as the step size of the second-level accumulator for one clock cycle, and after accumulating for the same number of clock cycles according to the step size, obtaining the velocity output by the second-level accumulator; Adding the recurrence parameter of the velocity for one clock cycle to the output of the second-level accumulator as the step size of the third-level accumulator for one clock cycle, and after accumulating for the same number of clock cycles according to the step size, and then adding the initial distance of each track data, obtaining the position output by the third-level accumulator.

[0068] It should be noted that cascading to generate the acceleration, velocity, and position for any number of clock cycles is achieved by using the recurrence parameters and the three-level accumulator. This process allows the system to continuously track the motion state of the crane and predict its future position.

[0069] Specifically, the cascading generation process starts with the first-level accumulator, which uses the recurrence parameter of the variable acceleration for one clock cycle as the step size and calculates the acceleration through an accumulation operation. Then, the second-level accumulator adds the output acceleration of the first-level accumulator to the recurrence parameter of the acceleration for one clock cycle as its own step size to calculate the velocity. Finally, the third-level accumulator adds the velocity output of the second-level accumulator to the recurrence parameter of the velocity for one clock cycle as the step size, and after accumulation, adds the initial distance to obtain the position. This process is repeated in each clock cycle to update the real-time position of the crane.

[0070] Preferably, the cascading generation process can be implemented through software programming, where the recurrence parameters and the step sizes of the accumulators can be adjusted according to the actual motion characteristics of the crane. For example, a real-time operating system RTOS can be used to ensure the real-time performance of the calculation.

[0071] Furthermore, to improve the accuracy of calculations, higher-precision numerical calculation methods can be adopted, such as multi-step methods or adaptive step-size control. In some cases, machine learning algorithms can also be considered to predict the movement trend of the crane, thereby optimizing the step size of the accumulator and the calculation process. To enhance the adaptability of the system, a user interface can be designed to allow the operator to adjust the parameters of the accumulator and the calculation period according to actual needs.

[0072] In some embodiments, the PLC further includes a clock management unit for receiving an external clock signal and performing differential conversion, and then inputting it to the clock interfaces of the FPGA, the interfaces of the A / D module and the D / A module through a clock drive circuit.

[0073] It should be noted that the clock management unit of the PLC is a key component to ensure the synchronization and precise operation of the system. It is responsible for receiving the external clock signal and performing necessary differential conversion to ensure that all modules can operate with a unified time reference.

[0074] Specifically, the clock management unit receives an external clock signal, which can be a pulse signal from GPS or other high-precision clock sources. This unit converts these signals into a format suitable for internal use in the system and performs differential processing to correct any possible time deviation. The processed clock signal is transmitted to the clock interfaces of the FPGA, the interfaces of the A / D module and the D / A module through a clock drive circuit.

[0075] Preferably, the clock management unit can be designed to have high anti-interference ability to adapt to the electromagnetic interference that may exist in the industrial environment. In addition, the clock drive circuit can adopt optical fiber or other isolation technologies to improve the stability and reliability of signal transmission. To further improve the accuracy of the system, a temperature compensation mechanism can be considered to correct the clock drift caused by temperature changes.

[0076] Furthermore, in some applications, redundant clock sources can also be considered to improve the fault tolerance of the system. In addition, the system can be designed to support remote synchronization, allowing synchronous signals to be received from multiple clock sources through the network to ensure global clock consistency.

[0077] The above-mentioned embodiments of the present invention have the following beneficial effects: The anti-collision system for gantry and portal cranes based on the analytical method described in the present invention can improve the safety and efficiency of crane operation by integrating multiple sensors and advanced data processing technologies. The combined use of the absolute encoder 101, RFID setting device 102, slewing angle sensor 103, and luffing angle sensor 104 enables the system to monitor the position and motion state of the crane in real time and accurately. The collision detection module and early warning control module inside the PLC can quickly process the collected data, generate real-time coordinate data, evaluate the collision risk based on these data, and generate early warning signals in a timely manner. This can issue warnings to the operator before a potential collision occurs, thus avoiding accidents and ensuring the safety of personnel and equipment.

[0078] In addition, the design of the third-order polynomial model and the three-level accumulator adopted by the system can accurately perform mathematical modeling and calculation on the motion parameters of the crane. In this way, the system can not only predict the position of the crane at any future moment, but also accurately calculate its speed and acceleration. This advanced data processing ability, combined with a fast communication interface, can ensure that the system can respond in real time and maintain a high level of reliability and accuracy even in a complex operating environment. The coordinated operation of the early warning signal generator and the control actuator can further improve the response speed of the system and the accuracy of operation, making the crane operation more intelligent and automated.

[0079] Furthermore, the storage medium of the embodiment of the present application stores program instructions capable of implementing all the above methods. Among them, the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, or terminal devices such as computers, servers, mobile phones, and tablets.

[0080] The above description is only some preferred embodiments of the present invention and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present invention is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the embodiments of the present invention.

Claims

1. A gantry and portal crane anti-collision system based on the analytical method, characterized in that, include: An absolute value encoder, an RFID positioning device, a rotation angle sensor and a variable angle sensor, wherein the absolute value encoder includes a trolley encoder and a trolley encoder, the RFID positioning device is used to determine the position of the crane on the track, the rotation angle sensor is used to monitor the rotation angle of the gantry crane, and the variable angle sensor is used to monitor the angle of the variable angle mechanism; the trolley encoder is used to encode the running position of the gantry crane trolley, obtain the trolley position information, and transmit it to the PLC of the gantry crane; the trolley encoder is used to encode the running position of the gantry crane trolley, obtain the trolley position information, and transmit it to the PLC of the gantry crane; the PLC communicates with the PLC of the gantry crane through a communication module, including a collision detection module and an early warning control module, the collision detection module generates real-time coordinate data according to the received crane position information and angle information, and stores it in a database, and the early warning control module generates an early warning signal according to the real-time coordinate data and after collision risk assessment, and outputs it to the control system to control the operation of the crane; Among them, the PLC includes a data processing unit and a communication interface. The data processing unit is used to convert the signals of the encoder and the sensor into digital signals, and transmit them to the communication interface. The communication interface outputs the digital signals to the control system; the early warning control module includes an early warning signal generator and a control executor. The early warning signal generator receives the real-time coordinate data of the collision detection module, generates an early warning signal after collision risk assessment, and the control executor receives the early warning signal and outputs control instructions to the crane's actuator.

2. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 1, characterized in that, The collision detection module receives the following data for generating real-time coordinate data: the position error of the crane, and the distance and speed of the track data sent by the host computer; and comprises the following steps: Correct the position error sent by the host computer and obtain the corrected position; The corrected position and distance are divided into time interval segments; Construct a third-order polynomial model of the distance and position of each segment of data; Fit each segment of data to obtain velocity, acceleration and variable acceleration; Construct a three-level accumulator to calculate the recursive parameters of a clock cycle based on speed, acceleration, and variable acceleration; According to the recursive parameters and the three-stage accumulator, the acceleration, velocity and position of any number of clock cycles are cascaded.

3. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 2, characterized in that, The early warning control module generates an early warning signal according to the input real-time coordinate data and the evaluation result of the collision detection module, including: processing the real-time coordinate data to obtain a complex baseband signal; capturing and tracking the complex baseband signal through a fast Fourier transform and a phase-locked loop to obtain the frequency of the complex baseband signal; obtaining the early warning signal frequency according to the complex baseband signal frequency and the Doppler frequency in the evaluation result of the collision detection module, and generating the early warning signal according to the early warning signal frequency.

4. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 3, characterized in that, A third-order polynomial model for distance and location is constructed using the following formula: Among them, represents the initial distance of each data segment, represents the initial time of each data segment, represents the speed of each data segment, represents the acceleration of each data segment, represents the variable acceleration of each data segment, represents any time of each data segment, represents the data cycle sent by the host computer.

5. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 4, characterized in that, The step size and output of each stage of the three-stage accumulator are obtained by: The step length of each stage accumulator in one clock cycle is calculated in turn according to the recursive parameters of each stage accumulator in one clock cycle and the output of the previous stage accumulator; Each - stage accumulator accumulates the same number of clock cycles according to its own step size, calculates the output of each - stage accumulator, and passes it to the next - stage accumulator.

6. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 5, characterized in that, The recurrence parameters of each - stage accumulator in one clock cycle include: obtaining the recurrence parameter of the variable acceleration of the first - stage accumulator in one clock cycle, the recurrence parameter of the acceleration of the second - stage accumulator in one clock cycle, and the recurrence parameter of the velocity of the third - stage accumulator in one clock cycle according to the velocity, acceleration, and variable acceleration of each data segment.

7. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 6, characterized in that, The cascading of the acceleration, velocity, and position of any number of clock cycles according to the recurrence parameters of one clock cycle and the three - stage accumulator includes: Taking the recurrence parameter of the variable acceleration in one clock cycle as the step size of the first - stage accumulator in one clock cycle, after accumulating any number of clock cycles according to its step size, the acceleration output by the first - stage accumulator is obtained; Adding the recurrence parameter of the acceleration in one clock cycle to the output of the first - stage accumulator as the step size of the second - stage accumulator in one clock cycle, after accumulating the same number of clock cycles according to its step size, the velocity output by the second - stage accumulator is obtained; Adding the recurrence parameter of the velocity in one clock cycle to the output of the second - stage accumulator as the step size of the third - stage accumulator in one clock cycle, after accumulating the same number of clock cycles according to its step size, and then adding the initial distance of each track data, the position output by the third - stage accumulator is obtained.

8. The anti-collision system for gantry and portal cranes based on the analytical method according to claim 7, characterized in that, The PLC also includes a clock management unit for receiving an external clock signal and performing differential conversion, and then inputting it to the clock interface of the FPGA, the interfaces of the A / D module and the D / A module respectively through a clock driving circuit.

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