A Smart Control Method for Separate Unloading Platforms

Abstract

A smart control method for a detachable unloading platform, relating to the field of equipment control technology, is disclosed. The method involves constructing a digital twin model of the detachable unloading platform, deploying multi-source data acquisition terminals to obtain different monitoring data, acquiring the aging coefficient and friction coefficient increase based on actual and theoretical acceleration under standard operating conditions, obtaining the desired driving force to achieve the desired speed under different friction coefficient increases and material weights, and constructing a smart control model. This model enables intelligent control of the detachable unloading platform and the acquisition of material weight thresholds. Based on the aging coefficient and monitoring data, the method determines whether the detachable unloading platform has reached a scrap or fault state, generates early warning signals, and provides feedback. This significantly improves the targeting of the detachable unloading platform control and provides flexible driving force control strategies for different material transportation situations.

Description

Technical Field

[0001] This invention relates to the field of equipment control technology, specifically an intelligent control method for a detachable unloading platform. Background Technology

[0002] In the actual application scenarios of building construction, unloading platforms for transferring materials from inside the building to the outside or from the outside to the inside are indispensable. Currently, the traditional unloading platforms in the construction industry are generally cantilevered unloading platforms, which often have various problems such as platform instability, low material transfer efficiency, inadequate safety monitoring measures, and long-term exposure of workers to the outside.

[0003] Therefore, the separate unloading platform has emerged. It uses a servo motor to drive the transport structure to transport materials. Existing technologies often adopt a fixed driving force control strategy because they fail to consider the aging of the equipment itself and the impact of different transport weights. This results in a lack of flexibility in the driving force control of the transport structure. In order to address the shortcomings of existing technologies, this invention provides an intelligent control method for the separate unloading platform. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent control method for a detachable unloading platform.

[0005] The objective of this invention can be achieved through the following technical solution: an intelligent control method for a detachable unloading platform, comprising the following steps:

[0006] Step S1: Obtain the structural information of each component of the separate unloading platform and build the corresponding digital twin model. Deploy a multi-source data acquisition terminal on the separate unloading platform, use the multi-source data acquisition terminal to acquire different monitoring data, and synchronize them to the digital twin model.

[0007] Step S2: Obtain the actual acceleration and theoretical acceleration of the separate unloading platform under standard working conditions, and obtain the corresponding aging coefficient and friction coefficient increase. In the digital twin model, obtain the expected driving force required to achieve the desired speed under different friction coefficient increases and material weights, and construct the corresponding intelligent control model.

[0008] Step S3: In actual application scenarios, use the intelligent control model to intelligently control the separate unloading platform and obtain the corresponding vibration coefficient. In the digital twin model, combine different expected speeds and material weights to obtain the corresponding material weight threshold.

[0009] Step S4: Set the scrap threshold and fault threshold, determine whether the separate unloading platform has reached the scrap state and fault state based on the aging coefficient and monitoring data, generate the corresponding early warning signal and provide feedback.

[0010] Furthermore, the process of obtaining structural information of each component of the separate unloading platform and constructing the corresponding digital twin model includes:

[0011] The separate unloading platform includes a platform structure and a separate transportation structure. The structural information of the platform structure and the separate transportation structure is obtained, including material specifications, connection relationships, and dimensional parameters.

[0012] A physical model of the split unloading platform is constructed using digital twin technology based on the acquired structural information. The constructed physical model is then simulated using simulation software to obtain a digital twin model.

[0013] Furthermore, the process of deploying multi-source data acquisition terminals on the separate unloading platform, acquiring different monitoring data using these terminals, and synchronizing them to the digital twin model includes:

[0014] The multi-source data acquisition terminal includes a load monitoring unit, a speed monitoring unit, and a drive monitoring unit;

[0015] Load monitoring units and speed monitoring units are installed on the separate transport structure to obtain the weight of the materials transported by the separate transport structure and the acceleration and speed of the separate transport structure in real time.

[0016] A drive monitoring unit is installed on the servo motor of the split transport structure to obtain the driving force provided by the servo motor to the split transport structure in real time. The monitoring data includes material weight, acceleration, speed and driving force. All monitoring data are uploaded to the digital twin model for synchronization.

[0017] Furthermore, the process of obtaining the actual and theoretical acceleration of the separate unloading platform under standard operating conditions, and obtaining the corresponding aging coefficient and friction coefficient increase, includes:

[0018] The standard operating condition refers to the fact that the driving force provided by the servo motor and the weight of the materials transported by the separate transport structure are both preset fixed values.

[0019] Under standard operating conditions, the acceleration of the separated transport structure of the separated unloading platform at the same moment in the actual application scenario and in the digital twin model is obtained, and denoted as S respectively. aj and S az ;

[0020] The aging coefficient and friction coefficient increase of the separate unloading platform in the actual application scenario are obtained and denoted as H.s and Δμ;

[0021]

[0022]

[0023] F y m y μ y Let m represent the driving force, material weight, and coefficient of friction under standard operating conditions, m0 represent the self-weight of the separated transport structure, and g represent the acceleration due to gravity.

[0024] Furthermore, the process of obtaining the desired driving force required to achieve the desired speed under different friction coefficient increases and material weights in the digital twin model, and constructing the corresponding intelligent control model, includes:

[0025] The desired speed is defined as the constant speed that the desired separation transport structure can achieve during transport. In the digital twin model, the method of controlling variables is used to obtain the desired driving force required to achieve different desired speeds under different friction coefficient increases and material weights.

[0026] The desired driving force refers to the minimum driving force that the servo motor needs to provide for the separate transport structure in order to achieve the desired speed. Based on different desired speeds, friction coefficient increases, material weights and their desired driving forces, an intelligent control set is generated, and the intelligent control set is divided into a training set and a test set.

[0027] Convolutional neural networks are constructed, with different desired speeds, friction coefficient increases, and material weights in the training set as input data and the corresponding desired driving forces in the training set as output data.

[0028] The convolutional neural network is trained to obtain an initial convolutional neural network. The initial convolutional neural network is then validated using a test set. The initial convolutional neural network whose output is less than or equal to a preset test error threshold is used as the intelligent control model.

[0029] Furthermore, in practical application scenarios, the process of using an intelligent control model to intelligently control the separate unloading platform and obtain the corresponding vibration coefficient includes:

[0030] In practical applications, a desired speed is set for the separated transport structure, and the increase in its friction coefficient and the weight of the material are obtained.

[0031] The above three data points are input into the intelligent control model, which outputs the corresponding desired driving force. The servo motor then provides the acquired desired driving force to the separate transport structure in real time to achieve intelligent control of the separate unloading platform.

[0032] Corresponding amplitude monitoring units are installed on each wire rope of the platform structure to obtain the vibration amplitude of each wire rope at the same moment in real time.

[0033] The average vibration amplitude of each wire rope at the end of the drive is taken as the corresponding amplitude coefficient. The end of the drive refers to the time when the separate transport structure reaches the designated position.

[0034] Furthermore, the process of obtaining the corresponding material weight threshold by combining different desired speeds and material weights in the digital twin model includes:

[0035] Set an amplitude coefficient threshold, keep a single desired speed constant in the digital twin model, continuously adjust the material weight to obtain the maximum material weight without exceeding the amplitude coefficient threshold, and use it as the material weight threshold at that desired speed.

[0036] The desired speed is adjusted to obtain the material weight threshold at different desired speeds, and the corresponding material weight threshold is provided for the set desired speed during actual operation.

[0037] Furthermore, the process of setting scrap and failure thresholds, determining whether the separate unloading platform has reached a scrap or failure state based on aging coefficients and monitoring data, generating corresponding early warning signals, and providing feedback includes:

[0038] Set a scrap threshold and compare the aging coefficient of the separate unloading platform with the scrap threshold. If the aging coefficient is greater than or equal to the scrap threshold, mark it as scrapped and generate a scrap warning signal.

[0039] Set fault thresholds, including acceleration threshold, speed threshold, and driving force threshold. Compare the acceleration, speed, and driving force in the monitoring data with their respective fault thresholds. If the monitoring data is greater than or equal to the fault threshold, mark it as a fault state and generate a fault warning signal. Feedback the scrap warning signal and the fault warning signal to relevant personnel.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] This invention constructs a digital twin model of a separate unloading platform, which can simulate the relevant data generated by the separate unloading platform under various working conditions. Based on the difference in acceleration between the actual and theoretical conditions of the separate unloading platform under standard working conditions, the aging coefficient and friction coefficient increase of the separate unloading platform can be obtained. This is beneficial to take the aging of the equipment into account and improve the pertinence of the control of the separate unloading platform.

[0042] By obtaining the desired driving force required to reach the desired speed under different friction coefficient increases and material weights in the digital twin model, and constructing the corresponding intelligent control model, a flexible driving force control strategy can be provided for different material transportation situations. By setting the vibration coefficient threshold, the material weight threshold under different desired speeds and material weights can be obtained, which can simultaneously ensure the stability of the separate unloading platform and not exceed its maximum transportation capacity, thus improving the stability of the separate unloading platform. Attached Figure Description

[0043] Figure 1 This is a flowchart of the present invention;

[0044] Figure 2 This is a schematic diagram of a detachable unloading platform;

[0045] Figure 3 This is a schematic diagram of the platform structure;

[0046] Figure 4 This is a schematic diagram of a separate transportation structure. Detailed Implementation

[0047] like Figure 1 As shown, an intelligent control method for a detachable unloading platform includes the following steps:

[0048] Step S1: Obtain the structural information of each component of the separate unloading platform and build the corresponding digital twin model. Deploy a multi-source data acquisition terminal on the separate unloading platform, use the multi-source data acquisition terminal to acquire different monitoring data, and synchronize them to the digital twin model.

[0049] Step S2: Obtain the actual acceleration and theoretical acceleration of the separate unloading platform under standard working conditions, and obtain the corresponding aging coefficient and friction coefficient increase. In the digital twin model, obtain the expected driving force required to achieve the desired speed under different friction coefficient increases and material weights, and construct the corresponding intelligent control model.

[0050] Step S3: In actual application scenarios, use the intelligent control model to intelligently control the separate unloading platform and obtain the corresponding vibration coefficient. In the digital twin model, combine different expected speeds and material weights to obtain the corresponding material weight threshold.

[0051] Step S4: Set the scrap threshold and fault threshold, determine whether the separate unloading platform has reached the scrap state and fault state based on the aging coefficient and monitoring data, generate the corresponding early warning signal and provide feedback.

[0052] It should be further explained that, in the specific implementation process, the process of obtaining the structural information of each component of the separate unloading platform and constructing the corresponding digital twin model includes:

[0053] Currently, the traditional unloading platforms in the construction industry are generally cantilevered unloading platforms, which often suffer from various problems such as platform instability, low material transfer efficiency, inadequate safety monitoring measures, and long-term exposure of workers to the elements.

[0054] In an embodiment of the present invention, a separate unloading platform is provided for construction engineering, for transferring materials from inside a building to the outside or from the outside to the inside of a building. Figure 2 As shown;

[0055] The detachable unloading platform consists of two parts: firstly, the platform structure, such as... Figure 3 As shown, the second type is a separate transportation structure, such as... Figure 4 As shown;

[0056] The platform structure uses I-beams as the main load-bearing structure. The cantilever platform is fixed to the structural floor slab by tail support poles and anchors. Multiple steel wire ropes are installed on both sides of the cantilever end to connect the cantilever end to the main structure of the upper building.

[0057] The detachable transport structure is driven by a servo motor and is separated and fixed to the platform structure by bolts. In the detached state, it can transport materials to a designated location and is equipped with corresponding limit devices to ensure that the material transport is always within a safe range.

[0058] Obtain the structural information of the platform structure and the separate transportation structure. The structural information refers to the various data necessary for constructing the physical model of the separate unloading platform, including the material specifications, connection relationships, and dimensional parameters of the platform structure and the separate transportation structure.

[0059] A physical model of a separate unloading platform is constructed using digital twin technology based on the acquired structural information. The constructed physical model is then simulated using simulation software to obtain a digital twin model of the separate unloading platform. This digital twin model is capable of acquiring the transportation process of the separate unloading platform and the relevant data generated during transportation.

[0060] It should be further explained that, in the specific implementation process, the deployment of multi-source data acquisition terminals on the separate unloading platform, the acquisition of different monitoring data by these terminals, and the synchronization of this data to the digital twin model include:

[0061] Different multi-source data acquisition terminals are set up on the separate unloading platform, including load monitoring unit, speed monitoring unit and drive monitoring unit;

[0062] A load monitoring unit and a speed monitoring unit are respectively installed on the separate transport structure. The load monitoring unit obtains the weight of the material transported by the separate transport structure in real time, and the speed monitoring unit obtains the acceleration and speed of the separate transport structure in real time.

[0063] A drive monitoring unit is set on the servo motor to obtain the driving force provided by the servo motor to the separate transport structure in real time. The monitoring data includes the material weight, acceleration, speed and driving force mentioned above. The obtained monitoring data is uploaded to the digital twin model of the separate unloading platform for synchronization.

[0064] It should be further explained that, in the specific implementation process, the process of obtaining the actual and theoretical acceleration of the separate unloading platform under standard operating conditions, and obtaining the corresponding aging coefficient and friction coefficient increase, includes:

[0065] The standard operating condition refers to the fact that the driving force provided by the servo motor and the weight of the materials transported by the separate transport structure are both preset fixed values.

[0066] Under standard operating conditions, the acceleration of the separated transport structure of the separated unloading platform at the same moment in the actual application scenario and in the digital twin model are obtained separately and denoted as S. aj and S az The same moment is calculated based on the start time of the drive;

[0067] The aging coefficient and friction coefficient increase of the separate unloading platform in the actual application scenario are obtained and denoted as H. s and Δμ;

[0068]

[0069]

[0070] Among them, F y m y μ y Let m represent the driving force, material weight, and coefficient of friction under standard operating conditions, m0 represent the self-weight of the separated transport structure, and g represent the acceleration due to gravity.

[0071] It should be further explained that, in the specific implementation process, the process of obtaining the desired driving force required to achieve the desired speed under different friction coefficient increases and material weights in the digital twin model, and constructing the corresponding intelligent control model, includes:

[0072] Set the desired speed, which refers to the constant speed that relevant personnel expect the separated transport structure to achieve during transport. In the digital twin model, the controlled variable method is used to obtain the desired driving force required to achieve the desired speed under different friction coefficient increases and material weights.

[0073] To maintain the desired speed, the friction coefficient increase and material weight are continuously adjusted to obtain the corresponding desired driving force. The desired driving force refers to the minimum driving force that the servo motor needs to provide to the separate transport structure in order to achieve the desired speed.

[0074] Keeping the friction coefficient increase and material weight constant, the desired speed is continuously adjusted to obtain the corresponding desired driving force. Based on different desired speeds, friction coefficient increases, material weights and their corresponding desired driving forces, an intelligent control set is generated, and the intelligent control set is divided into a training set and a test set.

[0075] Convolutional neural networks are constructed, with different desired speeds, friction coefficient increases, and material weights in the training set as input data and the corresponding desired driving forces in the training set as output data.

[0076] The convolutional neural network is trained to obtain an initial convolutional neural network. The initial convolutional neural network is then validated using a test set. The initial convolutional neural network whose output is less than or equal to a preset test error threshold is used as the intelligent control model.

[0077] It should be further explained that, in the specific implementation process, the process of using an intelligent control model to intelligently control the separate unloading platform and obtain the corresponding vibration coefficient in actual application scenarios includes:

[0078] In practical applications, relevant personnel set the desired speed for the separated transport structure and obtain its friction coefficient increase and material weight.

[0079] The above three data are input into the intelligent control model, and the intelligent control model outputs the corresponding desired driving force. The servo motor provides the output desired driving force to the separate transport structure in real time to realize the intelligent control of the separate unloading platform.

[0080] Each wire rope on the platform structure is numbered as i, i = 1, 2, ..., n, where n is the total number of wire ropes. A corresponding amplitude monitoring unit is set on each wire rope, and the vibration amplitude of each wire rope at the same moment is obtained through the amplitude monitoring unit.

[0081] The average vibration amplitude of each wire rope at the end of the drive is taken as the corresponding amplitude coefficient. The end of the drive refers to the time when the separate transport structure reaches the designated position.

[0082] It should be further explained that, in the specific implementation process, the process of obtaining the corresponding material weight threshold by combining different expected speeds and material weights in the digital twin model includes:

[0083] An amplitude coefficient threshold is set to limit the vibration amplitude of the wire rope, ensuring that the entire separate unloading platform remains as stable as possible during transportation.

[0084] In the digital twin model, a single desired velocity is kept constant, and the material weight is continuously adjusted to obtain the maximum material weight without exceeding the amplitude coefficient threshold, and this maximum material weight is used as the material weight threshold at that desired velocity.

[0085] The desired speed is adjusted to obtain the material weight threshold at different desired speeds. In actual operation, the corresponding material weight threshold is provided for the desired speed set by relevant personnel to ensure that the material transported by the separated transport structure does not exceed its corresponding material weight threshold.

[0086] It should be further explained that, in the specific implementation process, the process of setting scrap thresholds and failure thresholds, determining whether the separate unloading platform has reached a scrap or failure state based on the aging coefficient and monitoring data, generating corresponding early warning signals, and providing feedback includes:

[0087] Set a scrap threshold and compare the aging coefficient of the separate unloading platform with the scrap threshold. If the aging coefficient is greater than or equal to the scrap threshold, the separate unloading platform is judged to be severely worn and marked as scrapped, and a corresponding scrap warning signal is generated. If the aging coefficient is less than the scrap threshold, no other operation is performed on it.

[0088] Set fault thresholds, including acceleration threshold, velocity threshold, and driving force threshold. Compare the acceleration, velocity, and driving force in the monitoring data with their corresponding fault thresholds. If the monitoring data is greater than or equal to the fault threshold, it is determined that the separate unloading platform has a corresponding fault, and it is marked as a fault state, generating a corresponding fault warning signal.

[0089] The fault warning signals include acceleration warning signals, speed warning signals, and driving force warning signals. These warning signals (including scrap warning signals and fault warning signals) are fed back to relevant personnel to remind them to perform timely maintenance on the separate unloading platform.

[0090] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An intelligent control method for a detachable unloading platform, characterized in that, Includes the following steps: Step S1: Obtain the structural information of each component of the separate unloading platform and build the corresponding digital twin model. Deploy a multi-source data acquisition terminal on the separate unloading platform, use the multi-source data acquisition terminal to acquire different monitoring data, and synchronize them to the digital twin model. Step S2: Obtain the actual acceleration and theoretical acceleration of the separate unloading platform under standard working conditions, and obtain the corresponding aging coefficient and friction coefficient increase. In the digital twin model, obtain the expected driving force required to achieve the desired speed under different friction coefficient increases and material weights, and construct the corresponding intelligent control model. Step S3: In actual application scenarios, use the intelligent control model to intelligently control the separate unloading platform and obtain the corresponding vibration coefficient. In the digital twin model, combine different expected speeds and material weights to obtain the corresponding material weight threshold. Step S4: Set the scrap threshold and fault threshold, determine whether the separate unloading platform has reached the scrap state and fault state based on the aging coefficient and monitoring data, generate the corresponding early warning signal and provide feedback; The process of obtaining the actual and theoretical acceleration of the separate unloading platform under standard operating conditions, and obtaining the corresponding aging coefficient and friction coefficient increase, includes: The standard operating condition refers to the fact that the driving force provided by the servo motor and the weight of the materials transported by the separate transport structure are both preset fixed values. Under standard operating conditions, the acceleration of the separated transport structure of the separated unloading platform at the same moment in the actual application scenario and in the digital twin model is obtained, and denoted as S respectively. aj and S az ; The aging coefficient and friction coefficient increase of the separate unloading platform in the actual application scenario are obtained and denoted as H. s and ; The driving force, material weight, and coefficient of friction are given under standard operating conditions. For the weight of the separate transport structure, This is the acceleration due to gravity.

2. The intelligent control method for a detachable unloading platform according to claim 1, characterized in that, The process of building a digital twin model of a split unloading platform includes: The separate unloading platform includes a platform structure and a separate transportation structure. The structural information of the platform structure and the separate transportation structure is obtained, including material specifications, connection relationships, and dimensional parameters. A physical model of the split unloading platform is constructed using digital twin technology based on the acquired structural information. The constructed physical model is then simulated using simulation software to obtain a digital twin model.

3. The intelligent control method for a detachable unloading platform according to claim 2, characterized in that, The process of acquiring different monitoring data using multi-source data acquisition terminals includes: The multi-source data acquisition terminal includes a load monitoring unit, a speed monitoring unit, and a drive monitoring unit; Load monitoring units and speed monitoring units are installed on the separate transport structure to obtain the weight of the materials transported by the separate transport structure and the acceleration and speed of the separate transport structure in real time. A drive monitoring unit is installed on the servo motor of the split transport structure to obtain the driving force provided by the servo motor to the split transport structure in real time. The monitoring data includes material weight, acceleration, speed and driving force. All monitoring data are uploaded to the digital twin model for synchronization.

4. The intelligent control method for a detachable unloading platform according to claim 3, characterized in that, The process of building an intelligent control model includes: The desired speed is defined as the constant speed that the desired separation transport structure can achieve during transport. In the digital twin model, the method of controlling variables is used to obtain the desired driving force required to achieve different desired speeds under different friction coefficient increases and material weights. The desired driving force refers to the minimum driving force that the servo motor needs to provide for the separate transport structure in order to achieve the desired speed. Based on different desired speeds, friction coefficient increases, material weights and their desired driving forces, an intelligent control set is generated, and the intelligent control set is divided into a training set and a test set. Convolutional neural networks are constructed, with different desired speeds, friction coefficient increases, and material weights in the training set as input data and the corresponding desired driving forces in the training set as output data. The convolutional neural network is trained to obtain an initial convolutional neural network. The initial convolutional neural network is then validated using a test set. The initial convolutional neural network whose output is less than or equal to a preset test error threshold is used as the intelligent control model.

5. The intelligent control method for a detachable unloading platform according to claim 4, characterized in that, The process of intelligently controlling the split unloading platform and obtaining its vibration coefficient includes: In practical applications, a desired speed is set for the separated transport structure, and the increase in its friction coefficient and the weight of the material are obtained. The above three data points are input into the intelligent control model, which outputs the corresponding desired driving force. The servo motor then provides the acquired desired driving force to the separate transport structure in real time to achieve intelligent control of the separate unloading platform. Corresponding amplitude monitoring units are installed on each wire rope of the platform structure to obtain the vibration amplitude of each wire rope at the same moment in real time. The average vibration amplitude of each wire rope at the end of the drive is taken as the corresponding amplitude coefficient. The end of the drive refers to the time when the separate transport structure reaches the designated position.

6. The intelligent control method for a detachable unloading platform according to claim 5, characterized in that, The process of obtaining the material weight threshold includes: Set an amplitude coefficient threshold, keep a single desired speed constant in the digital twin model, continuously adjust the material weight to obtain the maximum material weight without exceeding the amplitude coefficient threshold, and use it as the material weight threshold at that desired speed. The desired speed is adjusted to obtain the material weight threshold at different desired speeds, and the corresponding material weight threshold is provided for the set desired speed during actual operation.

7. The intelligent control method for a detachable unloading platform according to claim 6, characterized in that, The process of determining whether a split unloading platform has reached a scrap or faulty state includes: Set a scrap threshold and compare the aging coefficient of the separate unloading platform with the scrap threshold. If the aging coefficient is greater than or equal to the scrap threshold, mark it as scrapped and generate a scrap warning signal. Set fault thresholds, including acceleration threshold, speed threshold, and driving force threshold. Compare the acceleration, speed, and driving force in the monitoring data with their respective fault thresholds. If the monitoring data is greater than or equal to the fault threshold, mark it as a fault state and generate a fault warning signal. Feedback the scrap warning signal and the fault warning signal to relevant personnel.

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