A warehouse management system based on big data

Abstract

The present invention discloses a warehouse management system based on big data, which relates to the field of warehouse management technology, including an initial speed setting module, a dynamic information collection module, a feature extraction and transmission environment perception module, an intelligent model prediction module, a graded speed control module, a speed data set generation module, and a minimum speed screening and transmission module; the initial speed setting module places large items of the same batch on a chain conveyor. The present invention obtains the dynamic information of large items at the turning point of the chain conveyor in real time, combines the support vector machine model for prediction and evaluation, dynamically adjusts the maximum initial transmission speed, and realizes graded regulation of safety and stability. Compared with the fixed low-speed method, the intelligent solution effectively avoids the tilting and falling of items, reduces risks and improves efficiency. By screening the minimum transmission speed and optimizing the multi-turn system, the operating efficiency is significantly improved, especially in peak hours or emergency order processing, and delays are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and in particular to a warehouse management system based on big data. Background Art

[0002] A warehouse management system (WMS) based on big data refers to a system that uses big data technology to comprehensively manage and optimize warehouse operations. It helps warehouse managers make more scientific and accurate decisions by collecting, analyzing and processing a large amount of data from all aspects of the warehouse in real time, such as inventory quantity, goods in and out of the warehouse, order information, equipment operation status, employee work efficiency, etc. Through big data analysis, WMS can dynamically adjust the inventory layout, optimize the storage and access paths of goods, and improve the efficiency of warehouse operations; it can also predict future inventory needs and reduce the risk of inventory backlog or shortage. In addition, WMS can also identify bottlenecks and room for improvement in operations through the analysis of historical data, and improve the intelligence level of the entire warehousing process. This system combines automated equipment, IoT sensors and artificial intelligence technology, which not only improves operational efficiency, but also reduces warehousing costs, improves customer service levels, and realizes the digital and intelligent transformation of warehouse management.

[0003] In warehouse management systems based on big data, chain conveyors are widely used to transport large items, such as furniture, home appliances, and mechanical equipment. These items have extremely high requirements for conveying equipment due to their large size and weight. When large items of the same batch are transported in batches, in order to ensure the stability of the items during transportation, the existing technology usually sets the conveying speed very low at the turns of the chain conveyor. This practice effectively prevents the items from tilting, shaking, or falling when turning, thereby improving safety. However, this setting has obvious limitations in applicability, especially during peak hours or when processing urgent orders. Low-speed transportation will significantly reduce overall operating efficiency, resulting in delays in order processing and decreased customer satisfaction. This problem is particularly prominent in chain conveyor systems with multiple turns.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide a warehouse management system based on big data, which can accurately grasp the transmission status of items by acquiring the dynamic information of large items at the turns of chain conveyors in real time, and predicting and evaluating the transmission environment in combination with a support vector machine model. The system timely adjusts the maximum initial transmission speed according to the dynamic changes of the items, realizes hierarchical regulation, and ensures the safety and stability of items at turns. Compared with the traditional fixed low-speed transmission method, this intelligent regulation scheme more effectively prevents items from tilting or falling, reduces safety risks, and improves transmission efficiency. At the same time, by screening out the minimum transmission speed after multiple adjustments, optimizing the multi-turn conveying system, especially during peak hours or when processing urgent orders, improving operating efficiency, reducing delays, and improving overall operating efficiency, so as to solve the problems in the above-mentioned background technology.

[0006] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a warehouse management system based on big data, comprising an initial speed setting module, a dynamic information collection module, a feature extraction and transmission environment perception module, an intelligent model prediction module, a hierarchical speed control module, a speed data set generation module and a minimum speed screening and transmission module;

[0007] The initial speed setting module places large items of the same batch on the chain conveyor and sets the maximum initial transmission speed for item transmission;

[0008] Dynamic information collection module, when the large items pass through the turning point of the chain conveyor, it can obtain the instantaneous transmission dynamic change information of the large items and the instantaneous dynamic change information of the turning point of the chain conveyor in real time;

[0009] The feature extraction and transmission environment perception module extracts features from the collected dynamic change information, analyzes the extracted features, and makes a preliminary perception of the stability of the transmission environment for large items through the analyzed features;

[0010] The intelligent model prediction module inputs the analyzed features into the pre-trained support vector machine model, uses the support vector machine model to predict the dynamic scene at the turning point of the chain conveyor, and evaluates the transmission stability under the current conditions;

[0011] The graded speed control module controls the maximum initial transmission speed of large items based on the prediction results of the support vector machine model to ensure the stability of the items when turning.

[0012] The speed data set generation module, when the speed control is performed more than once at the same time, creates a data set of the actual transmission speed after the control, and sorts the actual transmission speeds in the data set in order;

[0013] The minimum speed screening and transmission module, after the data set is established, screens out the minimum actual transmission speed, and transmits items on the chain conveyor at the screened actual transmission speed.

[0014] Preferably, the maximum initial transmission speed refers to the highest transmission speed set when the transmission of large items begins, and its purpose is to ensure that the large items can pass through the chain conveyor at the highest safe speed under the premise of ensuring safe and stable transmission.

[0015] Preferably, when the large items pass through the turning point of the chain conveyor, the acquired dynamic change information of the transmission of the large items includes the center of gravity offset at the turning point of the chain conveyor during the transmission of the large items, and the acquired instantaneous dynamic change information at the turning point of the chain conveyor includes the pressure change on the chain at the turning point. After analyzing the center of gravity offset at the turning point of the chain conveyor during the transmission of the large items, a quantitative reference value of the center of gravity offset is generated, and the degree of offset of the center of gravity position of the large items relative to the original center of gravity during the transmission process is quantified by the quantitative reference value of the center of gravity offset. After analyzing the pressure change on the chain at the turning point, a quantitative reference value of the chain tension is generated, and the change amplitude of the instantaneous pressure on the chain at the turning point is quantified by the quantitative reference value of the chain tension. The stability of the transmission environment for large items is initially perceived through the analyzed quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension.

[0016] Preferably, after obtaining the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension, the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension are input into a pre-trained support vector machine model, and a transmission stability evaluation coefficient is generated based on the model. The transmission stability evaluation coefficient is used to perform an intelligent evaluation of the transmission stability of items at the turning points of the chain conveyor.

[0017] Preferably, the specific steps of generating a quantitative reference value of the center of gravity offset after analyzing the center of gravity offset at the turning point of the chain conveyor during the transmission of large items are as follows:

[0018] Collect the center of gravity position of large items at different time points during the transmission process, and set the initial center of gravity position of the item to be , at a certain time point t, the center of gravity position shifts, and the new center of gravity position is , the change of the center of gravity position represents the change of the center of gravity position of the object in three-dimensional space, where, is the coordinate of the center of gravity of the object’s initial position, is the coordinate of the center of gravity of the object at time point t;

[0019] Calculate the three-dimensional vector of the object's center of gravity offset. The center of gravity offset vector is expressed as the distance between the initial center of gravity position and the current center of gravity position. The specific expression is:

[0020] , where is the distance of the center of gravity of the item at time t;

[0021] After calculating the center of gravity offset distance, the directionality of the center of gravity offset is further evaluated through the offset angle. The angle between the initial center of gravity position and the current center of gravity position of the object is calculated to more accurately evaluate the offset state of the object in space. The calculation expression is:

[0022] , where It is the gravity center offset angle of the item at time t, reflecting the deviation between the offset direction of the item and the running direction of the conveyor. is the path vector of the chain conveyor turning, indicating the running track direction of the conveyor. Represents the product of the magnitudes of two vectors; Represents the center of gravity offset vector The modulus is the actual distance of the center of gravity of the large item at time t. Representation vector The modulus length represents the vector of the turning path or running trajectory of the chain conveyor;

[0023] Combining the center of gravity offset distance and the center of gravity offset angle, the quantitative reference value of the center of gravity offset is calculated. The calculation expression is:

[0024] , where It is the critical load factor of the chain conveyor, which is used to limit the deviation of the center of gravity of the items. is the moment of inertia of the object, which represents the resistance to the rotation of the object's center of gravity. It is the velocity component of the object at the turn, which determines the effect of the center of gravity deviation of the object at different speeds on the overall stability. Quantitative reference value for the center of gravity offset of large items at time point t.

[0025] Preferably, when a large item passes through a bend of a chain conveyor, the specific steps of analyzing the pressure change on the chain at the bend to generate a quantitative reference value of the chain tension are as follows:

[0026] Real-time monitoring of the pressure changes of the chain at the bend, collecting the instantaneous pressure data of the chain through the pressure sensor, and using Indicates the instantaneous pressure value at time t;

[0027] Calculate the pressure change of the chain at the turn and obtain the pressure change amplitude at each time point. The calculation expression is: , where represents the pressure change amplitude at time point t, and T represents the sampling time interval;

[0028] The pressure variation is characterized and the quantitative reference value of the chain tension is calculated to quantify the instantaneous pressure variation amplitude of the chain at the bend. The calculation expression is: , where It represents the quantitative reference value of the chain tension of the chain conveyor at time point t, is the turning angle, is the chain length, reflecting the effective range of tension transmission.

[0029] Preferably, the maximum initial transmission speed of the large items is regulated, and the specific steps are:

[0030] The current transmission stability evaluation coefficient is obtained from the support vector machine model, and the transmission stability evaluation coefficient is compared and analyzed with the first gradient reference threshold and the second gradient reference threshold to divide the transmission status of large items. The specific expression is: , where Indicates the adjusted initial transmission speed, Indicates the maximum initial transmission speed, and is the deceleration coefficient, and , Used for transmission of partially stable conditions, Used in situations where transmission is unstable, the deceleration factor is used to adjust the transmission speed in stages.

[0031] Preferably, the actual transmission speed is calculated based on the weight of the large item, the size of the large item, and the turning radius, and the actual transmission speed is dynamically adjusted. The specific control expression is:

[0032] , where m Indicates the mass of large items. s Indicates the volume of an item. r Indicates the radius of the chain conveyor's turning point. Indicates the actual transmission speed after real-time monitoring and adjustment. and Respectively represent the transmission stability evaluation coefficients at the current moment and the previous moment, Indicates the time interval between two samples.

[0033] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0034] The present invention obtains the instantaneous dynamic change information of large items at the turning points of the chain conveyor in real time, and uses the support vector machine model to predict and evaluate the transmission environment. It can accurately grasp the state of the items during the transmission process. According to the dynamic changes of the items, the system can timely adjust the maximum initial transmission speed to achieve graded regulation to adapt to different transmission scenarios and ensure the safety and stability of the items at the turning points. Compared with the traditional fixed low-speed transmission method, the intelligent control scheme can more effectively prevent the items from tilting, shaking or falling at the turning points, thereby significantly reducing the safety risks in transportation and improving the efficiency of item transmission, with a wider range of applicability.

[0035] The present invention dynamically adjusts the transmission speed and selects the minimum actual transmission speed after multiple adjustments at the same time, ensuring that each turn in the transmission process meets the stability requirements while completing the transmission task with high efficiency. This method is particularly effective in a chain conveyor system with multiple turns, avoiding excessive restriction of the transmission speed at a single turn, which would lead to bottleneck problems in the overall system. Especially during peak hours or when processing urgent orders, it can significantly improve the overall operating efficiency, reduce delays in order processing, and enhance the overall operational efficiency and customer satisfaction of the warehouse management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0037] Figure 1 This is a module schematic diagram of a warehouse management system based on big data in the present invention. DETAILED DESCRIPTION

[0038] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0039] The present invention provides Figure 1 A warehouse management system based on big data is shown, comprising an initial speed setting module, a dynamic information collection module, a feature extraction and transmission environment perception module, an intelligent model prediction module, a hierarchical speed control module, a speed data set generation module, and a minimum speed screening and transmission module;

[0040] The initial speed setting module places large items of the same batch on the chain conveyor and sets the maximum initial transmission speed for item transmission;

[0041] The maximum initial transmission speed refers to the highest transmission speed set when large items begin to be transmitted. This speed is set after comprehensive consideration of factors such as the weight, volume, shape of the items, the design capacity of the chain conveyor, and the operating environment. Its purpose is to maximize the transmission efficiency while ensuring safe and stable transmission, especially in the absence of obvious external unstable factors, so that large items can pass through the chain conveyor at the highest safe speed. The setting of the maximum initial transmission speed also needs to take into account possible subsequent dynamic adjustments to meet the transmission needs of items at turns or other special scenarios.

[0042] The key to this step is to improve overall operational efficiency through fast transmission at maximum speed, especially during peak hours when high throughput is required. Unlike traditional fixed low-speed settings, this strategy allows the time for items to be transported to be shortened as much as possible under normal circumstances, gaining more time for subsequent processing.

[0043] The setting of the maximum initial transmission speed should take into account multiple factors, including the weight, volume, and material of the large items, as well as the design characteristics and load capacity of the chain conveyor. First, a safe starting speed range can be determined by analyzing the conveying data of similar items in the past. Secondly, it is necessary to refer to the mechanical performance indicators of the chain conveyor, such as maximum load, turning radius, and friction coefficient, to ensure that sufficient stability and safety are maintained when running at high speeds. In addition, it is recommended to conduct a small-scale test during the initial setting and gradually adjust the speed to find the best balance point.

[0044] Dynamic information collection module, when the large items pass through the turning point of the chain conveyor, it can obtain the instantaneous transmission dynamic change information of the large items and the instantaneous dynamic change information of the turning point of the chain conveyor in real time;

[0045] The feature extraction and transmission environment perception module extracts features from the collected dynamic change information, analyzes the extracted features, and makes a preliminary perception of the stability of the transmission environment for large items through the analyzed features;

[0046] The intelligent model prediction module inputs the analyzed features into the pre-trained support vector machine model, uses the support vector machine model to predict the dynamic scene at the turning point of the chain conveyor, and evaluates the transmission stability under the current conditions;

[0047] When large items pass through the turning of the chain conveyor, the dynamic change information of the transmission of the large items obtained includes the center of gravity offset at the turning of the chain conveyor during the transmission of the large items, and the instantaneous dynamic change information at the turning of the chain conveyor obtained includes the pressure change on the chain at the turning. After analyzing the center of gravity offset at the turning of the chain conveyor during the transmission of the large items, a center of gravity offset quantitative reference value is generated, and the degree of offset of the center of gravity position of the large items relative to the original center of gravity during the transmission process is quantified through the center of gravity offset quantitative reference value. After analyzing the pressure change on the chain at the turning, a chain tension quantitative reference value is generated, and the change amplitude of the instantaneous pressure on the chain at the turning is quantified through the chain tension quantitative reference value. The stability of the transmission environment for large items is initially perceived through the analyzed center of gravity offset quantitative reference value and chain tension quantitative reference value.

[0048] After obtaining the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension, the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension are input into the pre-trained support vector machine model, and a transmission stability evaluation coefficient is generated based on the model. The transmission stability evaluation coefficient is used to perform an intelligent evaluation of the transmission stability of items at the turning point of the chain conveyor.

[0049] A pre-trained support vector machine (SVM) model is a model built by training a large amount of historical data. The model can perform classification or regression prediction based on the input data (in this scenario, the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension) to evaluate the stability of the item transmission at the corner of the chain conveyor. During the model training process, the support vector machine learns a set of historical samples, each of which contains input features (such as the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension) and the corresponding output label (such as the classification label of whether the item transmission is stable). The support vector machine model optimizes the mathematical function to find an optimal hyperplane (or decision boundary) to divide the samples into different categories or output values.

[0050] In the scenario of transmission stability assessment, the pre-trained support vector machine model has been tuned and optimized to know how to judge the stability of the item based on the specific center of gravity offset and chain tension pattern. Specifically, by calculating the position of the input features on the decision boundary, the support vector machine model can predict the transmission stability corresponding to these feature combinations, generate a transmission stability assessment coefficient, and evaluate whether the item is stably transmitted at the turn in the current situation. The support vector machine model can be a linear or nonlinear model, depending on the relationship between the center of gravity offset of the item and the chain tension. By using kernel functions (such as Gaussian kernels or polynomial kernels), complex nonlinear relationships can be processed, further improving the accuracy of the transmission stability assessment.

[0051] When large items pass through the turning of the chain conveyor, if the center of gravity is offset greatly during the transmission process, it will indeed cause the transmission of the items to be extremely unstable. This is because the center of gravity position of the item determines its balance under force. During the turning process, the items are not only affected by gravity, but also by additional forces such as centrifugal force and inertia. If the center of gravity is offset, the force balance of the item will be broken, causing it to easily tilt, shake or even roll over when turning. Especially for large items, due to their large size and weight, the increase in the center of gravity offset will aggravate the impact of these additional forces, thereby amplifying their instability. Therefore, when the center of gravity of large items is offset greatly, it will significantly increase the instability of the transmission, affecting the safety and reliability of the entire conveying process.

[0052] The specific steps to generate a quantitative reference value of the center of gravity offset after analyzing the center of gravity offset at the turning point of the chain conveyor during the transmission of large items are as follows:

[0053] Collect the center of gravity position of large items at different time points during the transmission process, and set the initial center of gravity position of the item to be , at a certain time point t, the center of gravity position shifts, and the new center of gravity position is , the change of the center of gravity position represents the change of the center of gravity position of the object in three-dimensional space, where, is the coordinate of the center of gravity of the object’s initial position, is the coordinate of the center of gravity of the object at time point t;

[0054] When collecting the center of gravity position of large items at different time points during the transmission process, a variety of existing technologies can be used. These technologies can monitor the changes in the center of gravity position of the items in real time to ensure the safety and stability of the items during the transmission process. The following are some commonly used technical methods and their detailed descriptions:

[0055] 3D Laser Scanning;

[0056] 3D laser scanning technology uses LiDAR or other laser devices to emit light beams to capture point cloud data on the surface of an object, thereby accurately calculating the 3D shape and center of gravity of the object. During the transmission process, the laser scanning device can monitor the position change and shape of the object in real time, thereby calculating the center of gravity at different time points. This method is particularly suitable for large objects because it can provide high-precision 3D data to ensure the accuracy of center of gravity monitoring.

[0057] Inertial Measurement Unit (IMU);

[0058] IMU is a device that measures the acceleration, inclination and rotation angle of an object through sensors such as accelerometers and gyroscopes. By fixing the IMU device on a large object, the posture changes of the object during movement can be obtained in real time, and the changes in the center of gravity of the object can be calculated based on the acceleration and inclination. IMU technology is light and easy to use, and is suitable for monitoring large objects in dynamic environments.

[0059] Vision Tracking System;

[0060] The visual tracking system uses cameras and computer vision algorithms to track the position of objects in space. By attaching markers to the surface of the object, the camera can monitor the dynamic changes of the object such as displacement and tilt in real time. Combined with image processing technology, the system can measure the center of gravity of the object at different time points through the three-dimensional coordinates of multiple cameras. This method is widely used in logistics and industrial automation, and has good flexibility and real-time performance.

[0061] Calculate the three-dimensional vector of the object's center of gravity offset. The center of gravity offset vector is expressed as the distance between the initial center of gravity position and the current center of gravity position. The specific expression is:

[0062] , where is the distance of the center of gravity of the item at time t;

[0063] This formula quantifies the overall offset of the center of gravity of an item in three-dimensional space.

[0064] After calculating the center of gravity offset distance, the directionality of the center of gravity offset is further evaluated through the offset angle. The angle between the initial center of gravity position and the current center of gravity position of the object is calculated to more accurately evaluate the offset state of the object in space. The calculation expression is:

[0065] , where It is the gravity center offset angle of the item at time t, reflecting the deviation between the offset direction of the item and the running direction of the conveyor. is the path vector of the chain conveyor turning, indicating the running track direction of the conveyor. Represents the product of the magnitudes (or lengths) of two vectors; Represents the center of gravity offset vector The modulus is the actual distance of the center of gravity of the large item at time t. Representation vector The modulus length represents the vector of the turning path or running trajectory of the chain conveyor.

[0066] Combining the center of gravity offset distance and the center of gravity offset angle, the quantitative reference value of the center of gravity offset is calculated. The calculation expression is:

[0067] , where It is the critical load factor of the chain conveyor, which is used to limit the deviation of the center of gravity of the items. is the moment of inertia of the object, which represents the resistance to the rotation of the object's center of gravity. It is the velocity component of the object at the turn, which determines the effect of the center of gravity deviation of the object at different speeds on the overall stability. Quantify the reference value of the center of gravity offset of large items at time point t;

[0068] Quantitative reference value of center of gravity offset The system combines the deviation amplitude, angle, item inertia and critical load state of the conveying system to effectively quantify the degree of center of gravity deviation of large items at turns, accurately reflects the stability of items during transportation, and helps optimize transportation operations.

[0069] The range of critical load factors depends on the specific design and operation requirements of the system, and is usually determined by the mechanical properties of the chain conveyor, the physical properties of large items (such as weight, volume), and the safety margin of the system. Although the specific value of the critical load factor varies according to the actual system and equipment characteristics, it usually fluctuates in the range of 0.5 to 2.0. For lighter loads, the factor may be as low as 0.5, while for heavier and complex load scenarios, the critical load factor may be close to 2.0 or higher, but generally should not exceed the design limit of the equipment.

[0070] It can be seen from the quantitative reference value of the center of gravity shift that the larger the performance value of the quantitative reference value of the center of gravity shift generated after analyzing the center of gravity shift at the turning point of the chain conveyor during the transmission of large items, it usually means that the center of gravity of the large items is shifted during the transmission process. This indicates that the stability of the items at the turning point of the chain conveyor is worse. When the center of gravity shift is large, the deviation between the center of gravity of the item and the original position is large, which makes the item prone to tilting, shaking or instability, thereby increasing the risk of the item falling or being damaged. On the contrary, the smaller the quantitative reference value of the center of gravity shift, the smaller the change in the center of gravity of the item, which means that the item maintains a good balance and stability during the turning process. Therefore, the lower the quantitative reference value of the center of gravity shift, it usually means that the stability of the item is better during the transmission process.

[0071] When large items pass through the bends of a chain conveyor, if the chain is subjected to a large change in instantaneous pressure, it can indeed cause the transport of large items to be extremely unstable. This is because the center of gravity of the items will shift during the bend of the chain conveyor, causing the chain to bear additional lateral force. Drastic changes in instantaneous pressure usually indicate that the tension or stress state of the chain is constantly fluctuating, which may cause the chain to relax or become overly tense, thereby affecting its conveying capacity. When the chain is subjected to uneven stress, the stability of large items will be threatened, and they may tilt, shake, or fall.

[0072] When large items pass through the bend of the chain conveyor, the specific steps for analyzing the pressure changes on the chain at the bend and generating a quantitative reference value for the chain tension are as follows:

[0073] Real-time monitoring of the pressure changes of the chain at the bend, collecting the instantaneous pressure data of the chain through the pressure sensor, and using Indicates the instantaneous pressure value at time t;

[0074] Calculate the pressure change of the chain at the turn and obtain the pressure change amplitude at each time point. The calculation expression is: , where represents the pressure change amplitude at time point t, and T represents the sampling time interval;

[0075] This step calculates the difference between the current instantaneous pressure and the pressure at the last sampling moment.

[0076] The pressure variation is characterized and the quantitative reference value of the chain tension is calculated to quantify the instantaneous pressure variation amplitude of the chain at the bend. The calculation expression is:

[0077] , where It represents the quantitative reference value of the chain tension of the chain conveyor at time point t, is the turning angle (radians), is the chain length, reflecting the effective range of tension transmission.

[0078] It can be seen from the quantitative reference value of chain tension that when large items pass through the bend of the chain conveyor, the larger the performance value of the quantitative reference value of chain tension generated after analyzing the pressure change of the chain at the bend, it usually means that the pressure change of the chain at the bend is greater, indicating that there are unstable factors such as large center of gravity offset, inertia or centrifugal force in the transmission process of the items. Therefore, the larger the quantitative reference value of chain tension, the worse the transmission stability of large items at the bend, and there is a risk of tilting, shaking or falling. On the contrary, if the quantitative reference value of chain tension is small, it means that the pressure change of the chain at the bend is small, the center of gravity of the item is relatively stable, the transmission process is smoother, and the stability is better.

[0079] The support vector machine model is not specifically limited here, and can achieve the quantitative reference value of the center of gravity offset of large items at time point t and the quantitative reference value of the chain tension of the chain conveyor at time t Comprehensive analysis to generate transmission stability assessment coefficients The support vector machine model can be used. In order to implement the technical solution of the present invention, the present invention provides a specific implementation method; the transmission stability evaluation coefficient The resulting calculation formula is: , where , are the quantitative reference values ​​of the center of gravity offset of large items at time point t and the quantitative reference value of the chain tension of the chain conveyor at time t The preset scaling factor of , Both are greater than 0.

[0080] It can be seen from the transmission stability evaluation coefficient that the larger the performance value of the quantitative reference value of the center of gravity offset generated after analyzing the center of gravity offset at the turning of the chain conveyor during the transmission of large items, the larger the performance value of the quantitative reference value of the chain tension generated after analyzing the pressure change on the chain at the turning, indicating that the stability of the item at the turning of the chain conveyor is worse, and vice versa, it indicates that the stability of the item at the turning of the chain conveyor is better.

[0081] The graded speed control module controls the maximum initial transmission speed of large items based on the prediction results of the support vector machine model to ensure the stability of the items when turning.

[0082] The maximum initial transmission speed of large items is regulated. The specific steps are as follows:

[0083] The current transmission stability evaluation coefficient is obtained from the support vector machine model, and the transmission stability evaluation coefficient is compared and analyzed with the first gradient reference threshold and the second gradient reference threshold to divide the transmission status of large items. The specific expression is: , where and denote the first gradient reference threshold and the second gradient reference threshold, respectively, and , Indicates the current transmission stability assessment coefficient;

[0084] when When , it indicates that the transmission is relatively stable and a higher initial transmission speed can be allowed. When the transmission has certain risks, the initial transmission speed should be appropriately reduced. When the transmission environment is unstable, the initial transmission speed needs to be greatly reduced. , These are two thresholds set based on historical data and experience, and are used to divide the transmission status.

[0085] Based on the comparison results of the transmission stability evaluation coefficient with the first gradient reference threshold and the second gradient reference threshold, the maximum initial transmission speed is preliminarily adjusted. The adjustment expression is:

[0086] , where Indicates the adjusted initial transmission speed, Indicates the maximum initial transmission speed, and is the deceleration coefficient, and , Used for transmission of partially stable conditions, Used in cases where the transmission is unstable, the deceleration factor is used to adjust the transmission speed in stages;

[0087] The deceleration factor is not specifically limited here and can be flexibly adjusted according to actual conditions and needs. and Can be set to different values ​​to achieve optimal transmission efficiency and security.

[0088] Combined with the weight of large items, the size of large items and the turning radius, the actual transmission speed is calculated and dynamically adjusted to ensure that the speed adjustment meets the safe operation requirements of the built objects and equipment. The specific control expression is:

[0089] , where m Indicates the mass of large items.s Indicates the volume of an item. r Indicates the radius of the chain conveyor's turn. A smaller radius usually requires a lower transmission speed. Indicates the actual transmission speed after real-time monitoring and adjustment. and Respectively represent the transmission stability evaluation coefficients at the current moment and the previous moment, Indicates the time interval between two samplings;

[0090] The purpose of this step is to:

[0091] According to the change of transmission stability evaluation coefficient (i.e. ) to adjust the speed. If the stability of the transmission environment fluctuates greatly (i.e. Large), actual transmission speed will be reduced accordingly. The proportional coefficient dynamically reduces the speed according to the degree of instability. This can effectively deal with sudden unstable situations during transmission and prevent items from tilting or falling due to excessive transmission speed under unstable conditions.

[0092] This control mechanism enables the speed to be dynamically adjusted according to real-time conditions, thus avoiding the fixed speed problem in traditional methods and ensuring optimal conveying efficiency under different operating conditions.

[0093] The speed data set generation module, when the speed control is performed more than once at the same time, creates a data set of the actual transmission speed after the control, and sorts the actual transmission speeds in the data set in order;

[0094] The minimum speed screening and transmission module, after the data set is established, screens out the minimum actual transmission speed, and transmits items on the chain conveyor at the screened actual transmission speed;

[0095] The purpose of this step is to ensure that the items can be transported at the safest and most stable speed in a complex, multi-turn chain conveying environment, avoiding unstable transmission due to inconsistencies at different turns. When a multi-turn chain conveyor handles multiple complex turns at the same time, the transmission environment at each turn may be quite different. Therefore, the system may perform multiple speed controls for different turns at the same time, with the aim of adjusting the transmission speed of the items based on the real-time dynamic information of each turn to ensure that safety and stability requirements are met at each point. In these cases, multiple turns may have different speed control requirements, so higher speeds are allowed, while other turns may require significantly reduced speeds. By aggregating these regulated actual transmission speeds into a data set and sorting them, it is possible to ensure that the minimum speed for all turns is determined. Screening out the minimum actual transmission speed means selecting the safest speed suitable for all turns, avoiding instability caused by overspeed transmission at any turn.

[0096] This approach is particularly important in addressing the complexity of multi-turn environments: the different requirements of multiple turns may result in different safety speeds required at each point. If the transmission is carried out only at a higher speed set at a certain turn, other turns with stricter requirements may cause the items to tilt, slip or fall. By selecting the minimum transmission speed, it is ensured that even at the most challenging turns, the items can still pass stably and safely.

[0097] In addition, the method of sorting and screening the minimum actual transmission speed can effectively avoid frequent speed adjustments and improve the stability and consistency of system operation. For the system, each speed adjustment may increase the complexity of the chain conveyor, and multiple adjustments may affect the overall operating efficiency. Through this strategy, the system only needs to adjust to the minimum transmission speed once, avoiding frequent speed switching, and improving the efficiency and stability of logistics transmission.

[0098] In short, in a multi-turn environment, screening the minimum actual transmission speed ensures that items can be transmitted at a safe speed that meets all turn requirements, minimizing transportation risks while simplifying speed management during the transmission process, thereby improving the overall operating efficiency and safety of the system.

[0099] The present invention obtains the instantaneous dynamic change information of large items at the turning points of the chain conveyor in real time, and uses the support vector machine model to predict and evaluate the transmission environment. It can accurately grasp the state of the items during the transmission process. According to the dynamic changes of the items, the system can timely adjust the maximum initial transmission speed to achieve graded regulation to adapt to different transmission scenarios and ensure the safety and stability of the items at the turning points. Compared with the traditional fixed low-speed transmission method, the intelligent control scheme can more effectively prevent the items from tilting, shaking or falling at the turning points, thereby significantly reducing the safety risks in transportation and improving the efficiency of item transmission, with a wider range of applicability.

[0100] The present invention dynamically adjusts the transmission speed and selects the minimum actual transmission speed after multiple adjustments at the same time, ensuring that each turn in the transmission process meets the stability requirements while completing the transmission task with high efficiency. This method is particularly effective in a chain conveyor system with multiple turns, avoiding excessive restriction of the transmission speed at a single turn, which would lead to bottleneck problems in the overall system. Especially during peak hours or when processing urgent orders, it can significantly improve the overall operating efficiency, reduce delays in order processing, and enhance the overall operational efficiency and customer satisfaction of the warehouse management system.

[0101] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0102] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0103] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A warehouse management system based on big data, characterized in that: It includes an initial speed setting module, a dynamic information collection module, a feature extraction and transmission environment perception module, an intelligent model prediction module, a graded speed control module, a speed data set generation module, and a minimum speed screening and transmission module; The initial speed setting module places large items of the same batch on the chain conveyor and sets the maximum initial transmission speed for item transmission; Dynamic information collection module, when the large items pass through the turning point of the chain conveyor, it can obtain the instantaneous transmission dynamic change information of the large items and the instantaneous dynamic change information of the turning point of the chain conveyor in real time; The feature extraction and transmission environment perception module extracts features from the collected dynamic change information, analyzes the extracted features, and makes a preliminary perception of the stability of the transmission environment for large items through the analyzed features; Among them, when the large items pass through the turning of the chain conveyor, the obtained transmission dynamic change information of the large items includes the center of gravity offset at the turning of the chain conveyor during the transmission of the large items, and the obtained instantaneous dynamic change information at the turning of the chain conveyor includes the pressure change of the chain at the turning. After analyzing the center of gravity offset at the turning of the chain conveyor during the transmission of the large items, a center of gravity offset quantitative reference value is generated, and the degree of offset of the center of gravity position of the large items relative to the original center of gravity during the transmission process is quantified by the center of gravity offset quantitative reference value. After analyzing the pressure change of the chain at the turning, a chain tension quantitative reference value is generated, and the change amplitude of the instantaneous pressure on the chain at the turning is quantified by the chain tension quantitative reference value. The stability of the transmission environment of large items is preliminarily perceived through the analyzed center of gravity offset quantitative reference value and chain tension quantitative reference value; The intelligent model prediction module inputs the analyzed features into the pre-trained support vector machine model, uses the support vector machine model to predict the dynamic scene at the turning point of the chain conveyor, and evaluates the transmission stability under the current conditions; After obtaining the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension, the quantitative reference value of the center of gravity offset and the quantitative reference value of the chain tension are input into the pre-trained support vector machine model, and a transmission stability evaluation coefficient is generated based on the model. The transmission stability evaluation coefficient is used to perform an intelligent evaluation of the transmission stability of items at the turning point of the chain conveyor; The graded speed control module controls the maximum initial transmission speed of large items based on the prediction results of the support vector machine model to ensure the stability of the items when turning. Among them, the actual transmission speed is calculated based on the weight of the large items, the size of the large items and the turning radius, and the actual transmission speed is dynamically adjusted. The specific control expression is: , where m Indicates the mass of large items. s Indicates the volume of an item. r Indicates the radius of the chain conveyor's turning point. Indicates the actual transmission speed after real-time monitoring and adjustment. and Respectively represent the transmission stability evaluation coefficients at the current moment and the previous moment, represents the time interval between two samples, Indicates the adjusted initial transmission speed, represents the second gradient reference threshold; The speed data set generation module, when the speed control is performed more than once at the same time, creates a data set of the actual transmission speed after the control, and sorts the actual transmission speeds in the data set in order; The minimum speed screening and transmission module, after the data set is established, screens out the minimum actual transmission speed, and transmits items on the chain conveyor at the screened actual transmission speed.

2. The warehouse management system based on big data according to claim 1 is characterized in that: The maximum initial transmission speed refers to the highest transmission speed set when large items begin to be transmitted. Its purpose is to ensure that large items can pass through the chain conveyor at the highest safe speed under the premise of ensuring safe and stable transmission.

3. The warehouse management system based on big data according to claim 1 is characterized in that: The specific steps to generate a quantitative reference value of the center of gravity offset after analyzing the center of gravity offset at the turning point of the chain conveyor during the transmission of large items are as follows: Collect the center of gravity position of large items at different time points during the transmission process, and set the initial center of gravity position of the item to be , at a certain time point t, the center of gravity position shifts, and the new center of gravity position is , the change of the center of gravity position represents the change of the center of gravity position of the object in three-dimensional space, where, is the coordinate of the center of gravity of the object’s initial position, is the coordinate of the center of gravity of the object at time point t; Calculate the three-dimensional vector of the object's center of gravity offset. The center of gravity offset vector is expressed as the distance between the initial center of gravity position and the current center of gravity position. The specific expression is: , where is the distance of the center of gravity of the item at time t; After calculating the center of gravity offset distance, the directionality of the center of gravity offset is evaluated by the offset angle. The angle between the initial center of gravity position and the current center of gravity position of the object is calculated to evaluate the offset state of the object in space. The calculation expression is: , where It is the gravity center offset angle of the item at time t, reflecting the deviation between the offset direction of the item and the running direction of the conveyor. is the path vector of the chain conveyor turning, indicating the running track direction of the conveyor. Represents the product of the magnitudes of two vectors; Represents the center of gravity offset vector The modulus is the actual distance of the center of gravity of the large item at time t. Representation vector The modulus length represents the vector of the turning path or running trajectory of the chain conveyor; Combining the center of gravity offset distance and the center of gravity offset angle, the quantitative reference value of the center of gravity offset is calculated. The calculation expression is: , where It is the critical load factor of the chain conveyor, which is used to limit the deviation of the center of gravity of the items. is the moment of inertia of the object, which represents the resistance to the rotation of the object's center of gravity. It is the velocity component of the object at the turn, which determines the effect of the center of gravity deviation of the object at different speeds on the overall stability. Quantitative reference value for the center of gravity offset of large items at time point t.

4. The warehouse management system based on big data according to claim 1 is characterized in that: When large items pass through the bend of the chain conveyor, the specific steps for analyzing the pressure changes on the chain at the bend and generating a quantitative reference value for the chain tension are as follows: Real-time monitoring of the pressure changes of the chain at the bend, collecting the instantaneous pressure data of the chain through the pressure sensor, and using Indicates the instantaneous pressure value at time t; Calculate the pressure change of the chain at the turn and obtain the pressure change amplitude at each time point. The calculation expression is: , where represents the pressure change amplitude at time point t, and T represents the sampling time interval; The pressure variation is characterized and the quantitative reference value of the chain tension is calculated to quantify the instantaneous pressure variation amplitude of the chain at the bend. The calculation expression is: , where It represents the quantitative reference value of the chain tension of the chain conveyor at time point t, is the turning angle, is the chain length, reflecting the effective range of tension transmission.

5. The warehouse management system based on big data according to claim 1, characterized in that: The maximum initial transmission speed of large items is regulated. The specific steps are as follows: The current transmission stability evaluation coefficient is obtained from the support vector machine model, and the transmission stability evaluation coefficient is compared and analyzed with the first gradient reference threshold and the second gradient reference threshold to divide the transmission status of large items. The specific expression is: , where represents the first gradient reference threshold, and , Indicates the current transmission stability assessment coefficient; Based on the comparison results of the transmission stability evaluation coefficient with the first gradient reference threshold and the second gradient reference threshold, the maximum initial transmission speed is preliminarily adjusted. The adjustment expression is: , where Indicates the maximum initial transmission speed, and is the deceleration coefficient, and , Used for transmission part stability. Used in situations where transmission is unstable, the deceleration factor is used to adjust the transmission speed in stages.

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