A dynamic monitoring system for the connection of F-TR locking hooks in railway container loading and unloading operations

Abstract

The present application relates to the technical field of monitoring lifting equipment, and specifically to a dynamic monitoring system for F-TR lock hooking in railway container loading and unloading operations. The system comprises: obtaining tension data of each lifting point of a crane; dividing the lifting process into multiple lifting periods; obtaining the significant value of abnormal increase of a single lifting point position in each lifting period, and obtaining the tension abnormality coefficient of a single lifting point position in each lifting period in combination with the degree of irregularity of the tension data of the single lifting point position in each lifting period; obtaining the asynchronous coefficient of each lifting period based on the degree of correlation between the tension data of all two arbitrary lifting point positions in each lifting period, and the difference in the tension abnormality coefficient of all two arbitrary lifting point positions in each lifting period; obtaining the continuous significant coefficient at the current moment, and comparing it with the preset threshold to determine whether F-TR lock hooking occurs. The present application improves the monitoring accuracy of F-TR lock hooking by analyzing the multi-dimensional characteristics of tension data during the lifting process.

Description

Technical Field

[0001] The present application relates to the technical field of lifting device monitoring, and in particular to a dynamic monitoring system for F-TR lock couplings in railway container loading and unloading operations. Background Art

[0002] As an advanced, modern mode of transportation, container transport boasts higher efficiency and better economic benefits compared to traditional bulk transport. Its application in my country's railway freight sector is becoming increasingly widespread, and numerous loading and unloading machines and safety devices adapted to containerization have been developed and deployed. The new F-TR lock is widely used in my country's railway container transport to ensure container stability during transport and prevent overturning.

[0003] The F-TR lock is a key component used by container flat cars to lock and secure containers. During the process of loading and unloading containers using cranes, if the container corner fittings do not move smoothly in and out of the F-TR locks, the container may not be locked in place and the F-TR locks may be hooked during lifting. In addition, container overloading, severe deformation of container corner fittings, and shaking during transportation can easily cause the F-TR locks to become hooked. The existing technology collects the tension values of four tension sensors connected to the lifting sling. When the deviation between the tension change value of a certain tension sensor and the tension change value of another or several other tension sensors exceeds a set threshold, it is detected that the container and the F-TR locks corresponding to the tension sensor above and below are hooked. However, even if the F-TR locks do not become hooked, if the container is overloaded, it may also cause abnormal differences in the tension values of different lifting points. The existing method only analyzes the difference characteristics of the tension values of different lifting points to determine whether the F-TR lock hook phenomenon has occurred. It does not analyze the characteristics of the F-TR lock hook phenomenon from multiple angles. It has certain limitations, resulting in a low accuracy rate in the dynamic monitoring of F-TR lock hooking. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a dynamic monitoring system for F-TR lock coupling in railway container loading and unloading operations. The technical solutions adopted are as follows:

[0005] This application proposes a dynamic monitoring system for F-TR lock coupling in railway container loading and unloading operations, the system comprising:

[0006] Lifting process data acquisition module: real-time acquisition of the tension data of each lifting point of the crane during the container lifting process;

[0007] Crane lifting process analysis module: The container lifting process is evenly divided into multiple lifting periods; the slope of each tension data is obtained based on the fitting curve of the tension data of each lifting point position in each lifting period; the mutation data of each lifting point position in each lifting period is obtained based on the mutation point in the slope of all tension data of each lifting point position in each lifting period; the abnormal increase significance value of the single lifting point position in each lifting period is obtained based on the average level of all mutation data of the single lifting point position in each lifting period and the difference between each two adjacent tension data of the single lifting point position in each lifting period, and the tension abnormality coefficient of the single lifting point position in each lifting period is obtained based on the irregularity of the tension data of the single lifting point position in each lifting period; the positive correlation factor of each lifting period is obtained based on the correlation between the tension data of all two arbitrary lifting point positions in each lifting period, and the asynchronous coefficient of each lifting period is obtained based on the difference between the tension abnormality coefficients of all two arbitrary lifting point positions in each lifting period; the persistent significant coefficient at the current moment is obtained based on the difference between the asynchronous coefficients between adjacent lifting periods in all lifting periods before the current moment;

[0008] F-TR lock hook dynamic monitoring module: compares the current moment's continuous significance coefficient with the preset abnormal threshold to determine whether F-TR lock hook occurs at the current moment.

[0009] Preferably, the specific process of evenly dividing the container lifting process into a plurality of lifting periods is: continuously dividing the monitoring time in the lifting process from front to back into a plurality of lifting periods according to a fixed time length.

[0010] Preferably, the specific process of obtaining the slope of each tension data is: obtaining a fitting curve of the tension data at each lifting point position in each lifting period, and taking the value of each tension data in the differential equation of its corresponding fitting curve as the slope of each tension data.

[0011] Preferably, the specific process of obtaining the mutation data of each hanging point position in each lifting period is: arranging the slopes of the tension data of each hanging point position in each lifting period in chronological order to obtain the slope sequence of each hanging point position in each lifting period; obtaining the mutation points in the slope sequence of each hanging point position in each lifting period, and recording the data corresponding to the mutation points in the slope sequence as mutation data.

[0012] Preferably, the calculation formula for the significant value of abnormal increase in the position of a single lifting point in each lifting period is: Where, is the significant value of abnormal increase in the position of a single lifting point during the i-th lifting period, is the mean of all mutation data of a single lifting point position during the i-th lifting period, represents a logarithmic function with base 2, N represents the total number of tension data at a single lifting point during the i-th lifting period, 、 They respectively represent the slope values of the j-th and j-1-th tension data of a single lifting point position in the i-th lifting period.

[0013] Preferably, the process of obtaining the tension anomaly coefficient of a single lifting point position in each lifting period is: calculating the fractal dimension of the tension data of a single lifting point position in each lifting period; and recording the product of the abnormal increase significance value of the single lifting point position in each lifting period and the fractal dimension as the tension anomaly coefficient of the single lifting point position in each lifting period.

[0014] Preferably, the process of obtaining the positive correlation factor of each lifting period is: calculating the sum of the Spearman correlation coefficient between the tension data corresponding to all any two lifting point positions in each lifting period and 1, and recording the mean of all sum values as the positive correlation factor of the i-th lifting period.

[0015] Preferably, the calculation formula for the asynchronous coefficient of each lifting period is: Where, represents the asynchronous coefficient of the i-th lifting period, It represents the mean of the difference between the abnormal tension coefficients of any two lifting points in the i-th lifting period. Represents the positive correlation factor of the i-th lifting period.

[0016] Preferably, the expression of the persistent significant coefficient at the current moment is: Where, It represents the continuous significance index at the current moment, s represents the position value of the previous lifting period before the lifting period at the current moment, and They represent the asynchronous coefficients of the i-th lifting period and the i+1-th lifting period respectively.

[0017] Preferably, the specific process of determining whether F-TR lock hooking occurs at the current moment is as follows: if the normalized result of the persistent significance index is greater than or equal to a preset abnormality threshold, it is determined that F-TR lock hooking occurs when the crane is lifting at the current moment; otherwise, it is determined that F-TR lock hooking does not occur when the crane is lifting at the current moment.

[0018] This application has the following beneficial effects:

[0019] This application addresses the problem that most existing monitoring technologies use the method of whether there is a significant deviation between some tension values and other tension values to determine whether there is a hooking, resulting in low monitoring accuracy. By installing tension sensors at the four lifting points of the crane to collect tension data in real time, the abnormal characteristics of the tension data at each lifting point, the coordinated characteristics of the tension changes at different lifting points, and the differences in the abnormal tension characteristics in the adjacent time windows are analyzed, a continuous significance index is constructed, and the characteristics of the F-TR lock when hooking occurs are analyzed from multiple angles. The temporal change trend of the abnormal force at multiple lifting points during the lifting process is dynamically tracked, which can effectively reduce the impact of container interference factors, thereby reducing the misjudgment rate of the F-TR lock hooking, realizing dynamic and accurate monitoring of the F-TR lock hooking status, and improving the monitoring accuracy of the F-TR lock hooking status. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 A block diagram of a dynamic monitoring system for F-TR lock coupling in railway container loading and unloading operations provided by one embodiment of the present application;

[0022] Figure 2 This is an analysis flow chart of a crane lifting process analysis module provided in one embodiment of the present application. DETAILED DESCRIPTION

[0023] To further illustrate the technical means and effectiveness of this application to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effectiveness of a dynamic monitoring system for F-TR lock couplings in railway container loading and unloading operations proposed in this application. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0024] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0025] The following describes in detail a specific scheme of a F-TR lock coupling dynamic monitoring system for railway container loading and unloading operations provided by the present application with reference to the accompanying drawings.

[0026] See also Figure 1 , which shows a block diagram of a F-TR lock connection dynamic monitoring system for railway container loading and unloading operations provided by an embodiment of the present application. The system includes: a lifting process data acquisition module, a crane lifting process analysis module, and an F-TR lock connection dynamic monitoring module.

[0027] Lifting process data acquisition module: real-time acquisition of the tension data of each lifting point of the crane during the container lifting process.

[0028] The F-TR lock has the function of preventing containers from tipping over and jumping up, ensuring the transportation safety of containers after the railway speed is increased. In order to facilitate the entry and exit of the container corner fittings into the lock, the installation direction of the lock on the vehicle is the same direction at each end and opposite directions at both ends. During the unlocking operation, the container needs to produce a small plane rotation of about 2.5° on the horizontal plane to allow the FT-R lock to be smoothly withdrawn. In some unconventional cases, when the container is unloaded, the corner fittings of the box lock hole will get stuck with the F-TR lock body and cannot be smoothly unhooked. In the hooked state, it will cause abnormalities in the tension data of the container lifting. Therefore, tension sensors are installed at the four lifting points of the crane to collect tension data during lifting. In this embodiment, the time interval for collecting tension data is 0.05 seconds. The implementer can set the time interval according to the actual situation. At this point, the tension data during the crane lifting process can be obtained.

[0029] Crane lifting process analysis module: The container lifting process is evenly divided into multiple lifting periods; the slope of each tension data is obtained based on the fitting curve of the tension data of each lifting point position in each lifting period; the mutation data of each lifting point position in each lifting period is obtained based on the mutation point in the slope of all tension data of each lifting point position in each lifting period; the abnormal increase significance value of the single lifting point position in each lifting period is obtained based on the average level of all mutation data of the single lifting point position in each lifting period and the difference between each two adjacent tension data of the single lifting point position in each lifting period, and the tension anomaly coefficient of the single lifting point position in each lifting period is obtained based on the irregularity of the tension data of the single lifting point position in each lifting period; the positive correlation factor of each lifting period is obtained based on the correlation between the tension data of all arbitrary two lifting point positions in each lifting period, and the asynchronous coefficient of each lifting period is obtained based on the difference between the tension anomaly coefficients of all arbitrary two lifting point positions in each lifting period; the persistent significant coefficient at the current moment is obtained based on the difference between the asynchronous coefficients between adjacent lifting periods in all lifting periods before the current moment.

[0030] The analysis process of the crane lifting process analysis module is as follows: Figure 2As shown. Specifically, when the container is placed on a railway flat car, the F-TR lock is in a locked state. Before unloading the container, the lock head must be turned back to the unlocked position before the container can be lifted. When the lock is hooked, the container cannot be lifted normally. The main reasons for the hooking of the F-TR lock include: insufficient rotation angle or excessive rotation angle; excessive mutual friction between the lock head and the lock body, resulting in failure to unhook normally; severe deformation of the container corner fittings. Lock hooking usually causes abnormal or asynchronous changes in tension data. For example, when a corner of the container is hooked, the tension value at the hooking position will suddenly increase or fluctuate frequently, causing the tension at different positions to be out of sync. Existing methods based on tension value monitoring determine whether the F-TR lock is hooked. They mainly determine whether there is hooking based on the abnormality or asynchrony of some tension values.

[0031] However, when loading and unloading cargo in containers, there is a situation where the distribution of cargo is not properly planned during packing. Operators’ loading and unloading habits usually prioritize placing cargo on the inside of the container. In addition, the nature of the cargo and the need for protection will also cause environmentally sensitive cargo to be placed on the inside. This causes the inside of the container to be filled more fully, while the outside near the door is filled less heavily, causing the center of gravity of the container to deviate from the geometric center of the container, thereby causing overloading. During the lifting process, the tension value corresponding to the heavier side will also be larger, resulting in an imbalance of tension during the lifting process, which in turn affects the judgment of whether the lock is hooked. Therefore, it is necessary to analyze the specific change characteristics of the tension data when the F-TR lock is in the hooked state, so as to improve the accuracy of the hooked state monitoring.

[0032] The lifting process of a crane is relatively slow, typically requiring more than ten or even dozens of seconds. This process is monitored dynamically in real time, with the monitoring time during the lifting process continuously divided into multiple lifting periods, each lasting w seconds. In this embodiment, w is 2. The following analysis is conducted using the tension data at a particular lifting point as an example. First, during normal lifting without hooking, the tension value may slowly increase, remaining relatively stable and changing evenly. However, after long-term use, the lock may deform or excessive friction may result in insufficient unhooking, causing the tension data during the lifting process to increase rapidly in the short term, or suddenly increase due to a stuck corner piece. Therefore, the rate of change can better reflect any abnormalities in tension. First, the least squares method is used to obtain a fitting curve for the tension data at each lifting point within each lifting period. The value of each tension data in the differential equation of the corresponding fitting curve is used as the slope of the tension data. The slopes of the tension data at each lifting point during each lifting period are arranged in chronological order to obtain a slope sequence for each lifting point during each lifting period. Because the slopes of the tension data in the connected state may exhibit sudden changes, the slope sequences for each lifting point during each lifting period are used as inputs to the Stochastic Outlier Selection (SOS) algorithm. The sudden change points in the slope sequence for each lifting point during each lifting period are obtained, and the data corresponding to the sudden change points in the slope sequence are recorded as sudden change data. The least squares method and the SOS algorithm are well-known techniques, and the specific process is not further described.

[0033] As a preferred embodiment, based on the average level of all mutation data of a single lifting point position in each lifting period and the difference between two adjacent tension data of a single lifting point position in each lifting period, the significant value of abnormal increase of a single lifting point position in each lifting period is obtained, which is used to characterize the possibility of abnormal increase characteristics of short-term rapid increase and significant mutation in a single lifting point position in each lifting period.

[0034] In this embodiment, the abnormal increase in the position of a single lifting point during the i-th lifting period is recorded as , its specific expression is: Where, is the significant value of abnormal increase in the position of a single lifting point during the i-th lifting period, is the mean of all mutation data of a single lifting point position during the i-th lifting period, represents a logarithmic function with base 2, N represents the total number of tension data at a single lifting point during the i-th lifting period, 、 They respectively represent the slope values of the j-th and j-1-th tension data of a single lifting point position in the i-th lifting period.

[0035] right The purpose of finding the logarithmic function is to prevent The value of is too large; The larger the value is, the more obvious the increase feature of the tension data at the slope mutation point is; The larger the value is, the more obvious the short-term rapid increase feature of the tension data is. The larger the value of , the greater the possibility that the position of a single lifting point has a short-term rapid increase and a significant mutation in the i-th lifting period.

[0036] Furthermore, the F-TR lock requires a certain degree of horizontal rotation to unlock. Due to insufficient or excessive rotation angles, as well as deformation from long-term use, the gap between the F-TR lock and the corner fitting is too small. The constant friction during lifting causes irregular and frequent fluctuations in the tension data, leading to cross-talk. To capture these irregular and frequent fluctuations, the Higuchi algorithm is used to further calculate the fractal dimension of the tension data at a single lifting point during the i-th lifting period. This value reflects the irregular variations in the tension data. The Higuchi algorithm is well known, and the specific process is not detailed here.

[0037] As a preferred embodiment, the abnormal increase significance value of the single lifting point position in each lifting period is combined with the fractal dimension of the tension data of the single lifting point position in each lifting period to obtain the tension abnormality coefficient of the single lifting point position in each lifting period, which is used to characterize the abnormal degree of irregular abnormal changes in the tension data of the single lifting point position due to continuous friction during the lifting process of the crane.

[0038] In this embodiment, the product of the significant abnormal increase value of a single lifting point position during the i-th lifting period and the fractal dimension is recorded as the tension anomaly coefficient for the single lifting point position during the i-th lifting period. A larger value of the tension anomaly coefficient indicates a more significant abnormal change in the tension data at the corresponding lifting point position during the corresponding lifting period.

[0039] In another embodiment of the present application, the sum of the abnormal increase significance value of the single lifting point position in the i-th lifting period and the fractal dimension is recorded as the tension abnormality coefficient of the single lifting point position in the i-th lifting period.

[0040] Furthermore, due to the uneven deviation of the container's center of gravity, crane operation will cause the container to tilt. The greater the container's tilt, the greater the difference in tension between the lifting points. As the tilt continues to increase, one end of the container will be unlocked and suspended off the flatbed, while the other end has not yet been unlocked. This causes the lock to hook with the container's corner fitting, creating an angle between the container's bottom plane and the flatbed body. This angle inevitably affects the smooth unlocking of the F-TR locking device. As a result, the tension changes at various locations in the hooked state exhibit asynchronous characteristics. In contrast, under a good lifting condition, the tension data between different lifting points are highly similar, and the differences in abnormal tension changes are relatively small.

[0041] The sum of the Spearman correlation coefficients between the corresponding tension data for all two arbitrary lifting point positions within the i-th lifting period and 1 is calculated, and the mean of all these sums is recorded as the positive correlation factor for the i-th lifting period. The calculation process of the Spearman correlation coefficient is well known in the art and the specific process is not repeated here.

[0042] As a preferred embodiment, the positive correlation factor of each lifting period is obtained according to the correlation degree between the tension data of all any two lifting point positions in each lifting period, and the asynchronous coefficient of each lifting period is obtained in combination with the difference in the tension abnormality coefficient of all any two lifting point positions in each lifting period, which is used to characterize the degree of asynchronous state of the tension state of each lifting point position of the crane.

[0043] In this embodiment, the asynchronous coefficient of the i-th lifting period is recorded as , whose expression is: Where, represents the asynchronous coefficient of the i-th lifting period, It represents the mean of the difference between the abnormal tension coefficients of any two lifting points in the i-th lifting period. Represents the positive correlation factor of the i-th lifting period. The larger the value of , the more asynchronous the tension states of the lifting points in the i-th lifting period are.

[0044] Furthermore, if the container is unevenly loaded, the tension values between the lifting points may vary significantly, leading to misjudgment. However, the container lifting process is not affected by the coupling, so the tension difference characteristics under uneven loading do not continue to increase, but are relatively stable. If the F-TR lock is hooked, the coupling position does not disengage, while the other unlocked positions continue to increase, making the abnormal characteristics of asynchronous tension changes increasingly obvious.

[0045] As a preferred embodiment, the persistent significance coefficient at the current moment is obtained based on the difference in the asynchronous coefficients between adjacent lifting periods in all lifting periods before the current moment, which is used to characterize the possibility of F-TR lock hooking during the crane lifting operation.

[0046] In this embodiment, the current continuous significance index is recorded as , the specific formula is: Where, It represents the continuous significance index at the current moment, s represents the position value of the previous lifting period before the lifting period at the current moment, and They represent the asynchronous coefficients of the i-th lifting period and the i+1-th lifting period respectively. The larger the value, the greater the possibility of F-TR lock hooking during crane lifting operation.

[0047] F-TR lock hook dynamic monitoring module: compares the current moment's continuous significance coefficient with the preset abnormal threshold to determine whether F-TR lock hook occurs at the current moment.

[0048] In order to perform real-time dynamic detection, the sigmoid function is used to normalize the persistent significance index calculated at the current moment, and the normalized result is compared with the preset abnormality threshold. The preset abnormality threshold range is [0.6, 1]. If If the value is set too low, it will be difficult to detect abnormal hooking in a timely manner. If it is set too high, it will easily lead to oversensitivity to hooking detection and misjudgment. In this embodiment, the preset abnormality threshold is set to 0.75. If the normalized result of the persistent significance index is greater than or equal to the preset abnormality threshold, it is determined that F-TR hooking has occurred during the current crane lifting moment, and it is necessary to stop the lifting immediately and use the container rotation control system to automatically adjust the rotation angle of the container to facilitate smooth uncoupling. Otherwise, it is determined that F-TR hooking has not occurred during the current crane lifting moment.

[0049] It should be noted that the order of the embodiments of the present application is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0050] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0051] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A dynamic monitoring system for F-TR lock coupling in railway container loading and unloading operations, characterized in that: The system comprises: Lifting process data acquisition module: real-time acquisition of the tension data of each lifting point of the crane during the container lifting process; Crane lifting process analysis module: The container lifting process is evenly divided into multiple lifting periods; the slope of each tension data is obtained based on the fitting curve of the tension data of each lifting point position in each lifting period; the mutation data of each lifting point position in each lifting period is obtained based on the mutation point in the slope of all tension data of each lifting point position in each lifting period; the abnormal increase significance value of the single lifting point position in each lifting period is obtained based on the average level of all mutation data of the single lifting point position in each lifting period and the difference between each two adjacent tension data of the single lifting point position in each lifting period, and the tension abnormality coefficient of the single lifting point position in each lifting period is obtained based on the irregularity of the tension data of the single lifting point position in each lifting period; the positive correlation factor of each lifting period is obtained based on the correlation between the tension data of all two arbitrary lifting point positions in each lifting period, and the asynchronous coefficient of each lifting period is obtained based on the difference between the tension abnormality coefficients of all two arbitrary lifting point positions in each lifting period; the persistent significant coefficient at the current moment is obtained based on the difference between the asynchronous coefficients between adjacent lifting periods in all lifting periods before the current moment; F-TR lock hook dynamic monitoring module: compares the current moment's continuous significance coefficient with the preset abnormal threshold to determine whether F-TR lock hook occurs at the current moment.

2. A railway container loading and unloading operation F-TR lock hook dynamic monitoring system as claimed in claim 1, characterized in that: The specific process of evenly dividing the container lifting process into a plurality of lifting periods is as follows: continuously dividing the monitoring time in the lifting process from the beginning to the end into a plurality of lifting periods according to a fixed time length.

3. A railway container loading and unloading operation F-TR lock hook dynamic monitoring system as claimed in claim 1, characterized in that: The specific process of obtaining the slope of each tension data is: obtaining a fitting curve of the tension data at each lifting point position in each lifting period, and using the value of each tension data in the differential equation of its corresponding fitting curve as the slope of each tension data.

4. A railway container loading and unloading operation F-TR lock hook dynamic monitoring system as claimed in claim 1, characterized in that: The specific process of obtaining the mutation data of each hanging point position in each lifting period is as follows: arranging the slopes of the tension data of each hanging point position in each lifting period in chronological order to obtain a slope sequence of each hanging point position in each lifting period; obtaining the mutation points in the slope sequence of each hanging point position in each lifting period, and recording the data corresponding to the mutation points in the slope sequence as mutation data.

5. A railway container loading and unloading operation F-TR lock hook dynamic monitoring system as claimed in claim 1, characterized in that: The calculation formula for the significant value of abnormal increase in the position of a single lifting point during each lifting period is: Where, is the significant value of abnormal increase in the position of a single lifting point during the i-th lifting period, is the mean of all mutation data of a single lifting point position during the i-th lifting period, represents a logarithmic function with base 2, N represents the total number of tension data at a single lifting point during the i-th lifting period, 、 They respectively represent the slope values of the j-th and j-1-th tension data of a single lifting point position in the i-th lifting period.

6. A railway container loading and unloading operation F-TR lock coupling dynamic monitoring system as claimed in claim 1, characterized in that: The process of obtaining the abnormal tension coefficient of a single lifting point position in each lifting period is as follows: calculating the fractal dimension of the tension data of a single lifting point position in each lifting period; and recording the product of the abnormal increase significance value of the single lifting point position in each lifting period and the fractal dimension as the abnormal tension coefficient of the single lifting point position in each lifting period.

7. A railway container loading and unloading operation F-TR lock coupling dynamic monitoring system as claimed in claim 1, characterized in that: The process of obtaining the positive correlation factor of each lifting period is as follows: calculating the sum of the Spearman correlation coefficient between the tension data corresponding to all two arbitrary lifting point positions in each lifting period and 1, and recording the mean of all the sum values as the positive correlation factor of the i-th lifting period.

8. A railway container loading and unloading operation F-TR lock coupling dynamic monitoring system as claimed in claim 1, characterized in that: The calculation formula of the asynchronous coefficient of each lifting period is: Where, represents the asynchronous coefficient of the i-th lifting period, It represents the mean of the difference between the abnormal tension coefficients of any two lifting points in the i-th lifting period. Represents the positive correlation factor of the i-th lifting period.

9. A railway container loading and unloading operation F-TR lock hook dynamic monitoring system as claimed in claim 1, characterized in that: The expression of the persistent significant coefficient at the current moment is: Where, It represents the continuous significance index at the current moment, s represents the position value of the previous lifting period before the lifting period at the current moment, and They represent the asynchronous coefficients of the i-th lifting period and the i+1-th lifting period respectively.

10. A railway container loading and unloading operation F-TR lock coupling dynamic monitoring system as claimed in claim 1, characterized in that: The specific process of determining whether F-TR lock hooking occurs at the current moment is as follows: if the normalized result of the persistent significance index is greater than or equal to the preset abnormality threshold, it is determined that F-TR lock hooking occurs when the crane is lifting at the current moment; otherwise, it is determined that F-TR lock hooking does not occur when the crane is lifting at the current moment.

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