F-TR lock hooking dynamic monitoring system for railway container loading and unloading operation

Abstract

The invention relates to the technical field of hoisting device monitoring, in particular to an F-TR lock hooking dynamic monitoring system for railway container loading and unloading operation. The method comprises the following steps: acquiring tension data of each hoisting point of the crane; the hoisting process is divided into a plurality of hoisting time periods; obtaining an abnormal increase significant value of a single hoisting point position in each hoisting time period, and obtaining a tension abnormal coefficient of the single hoisting point position in each hoisting time period by combining the irregular degree of the tension data of the single hoisting point position in each hoisting time period; according to the correlation degree of the tension data of all any two hoisting point positions in each hoisting time period and the difference of the tension abnormal coefficients of all any two hoisting point positions in each hoisting time period, acquiring an asynchronous coefficient of each hoisting time period; and acquiring a continuous significance coefficient at the current moment, comparing the continuous significance coefficient with a preset threshold value, and judging whether F-TR lock hooking occurs or not. According to the method, the monitoring accuracy of F-TR lock hooking is improved by analyzing the multi-dimensional characteristics of the tension data in the hoisting process.

Description

Technical Field

[0001] This application relates to the technical field of lifting device monitoring, and particularly relates to a dynamic monitoring system for the F-TR lock connection during railway container loading and unloading operations. Background Art

[0002] As an advanced modern transportation method, container transportation has the characteristics of high transportation efficiency and good economic benefits compared with the traditional bulk transportation method. Its application in the field of railway freight in China is becoming increasingly widespread, and many loading and unloading operation machines and safety protection devices adapted to containerization have been developed and configured. New-type container eagle head locks (F-TR locks) are widely used in railway container transportation in China to ensure the stability during the container transportation process and prevent the container from tipping over.

[0003] The F-TR lock is a key component for locking the container on the flat car of the container. During the process of loading and unloading the container using a crane, if the smoothness of the container corner fitting entering and exiting the F-TR lock is insufficient, there will be phenomena such as the container not being locked in place and the lifting hook connecting to the F-TR lock. Moreover, container partial load, serious deformation of the container corner fitting, and shaking during transportation are all likely to cause the F-TR lock to be hooked. The existing technology detects that the F-TR lock corresponding to the container and the tension sensor above and below appears to be hooked by collecting the tension values of four tension sensors connected to the lifting spreader. When the deviation amount of the tension change value of a certain tension sensor from the tension change value of another one or several is greater than the set threshold. However, in the case where there is no F-TR lock hook-up, if the container is partially loaded, 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 judge whether the F-TR lock hook-up phenomenon occurs, and does not analyze the characteristics when the F-TR lock hook-up phenomenon occurs from multiple angles, which has certain limitations and results in a low accuracy of dynamic monitoring of the F-TR lock hook-up. 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 the F-TR lock connection during railway container loading and unloading operations, and the specific technical solution adopted is as follows: This application proposes a dynamic monitoring system for the F-TR lock connection during railway container loading and unloading operations, and the system includes: Lifting process data acquisition module: Real-time acquisition of the tension data of the positions of each lifting point of the crane during the lifting process of the container; Crane lifting process analysis module: evenly divide the container lifting process into multiple lifting time periods; obtain the slope of each tensile force data according to the fitting curve of the tensile force data at each lifting point position within each lifting time period; obtain the mutation data at each lifting point position within each lifting time period according to the mutation points among the slopes of all tensile force data at each lifting point position within each lifting time period; obtain the significantly abnormal increase value at each single lifting point position within each lifting time period according to the average level of all mutation data at each single lifting point position within each lifting time period and the difference between each adjacent two tensile force data at each single lifting point position within each lifting time period, and combine the irregularity degree of the tensile force data at each single lifting point position within each lifting time period to obtain the tensile force anomaly coefficient at each single lifting point position within each lifting time period; obtain the positive correlation factor of each lifting time period according to the correlation degree between the tensile force data at any two lifting point positions within each lifting time period, and combine the difference between the tensile force anomaly coefficients at any two lifting point positions within each lifting time period to obtain the non-synchronization coefficient of each lifting time period; obtain the continuous significant coefficient at the current moment according to the difference between the non-synchronization coefficients between adjacent lifting time periods among all lifting time periods before the current moment; F-TR locking hook connection dynamic monitoring module: compare the continuous significant coefficient at the current moment with a preset abnormal threshold to determine whether an F-TR locking hook connection occurs at the current moment.

[0005] Preferably, the specific process of evenly dividing the container lifting process into multiple lifting time periods is as follows: continuously divide the monitoring time during the lifting process into multiple lifting time periods from front to back according to a fixed time length.

[0006] Preferably, the specific process of obtaining the slope of each tensile force data is as follows: obtain the fitting curve of the tensile force data at each lifting point position within each lifting time period, and take the value of each tensile force data in the differential equation of its corresponding fitting curve as the slope of each tensile force data.

[0007] Preferably, the specific process of obtaining the mutation data at each lifting point position within each lifting time period is as follows: arrange the slopes of the tensile force data at each lifting point position within each lifting time period in chronological order to obtain the slope sequence at each lifting point position within each lifting time period; obtain the mutation points in the slope sequence at each lifting point position within each lifting time period, and record the data corresponding to the mutation points in the slope sequence as the mutation data.

[0008] Preferably, the calculation formula for the significantly abnormal increase value at each single lifting point position within each lifting time period is: ; where is the significantly abnormal increase value at the single lifting point position within the i-th lifting time period, is the mean value of all mutation data at the single lifting point position within the i-th lifting time period, represents the logarithmic function with base 2, and N represents the total number of tensile force data at the single lifting point position within the i-th lifting time period, , respectively represent the slope values of the j-th and (j - 1)-th tensile force data at the position of a single lifting point during the i-th lifting period.

[0009] Preferably, the process of obtaining the tensile force anomaly coefficient at the position of a single lifting point in each lifting period is as follows: calculate the fractal dimension of the tensile force data at the position of a single lifting point in each lifting period; record the product of the significantly increased anomaly value at the position of a single lifting point in each lifting period and the fractal dimension as the tensile force anomaly coefficient at the position of a single lifting point in each lifting period.

[0010] Preferably, the process of obtaining the positive correlation factor of each lifting period is as follows: calculate the sum of the Spearman correlation coefficient between the tensile force data corresponding to any two lifting point positions in each lifting period and 1, and record the mean value of all the sum values as the positive correlation factor of the i-th lifting period.

[0011] Preferably, the calculation formula for the asynchronous coefficient of each lifting period is: ; where represents the asynchronous coefficient of the i-th lifting period, represents the mean value of the differences between the tensile force anomaly coefficients corresponding to any two lifting point positions in the i-th lifting period, represents the positive correlation factor of the i-th lifting period.

[0012] Preferably, the expression of the continuous significance coefficient at the current moment is: ; where represents the continuous significance index at the current moment, s represents the sequence value of the previous lifting period where the current moment is located, and respectively represent the asynchronous coefficients of the i-th lifting period and the (i + 1)-th lifting period.

[0013] Preferably, the specific process of determining whether F-TR hook connection occurs at the current moment is as follows: if the normalized result of the continuous significance index is greater than or equal to the preset anomaly threshold, it is determined that F-TR hook connection occurs during the crane lifting at the current moment; otherwise, it is determined that F-TR hook connection does not occur during the crane lifting at the current moment.

[0014] The present application has the following beneficial effects: In view of the problem that most of the existing monitoring technologies use the method of whether there is an obvious deviation between some tensile values and other tensile values to judge whether there is a snag, resulting in a low monitoring accuracy rate, by installing tensile sensors at the four lifting points of the crane to collect tensile data in real time, analyzing the abnormal characteristics of the tensile data at each lifting point, the collaborative characteristics of the tensile changes at different lifting points, and the differences in the abnormal characteristics of the tensile force in the adjacent time windows before and after, a continuous significance index is constructed. The characteristics when the F-TR lock is snagged are analyzed from multiple angles, and the time-series change trend of the abnormal forces on multiple lifting points during the lifting process is dynamically tracked, which can effectively reduce the influence of container interference factors, thereby reducing the misjudgment rate of F-TR lock snags, achieving dynamic and accurate monitoring of the F-TR lock snag state, and improving the monitoring accuracy rate of the F-TR lock snag state. Brief Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0016] Figure 1 It is a block diagram of a dynamic monitoring system for F-TR lock snags in railway container loading and unloading operations provided by an embodiment of the present application; Figure 2 It is an analysis flow chart of the lifting process analysis module provided by an embodiment of the present application. Detailed Embodiments

[0017] In order to further elaborate on the technical means and effects adopted by the present application to achieve the intended invention purpose, the following will, in conjunction with the drawings and preferred embodiments, detail the specific embodiments, structures, features and effects of a dynamic monitoring system for F-TR lock snags in railway container loading and unloading operations proposed according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs.

[0019] The following will specifically describe the specific solution of a dynamic monitoring system for F-TR lock snags in railway container loading and unloading operations provided by the present application in conjunction with the drawings.

[0020] Please refer to Figure 1, which shows a block diagram of an F-TR lock coupling dynamic monitoring system 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 coupling dynamic monitoring module.

[0021] Lifting process data acquisition module: Real-time acquisition of the tension data of each lifting point position of the crane during the container lifting process.

[0022] The F-TR lock has the functions of preventing the container from tipping over and jumping, ensuring the transportation safety of the container after the railway speed increase. To facilitate the entry and exit of the container corner fittings into the lock head, the installation direction of the lock head on the vehicle is the same in each end and opposite at both ends. During the unlocking operation, it is necessary for the container to generate a small plane rotation of about 2.5° on the horizontal plane to smoothly withdraw the FT-R lock head. In some unconventional cases during the container unloading operation, the lock hole corner fittings of the container body will get stuck with the F-TR lock body and cannot be unhooked smoothly. In the hooked state, it will cause abnormal tension data of the container lifting. Therefore, tension sensors are installed at the four lifting point positions of the crane to collect the tension data during lifting. In this embodiment, the time interval for tension data acquisition is 0.05 seconds, and the implementer can set the time interval according to the actual situation. Thus, the tension data during the crane lifting process can be obtained.

[0023] Crane lifting process analysis module: Evenly divide the container lifting process into multiple lifting time periods; obtain the slope of each tension data according to the fitting curve of the tension data at each lifting point position within each lifting time period; obtain the mutation data at each lifting point position within each lifting time period according to the mutation points among the slopes of all tension data at each lifting point position within each lifting time period; obtain the significantly abnormal increase value at each lifting point position within each lifting time period according to the average level of all mutation data at a single lifting point position within each lifting time period and the difference between each adjacent two tension data at a single lifting point position within each lifting time period, and combine with the irregularity degree of the tension data at a single lifting point position within each lifting time period to obtain the tension anomaly coefficient at a single lifting point position within each lifting time period; obtain the positive correlation factor of each lifting time period according to the correlation degree between the tension data at any two lifting point positions within each lifting time period, and combine with the difference between the tension anomaly coefficients at any two lifting point positions within each lifting time period to obtain the non-synchronization coefficient of each lifting time period; obtain the continuous significant coefficient at the current moment according to the difference between the non-synchronization coefficients between adjacent lifting time periods among all the lifting time periods before the current moment.

[0024] The analysis process of the crane lifting process analysis module is as Figure 2As shown in the figure. Specifically, when the container is placed on the railway flatcar, the F-TR lock is in the locked state. Before unloading the container, the lock head needs to be rotated to the unlocking position before the container can be lifted. When there is a lock hook connection, the container cannot be lifted normally. The main reasons for the lock hook connection 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 abnormal unhooking; serious deformation of the container corner fittings. The lock hook connection usually causes abnormal or asynchronous changes in the tension data. For example, when there is a hook connection at a certain corner of the container, the tension value at the hook connection position will suddenly increase or fluctuate frequently, resulting in asynchronous tensions at different positions. The existing method for judging whether there is a hook connection of the F-TR lock based on tension value monitoring mainly judges whether there is a hook connection according to abnormal or asynchronous partial tension values.

[0025] However, when loading and unloading goods in the container, there is no reasonable planning for the distribution of goods during loading. Operators' loading and unloading habits usually give priority to placing goods inside the container, and the nature of the goods and the protection requirements also cause environmentally sensitive goods to be placed inside. As a result, the inside of the container is relatively full, while the outside near the door is loaded lightly, causing the center of gravity of the container to deviate from the geometric center of the box body, and thus causing uneven loading. During the lifting process, the tension value corresponding to the heavier side will also be larger, resulting in uneven tension during the lifting process, and further affecting the judgment of the lock hook connection. Therefore, it is necessary to analyze the specific change characteristics of the tension data in the case of the F-TR lock in the hook connection state, so as to improve the accuracy of monitoring the hook connection state.

[0026] The lifting process of the crane is relatively slow and usually takes more than ten seconds or dozens of seconds. For real-time dynamic monitoring of this process, the monitoring time during the lifting process is continuously divided into multiple lifting periods from front to back according to the time length of w seconds. In this embodiment, w is taken as 2. Taking the tensile force data at a certain hoisting point position as an example, the following analysis is carried out. First, in the normal lifting state without hook connection, the tensile force value may have a slow increasing process, is relatively stable as a whole, and changes evenly. After long-term use, the lock head may be deformed or the friction force may be too large, making it easy to have insufficient smoothness of unhooking, resulting in a short-term rapid increase trend in the tensile force data during the lifting process, or the tensile force value suddenly becomes larger due to the jamming of the angle parts. Therefore, the abnormal characteristics of the tensile force can be better reflected through the change rate. First, the least squares method is used to obtain the fitting curve of the tensile force data at each hoisting point position within each lifting period, and the value of each tensile force data in the differential equation of its corresponding fitting curve is used as the slope of each tensile force data. The slopes of the tensile force data at each hoisting point position within each lifting period are arranged in chronological order to obtain the slope sequence of each hoisting point position within each lifting period. Since there will be mutations in the slopes of the tensile force data in the hooked state, the slope sequences of each hoisting point position within each lifting period are respectively used as the input of the SOS (Stochastic Outlier Selection) algorithm to obtain the mutation points in the slope sequences of each hoisting point position within each lifting period, and the data corresponding to the mutation points in the slope sequence is recorded as the mutation data. Among them, the least squares method and the SOS algorithm are well-known technologies, and the specific processes will not be elaborated.

[0027] As a preferred implementation manner, according to the average level of all mutation data at a single hoisting point position within each lifting period, and the difference between each adjacent two tensile force data at a single hoisting point position within each lifting period, the abnormal increase significant value at a single hoisting point position within each lifting period is obtained, which is used to characterize the possibility of the abnormal increase characteristics of short-term rapid increase and significant mutation at a single hoisting point position within each lifting period.

[0028] In this embodiment, the abnormal increase significant value at a single hoisting point position within the i-th lifting period is denoted as , and its specific expression is: ; In the formula, is the abnormal increase significant value at a single hoisting point position within the i-th lifting period, is the mean value of all mutation data at a single hoisting point position within the i-th lifting period, represents the logarithmic function with base 2, N represents the total number of tensile force data at a single hoisting point position within the i-th lifting period, , respectively represent the slope values of the j-th and j-1-th tensile force data at a single hoisting point position within the i-th lifting period.

[0029] For The purpose of the logarithmic function is to prevent the value from being too large; The larger the value, the more obvious the increasing characteristic of the tension data at the slope mutation point; The larger the value, the more obvious the short-term rapid increase characteristic of the tension data. The larger the value, the greater the possibility of the abnormal increase characteristic of short-term rapid increase and significant mutation existing in the position of a single lifting point during the i-th lifting period.

[0030] In addition, when the F-TR lock is unlocked, it needs to rotate at a certain angle on the horizontal plane. Affected by insufficient or excessive rotation angle and deformation during long-term use, the gap between the F-TR lock and the corner fitting is too small. During the continuous friction during lifting, the tension data shows irregular and frequent up and down fluctuations, and then hook connection occurs. To obtain this irregular and frequent fluctuation characteristic, the Higuchi algorithm is used to further calculate the fractal dimension of the tension data at the position of a single lifting point during the i-th lifting period. This value reflects the irregular change characteristic of the tension data. The Higuchi algorithm is a well-known technology, and the specific process will not be elaborated here.

[0031] As a preferred implementation manner, the significant abnormal increase value at the position of a single lifting point in each lifting period is combined with the fractal dimension of the tension data at the position of a single lifting point in each lifting period to obtain the tension abnormal coefficient at the position of a single lifting point in each lifting period, which is used to characterize the abnormal degree of the irregular abnormal change of the tension data at the position of a single lifting point during the crane lifting process due to continuous friction.

[0032] In this embodiment, the product of the significant abnormal increase value at the position of a single lifting point in the i-th lifting period and the fractal dimension is recorded as the tension abnormal coefficient at the position of a single lifting point in the i-th lifting period. The larger the value of the tension abnormal coefficient, the more significant the abnormal change of the tension data at the corresponding lifting point position in the corresponding lifting period.

[0033] In another embodiment of the present application, the sum of the significant abnormal increase value at the position of a single lifting point in the i-th lifting period and the fractal dimension is recorded as the tension abnormal coefficient at the position of a single lifting point in the i-th lifting period.

[0034] Furthermore, due to the uneven deviation of the center of gravity of the container, the container will tilt during the operation of the crane. The greater the tilt degree of the container, the greater the difference in the tensile force state between the lifting points. And as the tilt degree continues to increase, one end of the container has been unlocked and suspended away from the flat car, while the other end has not been unlocked, resulting in the locking head being hooked to the corner fitting of the container, that is, the bottom plane of the container forms an angle with the body of the flat car. This angle will inevitably affect the smooth unlocking of the F-TR locking device. Therefore, the change of the tensile force at each position in the hooked state shows an asynchronous characteristic. Under the good lifting state, the similarity degree of the tensile force data between different lifting points is relatively high, and the difference in the abnormal change of the tensile force is relatively small.

[0035] Calculate the sum of the Spearman correlation coefficient between the tensile force data corresponding to all any two lifting point positions in the i-th lifting period and 1, and record the mean value of all the sum values as the positive correlation factor of the i-th lifting period. The calculation process of the Spearman correlation coefficient is a well-known technology, and the specific process will not be elaborated here.

[0036] As a preferred implementation manner, obtain the positive correlation factor of each lifting period according to the correlation degree between the tensile force data of all any two lifting point positions in each lifting period, and combine the difference in the tensile force anomaly coefficients of all any two lifting point positions in each lifting period to obtain the asynchronous coefficient of each lifting period, which is used to characterize the asynchronous degree of the tensile force state at each lifting point position of the crane.

[0037] In this embodiment, record the asynchronous coefficient of the i-th lifting period as , and its expression is: ; In the formula, represents the asynchronous coefficient of the i-th lifting period, represents the mean value of the difference in the tensile force anomaly coefficients corresponding to all any two lifting point positions in the i-th lifting period, represents the positive correlation factor of the i-th lifting period. The larger the value of

[0038] , the more asynchronous the tensile force state at each lifting point position in the i-th lifting period. Furthermore, if there is container partial load, there may be too large a deviation in the tensile force value between the lifting points, resulting in misjudgment. However, the lifting process of the container is not affected by the hooking, so that the tensile force difference characteristics in the partial load state will not continue to increase, but are relatively stable. If the F-TR lock is hooked and the hooked position is not unlocked, while the other unlocked positions continue to rise, the abnormal characteristics of the asynchronous change of the tensile force will become more and more significant.

[0039] As a preferred implementation manner, obtain the continuous significant coefficient at the current moment according to the difference in the asynchronous coefficients between adjacent lifting periods in all the lifting periods before the current moment, which is used to characterize the possibility of the F-TR lock being hooked during the crane lifting operation.

[0040] In this embodiment, the continuous significance index at the current moment is denoted as , and its specific formula is: ; In the formula, represents the continuous significance index at the current moment, s represents the sequence value of the previous hoisting period of the hoisting period where the current moment is located, and respectively represent the asynchronous coefficients of the i-th hoisting period and the (i + 1)-th hoisting period. The obtained is larger, indicating that the possibility of F-TR hook connection occurring during the crane hoisting operation is greater.

[0041] F-TR Hook Connection Dynamic Monitoring Module: Compare the continuous significance coefficient at the current moment with a preset abnormal threshold to determine whether F-TR hook connection occurs at the current moment.

[0042] For real-time dynamic detection, the sigmoid function is used to normalize the continuous significance index calculated at the current moment, and the normalized result is compared with the preset abnormal threshold. The range of the preset abnormal threshold is [0.6, 1]. If is set too small, it is difficult to detect abnormal connections in time; if set too large, it is easy to cause the monitoring of connections to be too sensitive and result in misjudgment. In this embodiment, the preset abnormal threshold is set to 0.75. If the normalized result of the continuous significance index is greater than or equal to the preset abnormal threshold, it is determined that F-TR hook connection occurs during the crane hoisting at the current moment, and the hoisting needs to be stopped in time, and the container rotation control system is used to automatically adjust the rotation angle of the container to facilitate smooth unhooking; otherwise, it is determined that F-TR hook connection does not occur during the crane hoisting at the current moment.

[0043] It should be noted that: the above sequence of the embodiments of the present application is only for description and does not represent the advantages or disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be beneficial.

[0044] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0045] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present application shall be included in the protection scope of the present application.

Claims

1. A dynamic monitoring system for the F-TR locking hook connection in railway container loading and unloading operations, characterized in that, The system includes: Lifting process data acquisition module: It obtains the tension data of each lifting point position of the crane in real time during the container lifting process. Crane lifting process analysis module: The container lifting process is evenly divided into multiple lifting time periods; according to the fitting curve of the tension data of each lifting point position in each lifting time period, the slope of each tension data is obtained; according to the mutation points among the slopes of all the tension data of each lifting point position in each lifting time period, the mutation data of each lifting point position in each lifting time period is obtained; according to the average level of all the mutation data of a single lifting point position in each lifting time period, and the difference between each adjacent two tension data of a single lifting point position in each lifting time period, the significantly abnormal increase value of a single lifting point position in each lifting time period is obtained, and in combination with the irregularity degree of the tension data of a single lifting point position in each lifting time period, the tension anomaly coefficient of a single lifting point position in each lifting time period is obtained; according to the correlation degree between the tension data of any two lifting point positions in each lifting time period, the positive correlation factor of each lifting time period is obtained, and in combination with the difference between the tension anomaly coefficients of any two lifting point positions in each lifting time period, the non-synchronization coefficient of each lifting time period is obtained; according to the difference between the non-synchronization coefficients between adjacent lifting time periods in all the lifting time periods before the current moment, the continuous significant coefficient at the current moment is obtained. F-TR lock connection dynamic monitoring module: It compares the continuous significant coefficient at the current moment with a preset abnormal threshold to determine whether an F-TR lock connection occurs at the current moment.

2. The F-TR locking hook connection dynamic monitoring system for railway container loading and unloading operations according to claim 1, characterized in that, The specific process of evenly dividing the container lifting process into multiple lifting time periods is as follows: The monitoring time during the lifting process is continuously divided into multiple lifting time periods from front to back according to a fixed time length.

3. The F-TR locking hook connection dynamic monitoring system for railway container loading and unloading operations according to claim 1, wherein The specific process of obtaining the slope of each tension data is as follows: The fitting curve of the tension data of each lifting point position in each lifting time period is obtained, and the value of each tension data in the differential equation of its corresponding fitting curve is used as the slope of each tension data.

4. The dynamic monitoring system for the F-TR locking hook connection in railway container loading and unloading operations according to claim 1, characterized in that The specific process of obtaining the mutation data of each lifting point position in each lifting time period is as follows: The slopes of the tension data of each lifting point position in each lifting time period are arranged in chronological order to obtain the slope sequence of each lifting point position in each lifting time period; the mutation points in the slope sequence of each lifting point position in each lifting time period are obtained, and the data corresponding to the mutation points in the slope sequence is recorded as the mutation data.

5. The F-TR locking hook connection dynamic monitoring system for railway container handling operations according to claim 1, characterized in that The calculation formula for the significant abnormal increase value of the position of a single lifting point during each lifting period is as follows: ; In the formula, is the significant abnormal increase value of the position of a single lifting point during the i-th lifting period, is the mean value of all mutation data of the position of a single lifting point during the i-th lifting period, represents the logarithmic function with base 2, N represents the total number of tensile force data of the position of a single lifting point during the i-th lifting period, 、 respectively represent the slope values of the j-th and j-1-th tensile force data of the position of a single lifting point during the i-th lifting period.

6. The dynamic monitoring system for the F-TR locking hook connection in railway container loading and unloading operations according to claim 1, wherein The obtaining process of the tension anomaly coefficient of a single lifting point position in each lifting time period is as follows: The fractal dimension of the tension data of a single lifting point position in each lifting time period is calculated; the product of the significantly abnormal increase value of a single lifting point position in each lifting time period and the fractal dimension is recorded as the tension anomaly coefficient of a single lifting point position in each lifting time period.

7. The dynamic monitoring system for the F-TR locking hook connection in railway container handling operations according to claim 1, characterized in that The obtaining process of the positive correlation factor of each lifting time period is as follows: The sum of the Spearman correlation coefficient between the corresponding tension data of any two lifting point positions in each lifting time period and 1 is calculated, and the mean value of all the sum values is recorded as the positive correlation factor of the i-th lifting time period.

8. The F-TR locking hook connection dynamic monitoring system for railway container handling operations according to claim 1, wherein The calculation formula for the asynchronous coefficient of each hoisting period is as follows: ; In the formula, represents the asynchronous coefficient of the i-th hoisting period, represents the average value of the differences in the abnormal force coefficients corresponding to the positions of any two lifting points within the i-th hoisting period, represents the positive correlation factor of the i-th hoisting period.

9. The dynamic monitoring system for the F-TR locking hook connection in railway container handling operations according to claim 1, characterized in that The expression for the continuous significance coefficient at the current moment is as follows: ; where represents the continuous significance index at the current moment, s represents the sequence value of the previous hoisting period of the hoisting period where the current moment is located, and respectively represent the asynchronous coefficients of the i-th hoisting period and the (i + 1)-th hoisting period.

10. The F-TR locking hook connection dynamic monitoring system for railway container loading and unloading operations according to claim 1, characterized in that The specific process of determining whether the F-TR lock hook connection occurs at the current moment is as follows: If the normalized result of the continuous significant index is greater than or equal to the preset abnormal threshold, it is determined that the F-TR lock hook connection occurs during the crane hoisting at the current moment; otherwise, it is determined that the F-TR lock hook connection does not occur during the crane hoisting at the current moment.

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