A swing operating state monitoring method and device

Abstract

The application discloses a swing operation state monitoring method and device, and the method comprises the following steps: predicting the predicted swing time T of each swing in the previous N swings and predicting the maximum tension TF through a state prediction model; comparing the predicted swing time T with a first early warning threshold value, comparing the predicted maximum tension TF with a second early warning threshold value, and determining whether to give a maintenance early warning; comparing the predicted swing time, the predicted maximum tension, the actual swing time and the actual maximum tension respectively, and determining whether to give a model optimization early warning. The application uses historical swing data and a multiple linear regression method to establish a prediction model. The predicted data, the threshold value determined according to the historical data and the actual measurement value are compared to determine whether to give an early warning, and the safety of the swing operation is improved.

Description

A method and device for monitoring the operating status of a swing Technical Field

[0001] This invention belongs to the field of amusement equipment testing technology, and discloses a method and device for monitoring the operating status of a swing. Background Technology

[0002] Canyon Crossing is a large-scale amusement ride, similar to a swing, installed on the edge of a canyon cliff. It involves placing passengers in full-body flight suits, which are then connected to a supporting steel cable. The cable is then connected to an arched tower steel structure via a support structure.

[0003] During the canyon crossing experience, passengers are first lifted to a height of nearly 100 meters by a winch, and then released to fly freely along an arc trajectory towards the outside of the cliff. Passengers look down at the scenery below from the air, experiencing both the thrill of flying with the wind and the excitement of soaring over the canyon, making it an unforgettable experience.

[0004] Currently, safety for swing-type amusement equipment is usually ensured only from a design perspective, such as using structures and materials with high safety factors in the design and inspecting it when it is stopped. However, there is no method to use its historical operating data to monitor its safety during operation. Summary of the Invention

[0005] This application establishes a predictive model by learning from the historical operating data of the swing. The predictive model predicts the operating status of the swing. When the predicted data deviates from the actual data and exceeds a certain value, the system issues an early warning. Relevant personnel then inspect the wire rope and other related hardware equipment to detect changes in the equipment status in advance and ensure the safety of the equipment.

[0006] A method for monitoring the operational status of a swing includes the following steps:

[0007] The swing's characteristic values ​​for the first N swings in each operating cycle are predicted using a state prediction model. These characteristic values ​​include the predicted swing time T for each swing and the predicted maximum tension TF.

[0008] The state prediction model was obtained by modeling using data from multiple normal operating cycles of the swing through a multiple linear regression method.

[0009] The predicted swing time T of each swing in the first N swings is compared with the first warning threshold, and the predicted maximum tension TF of each swing in the first N swings is compared with the second warning threshold. When the predicted swing time and predicted maximum tension of each swing in the first N swings exceed the corresponding warning threshold for M consecutive operating cycles, maintenance warning is issued.

[0010] During the swing's operation, tension sensors installed on the steel wire rope are used to detect the rope's tension, obtaining the actual maximum tension of each swing in the first N swings, as well as the actual swing time for each swing. The predicted swing time and predicted maximum tension are compared with the actual swing time and actual maximum tension. When the deviation between the predicted swing time and predicted maximum tension and the actual values ​​in the first N swings of M consecutive operating cycles exceeds the fourth warning threshold, an early warning for optimization of the state prediction model is issued, and the prediction model is reconstructed using data from multiple new operating cycles.

[0011] Optionally, it also includes

[0012] The strain force of the wire rope hanger corresponding to the moment of maximum tension of the wire rope in each of the previous N swings is taken as the maximum strain force of the wire rope hanger in that swing. Thus, the maximum strain force of the wire rope hanger corresponding to the moment of maximum tension of the wire rope in each of the previous N swings is obtained.

[0013] The maximum strain force of the wire rope hanger in each of the first N swings is compared with the third warning threshold. If the strain force exceeds the third warning threshold for M consecutive operating cycles, a maintenance warning is issued.

[0014] Optionally, the state prediction model is as follows:

[0015] Predicted swing time T = a11 * number of passengers + a12 * wind speed + a13 * temperature + a20

[0016] Predicted maximum tension TF = b11 * number of passengers + b12 * wind speed + b13 * temperature + b20

[0017] Among them, a11, a12, a13, a20, b11, b12, b13, and b20 are regression parameters, which are estimated and determined by data from multiple normal operating cycles of the swing.

[0018] Optionally, the state prediction model can be optimized by using data from at least every 500 normal operating cycles of the swing.

[0019] Optionally, the third warning threshold is formed by statistically analyzing the maximum and minimum values ​​of the maximum strain force of the wire rope suspension seat in each of the first N swings when different numbers of people ride the swing during at least 500 normal operating cycles.

[0020] Optionally, the first warning threshold and the second warning threshold are formed by statistically analyzing the maximum and minimum values ​​of the swing time and maximum tension in each of the first N swings when different numbers of people ride the swing during at least 500 normal operating cycles.

[0021] Optionally, N equals 4.

[0022] Optionally, M equals 3.

[0023] This application also provides an electronic device, including:

[0024] At least one processor; and,

[0025] A memory communicatively connected to the at least one processor; wherein,

[0026] The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, causes the at least one processor to perform the swing operation status monitoring method as described above.

[0027] The swing operation status monitoring method and device of this application have the following beneficial effects:

[0028] (1) Make full use of the historical data of the swing and combine it with the multiple linear regression method to establish a state prediction model. The model can be used to predict the swing's operating status data for monitoring.

[0029] (2) Unlike the previous simple monitoring of amusement facilities through sensor data, the swing characteristic value of the swing is selected. The swing time, maximum swing tension and maximum swing strain are predicted by the state prediction model to monitor the swing operation status. The range threshold of normal swing operation is determined by historical data to determine whether to issue an early warning. The historical data of the swing can be effectively used to monitor the swing operation status and improve the safety of swing operation.

[0030] (3) Not only monitor the tension change of the wire rope, but also use strain gauges to detect the maximum strain of the wire rope hanger corresponding to the maximum tension of the wire rope. The maximum strain of the wire rope hanger is compared with the threshold determined based on historical data to determine whether to issue an early warning, which can further improve the safety of the swing operation.

[0031] (4) Use a tension sensor to detect the actual maximum stress, compare the predicted swing time and predicted maximum tension with the actual swing time and actual maximum tension to determine whether to optimize the state model and provide an early warning, so as to update and optimize the prediction model in time when the model prediction data exceeds the error. Attached Figure Description

[0032] Figure 1 is a flowchart illustrating the swing operation status monitoring method according to an embodiment of the present invention.

[0033] Figure 2 is a schematic diagram of the swing according to an embodiment of the present invention.

[0034] Figure 3 shows the tension variation curve of the swing steel wire rope in an embodiment of the present invention. Detailed Implementation

[0035] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] The swing in this embodiment uses an arched tower, as shown in Figure 2, with two steel wire ropes 30. One end of each steel wire rope is connected to the arched tower 10 via a steel wire rope hanger 20, and the other end is connected to the passenger suspension device. Of course, it is not impossible to have more steel wire ropes and connect them to the arched tower 10 through more suspension points. The swing operates as follows: after the passenger is connected to the passenger suspension device, the motor drives the winch to wind the lifting steel wire rope and lift the passenger to a height of nearly 100 meters. After release, the swing swings several times, gradually decreasing in speed until it stops, or when the speed decreases to a level close to the operator's walking speed, the operator extends a landing bar to help the passenger stop.

[0037] In the following text, one cycle of a swing refers to the process from when the swing starts to swing from rest until it stops.

[0038] The swing operation status monitoring method of this embodiment, as shown in Figure 1, includes the following steps:

[0039] Step S1: Predict the swing characteristic values ​​of the first 4 swings in each operating cycle of the swing using a state prediction model. The swing characteristic values ​​include swing times T1, T2, T3 and T4, and the maximum tensions T1F1, T2F2, T3F3 and T4F4 in the first 4 swings.

[0040] The state prediction model can be established using data from multiple normal operating cycles of the swing, and modeled using a multiple linear regression method. The state prediction model is as follows:

[0041] Swing time T = a11 * number of passengers + a12 * wind speed + a13 * temperature + a20

[0042] Maximum tension TF = b11 * number of passengers + b12 * wind speed + b13 * temperature + b20

[0043] Among them, a11, a12, a13, a20, b11, b12, b13, and b20 are regression parameters, which can be estimated and determined using data from multiple normal operating cycles of the swing. To further optimize the regression parameters, parameter optimization can be performed every 500 normal operating cycles after the swing, thereby improving the accuracy of system predictions.

[0044] As shown in Figure 3, the tension change process of the wire rope during one operating cycle of the swing is as follows: First swing: The swing is released and begins to run freely. At this time, the tension value is the minimum. As the swing descends, the tension gradually increases. When it reaches the lowest position, the tension value is the maximum (T1F1), and the running speed is also the maximum. Subsequently, the swing begins to gradually move upward, and the tension gradually decreases. When the tension decreases to a certain extent, the swing begins to descend in the opposite direction. At this time, the first swing ends, and the swing time is T1.

[0045] Second swing: When the first swing reaches its highest point, the tension is at its minimum, and the swing begins to swing freely in the opposite direction. Similarly, when it swings to its lowest point, the tension is at its maximum (T2F2), and the speed is also at its maximum. Because it is a conversion of potential energy to kinetic energy, the swing experiences energy loss due to factors such as wind resistance during its operation. Therefore, the maximum tension and maximum speed of the second swing are smaller than those of the first swing. The duration of the second swing is T2.

[0046] The situation is the same for the third and fourth swings. The first swing is in the opposite direction to the second swing, and the third swing is in the opposite direction to the fourth swing. The wind direction has a very different effect on these two operating states.

[0047] Since the main purpose is to determine whether the equipment is operating abnormally and to ensure personnel safety, the status of the first four cycles can meet the detection requirements. Therefore, the characteristic values ​​such as the running time and maximum tension of the first four cycles can be taken in one operating cycle.

[0048] Step S2: Compare the predicted swing time T of the first four swings predicted by the state prediction model with the first warning threshold, and compare the predicted maximum tension TF of the first four swings with the second warning threshold. When the predicted swing time and predicted maximum tension of three consecutive operating cycles exceed the corresponding warning threshold, a maintenance warning is issued. Relevant personnel need to check the condition of the wire rope and the components connected to the wire rope to ensure the safe operation of the equipment before the swing can continue to operate.

[0049] The first and second warning thresholds can be obtained through analysis and statistics of historical normal operation data. For example, by analyzing data from 500 normal operation cycles, the maximum and minimum values ​​of various characteristic values ​​(swing time and maximum tension) can be calculated for different numbers of people riding the swing. These include the maximum swing time T1max and minimum swing time T1min in 500 first swings, the maximum swing time T2max and minimum swing time T2min in 500 second swings, and the maximum and minimum swing times in 500 third and fourth swings. Additionally, the maximum tension F1max and minimum tension F1min in 500 first swings, and the maximum and minimum tension in 500 second, third, and fourth swings can be calculated. It should be noted that the first and second warning thresholds obtained from different numbers of people riding the swing can be compared with the thresholds for the current number of riders.

[0050] Step S3: In each operating cycle, the tension of the wire rope is detected by a tension sensor installed on the wire rope to obtain the actual maximum tension and actual swing time of each of the first four swings. The predicted swing time and predicted maximum tension are compared with the actual swing time and actual maximum tension. If the deviation between the predicted swing time and predicted maximum tension and the actual values ​​for three consecutive operating cycles exceeds a fourth warning threshold, an early warning for optimization of the prediction model is issued. The fourth warning threshold can be selected between 5% and 10%. If the deviation exceeds the fourth warning threshold, relevant personnel need to check the condition of the wire rope and its connected components to ensure the safe operation of the equipment before the swing can continue to operate. Furthermore, the state prediction model needs to be reconstructed using data from new operating cycles. If the swing characteristic value does not exceed the fourth warning threshold for three consecutive operating cycles, the predicted values ​​of the predicted swing time and predicted maximum tension are considered accurate, and the prediction model does not need optimization. The swing does not need to stop operating (here, "not needing to stop operating" means that the swing operates according to normal operating mode, not that it will never stop).

[0051] The swing's operational status is monitored using two tension meters installed on the load-bearing wire rope and stress testing plates installed on two wire rope hangers.

[0052] Step S4: The moment when the wire rope hanger experiences the greatest force is when the swing is at its lowest point, i.e., when the tension of the wire rope on the swing is at its maximum. Simultaneously, the maximum tension is detected during each swing in each operating cycle, and the strain force of the wire rope hanger at this moment is also the greatest. The strain forces of the wire rope hanger corresponding to the maximum tension T1F1, T2F2, T3F3, and T4F4 in the previous four swings are taken as the maximum strain forces of the wire rope hanger in the current swing. Thus, the maximum strain forces F1P1, F2P2, F3P3, and F4P4 of the wire rope hanger corresponding to the maximum tension T1F1, T2F2, T3F3, and T4F4 in the previous four swings are obtained.

[0053] Step S5: Compare the maximum strain forces F1P1, F2P2, F3P3, and F4P4 of the wire rope hanger during the first four swings with the third warning threshold. If the third warning threshold is exceeded for three consecutive operating cycles, a maintenance warning is issued. Relevant personnel must inspect the hanger to ensure the safe operation of the equipment before the swing can continue. The strain force detection on the wire rope hanger is closely related to the tension of the supporting wire rope. Since the tension of the wire rope changes with its position during movement, the strain force detected on the hanger also changes. If the maximum tension of the wire rope does not change, but a change in the maximum strain force is detected, it indicates that the hanger is damaged, and relevant personnel must inspect the hanger.

[0054] The third warning threshold can be obtained through analysis and statistics of historical normal operation data. For example, by analyzing data from 500 normal operation cycles, the maximum strain force of the wire rope suspension seat in each of the first four swings in each of the 500 normal operation cycles can be calculated when different numbers of people are riding the swing. From the 500 normal operation cycles, the maximum and minimum values ​​of the first, second, third, and fourth swings can be identified, forming the corresponding third warning thresholds. For example, the maximum and minimum values ​​of the maximum strain force of the wire rope suspension seat can be identified from the 500 first swings. It should be noted that the third warning threshold obtained from different numbers of people riding the swing can be selected for comparison with the third warning threshold that corresponds to the current number of riders.

[0055] It should be noted that although this embodiment selects the first 4 swing feature values ​​of the running cycle, this application is not limited to taking the swing feature values ​​of the first few swings in a running cycle. It can be the swing feature values ​​of the first N swings, where N is a natural number. For example, N can also be 3, 5, or 6.

[0056] Of course, the present invention may have other various embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art can make various corresponding changes and modifications according to the present invention, but these corresponding changes and modifications are all within the protection scope of the claims of the present invention.

Claims

1. A method for monitoring the operating status of a swing, characterized in that, Includes the following steps: The swing's characteristic values ​​for the first N swings in each operating cycle are predicted using a state prediction model. These characteristic values ​​include the predicted swing time T and the predicted maximum tension TF for each swing. The state prediction model is obtained by modeling using multiple linear regression methods based on data from multiple normal operating cycles of the swing. The predicted swing time T for each of the first N swings is compared with a first warning threshold, and the predicted maximum tension TF for each of the first N swings is compared with a second warning threshold. When the predicted swing time and predicted maximum tension for M consecutive operating cycles exceed the corresponding warning thresholds, a maintenance warning is issued. During the swing's operation, tension sensors installed on the steel wire rope are used to detect the rope's tension, obtaining the actual maximum tension of each swing in the first N swings, as well as the actual swing time for each swing. The predicted swing time and predicted maximum tension are compared with the actual swing time and actual maximum tension. When the deviation between the predicted swing time and predicted maximum tension and the actual swing time and actual maximum tension in the first N swings of M consecutive operating cycles exceeds the fourth warning threshold, an early warning for optimization of the state prediction model is issued. The state prediction model is then reconstructed using data from multiple new operating cycles.

2. The swing operation status monitoring method according to claim 1, characterized in that, It also includes taking the strain force of the wire rope hanger corresponding to the moment of maximum tension of the wire rope in each of the previous N swings as the maximum strain force of the wire rope hanger in that swing, thereby obtaining the maximum strain force of the wire rope hanger corresponding to the moment of maximum tension of the wire rope in each of the previous N swings; comparing the maximum strain force of the wire rope hanger in each of the previous N swings with the third warning threshold, and issuing a maintenance warning if it exceeds the third warning threshold for M consecutive operating cycles.

3. The swing operation status monitoring method according to claim 1, characterized in that, The state prediction model is as follows: Predicted swing time T = a11 Passenger capacity + a12 Wind speed +a13 Temperature + a20 predicts maximum tension TF = b11 Passenger capacity + b12 Wind speed + b13 Temperature + b20, where a11, a12, a13, a20, b11, b12, b13, and b20 are regression parameters, estimated and determined using data from multiple normal operating cycles of the swing.

4. The swing operation status monitoring method according to claim 1, characterized in that, The parameters of the state prediction model are optimized using data from at least 500 normal operating cycles of the swing.

5. The swing operation status monitoring method according to claim 2, characterized in that, The third warning threshold is formed by statistically analyzing the maximum and minimum values ​​of the maximum strain force of the wire rope suspension seat during the first N swings of a swing with different numbers of people in at least 500 normal operating cycles.

6. The swing operation status monitoring method according to claim 1, characterized in that, The first and second warning thresholds are determined by statistically analyzing the swing time and the maximum and minimum values ​​of the maximum tension in each of the first N swings during at least 500 normal operating cycles when different numbers of people ride the swing.

7. The swing operation status monitoring method according to claim 1, characterized in that, The value of N is 4.

8. The method for monitoring the operating status of a swing according to claim 1, characterized in that, The value of M is 3.

9. An electronic device, characterized in that, include: At least one processor; And a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to cause the at least one processor to perform the swing operation status monitoring method as described in any one of claims 1 to 8.

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