Synchronous winding and unwinding control method for pipe winding device

Abstract

The invention discloses a synchronous winding and unwinding control method for a pipe winder, which relates to the technical field of tension adjustment control and comprises the following steps of: arranging a tension monitoring unit on a pipeline, and acquiring tension information of the pipeline in real time through the tension monitoring unit; dynamic compensation processing is carried out on the collected pipeline tension information to obtain real tension data; the method comprises the following steps: collecting real tension data of a pipeline at a time, comparing the tension data with a preset tension threshold range, calculating a primary tension deviation value, determining speed regulation data based on the primary tension deviation value, and generating a first regulation control signal based on the speed regulation data; and the first control signal is transmitted to a controller, and the controller controls the pipe coiling device to adjust and control the pipeline so as to adjust the tension of the pipeline. According to the invention, quick response and adjustment can be realized, the operation complexity is reduced, the working efficiency is improved, the protection effect on the pipeline is improved, and the simple and efficient adaptive control of the pipe coiling device is realized.

Description

Technical Field

[0001] The invention relates to the technical field of tension adjustment control, and in particular to a method for controlling synchronous winding and unwinding of a hose reel. Background Art

[0002] As the fire protection field has higher and higher requirements for fire protection equipment and technology, fire protection equipment shows a diversified development trend of field differentiation, equipment specialization, and intelligent automation. The complex and advanced fire protection equipment using hydraulic technology has a tendency to increase year by year. Some complex hydraulically driven equipment is located at the top of the lifting system, or extends outward through the top of the lifting boom. This requires a hose reel to reel up the hydraulic oil pipe to prevent the oil pipe from bending and becoming messy; when operating the lifting system or when the lifting wire rope needs to move, the hydraulic oil pipe also needs to move with it, which requires controlling the rotation of the hose reel to release or reel the oil pipe line. In order to ensure that the pipeline is consistent with the telescopic length of the lifting boom or the lifting length of the wire rope, the hose reel needs to be continuously adjusted while controlling the telescopic length of the lifting boom or the lifting of the wire rope. This increases the complexity of the operation and reduces the operating efficiency. In order to improve the operating efficiency and the level of equipment automation, it is very necessary to control the synchronous reeling and unwinding of the hose reel.

[0003] At present, the action control of the lifting system and the hose reel is mostly carried out by separate operation. When the lifting boom is extended or the wire rope is hoisted, it is necessary to adjust the hose reel to release or reel in the length of the pipeline at the same time, so that the extension of the pipeline is synchronized with the extension of the boom or the lifting length of the wire rope. However, it is difficult to ensure the synchronization of the operation during independent operation, resulting in messy or uneven reeling of the pipeline. When the release of the pipeline is slower than the extension of the boom or the lifting of the wire rope, the pipeline is easily pulled, resulting in irreversible damage to the pipeline, reducing its service life, and even causing pipeline breakage in severe cases. It is not friendly to the operator to operate independently, and he often gets flustered, which greatly reduces the operating efficiency.

[0004] For example, the patent application with application publication number CN116812640A, application publication date 2023.09.29, and titled "Tension Control Method and Device" sets a target first interval with a larger variation range, detects the first tension, and iteratively adjusts the angular velocity of the winding and unwinding mechanism to achieve stability in the tension fluctuation amplitude. In the balance stage of the winding device, a target second interval with a smaller variation range is set, and the angular velocity of the winding and unwinding mechanism is iteratively adjusted by periodically detecting the second tension to achieve stability in the tension fluctuation amplitude within a smaller range, thereby achieving more precise tension control.

[0005] The shortcoming of the prior art including the above-mentioned application is that when the tension is detected by the tension sensor, when the tension data is greater than the preset pre-set range, the staff is required to adjust the speed of the winder based on experience or in a small range and then detect the tension changes in real time and make multiple iterative adjustments. The operation is cumbersome and cannot respond to adjustments quickly, which increases the complexity of the operation, reduces the operating efficiency, and easily causes damage to the pipeline and reduces the service life of the pipeline. Summary of the invention

[0006] The object of the present invention is to provide a method for controlling the synchronous winding and unwinding of a hose reel, so as to solve the above-mentioned deficiencies in the prior art.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a method for controlling synchronous winding and unwinding of a hose reel, comprising the following steps:

[0008] S01: a tension monitoring unit is set on the pipeline, the tension information of the pipeline is collected in real time through the tension monitoring unit, and the collected pipeline tension information is dynamically compensated to obtain real tension data;

[0009] S02: collecting real tension data of the pipeline once, comparing the tension data with a preset tension threshold range, calculating a primary tension deviation value, determining speed regulation data based on the primary tension deviation value, and generating a first regulation control signal based on the speed regulation data;

[0010] S03: transmitting the first control signal to the controller, and controlling the hose reel through the controller to adjust the pipeline to adjust the tension of the pipeline;

[0011] S04: collecting pipeline real tension data for a second time, associating the pipeline real tension data collected once and the pipeline real tension data collected twice to calculate a reference adjustment coefficient, calculating secondary tension speed regulation data based on the reference adjustment coefficient; and generating a second control signal based on the secondary tension speed regulation data;

[0012] S05: transmitting the second control signal to the controller, controlling the hose reel through the controller to adjust and control the pipeline, collecting the adjusted pipeline tension data, and when the pipeline tension data meets the preset tension threshold range, it indicates that the regulation is completed;

[0013] S06: When the pipeline tension data does not meet the preset tension threshold range, repeat step S04 to perform continuous adjustment control so that the pipeline tension data remains within the tension threshold range.

[0014] As a further description of the above technical solution: the tension monitoring unit is arranged on the pipeline specifically as follows:

[0015] The tension detection unit includes a detection sensor, which is installed on the pipeline part pulled out downstream of the hose reel to measure the pipeline tension data, and the measuring point of the detection sensor presses down or pushes up the pipeline to the pre-tightening force through an elastic device.

[0016] As a further description of the above technical solution: the collected pipeline tension data is compared with the preset tension threshold range, and the tension deviation value is calculated as follows:

[0017] The calculation method of the primary tension deviation value is:

[0018] F c1 is the primary tension deviation value, F1 represents the pipeline tension data collected once, and F s Indicates the upper limit of the preset tension threshold range, F x Indicates the lower limit of the preset tension threshold range.

[0019] As a further description of the above technical solution: determining the speed control data based on the primary tension deviation value, and generating the first adjustment control signal based on the speed control data is specifically:

[0020] Preset tension deviation value to adjust comparison threshold F m 、F n , where F m >F n >0;

[0021] When F c1 <F n , generate first-level speed regulation data;

[0022] When F m >F c1 >F n , generate secondary speed regulation data;

[0023] When F c1 >F m , generate three-level unwinding speed regulation data;

[0024] A first adjustment control signal is generated based on the speed adjustment data.

[0025] As a further description of the above technical solution: the reference adjustment coefficient calculated by associating the pipeline tension data collected once and the pipeline tension data collected twice is specifically:

[0026] Calculate the reference adjustment coefficient K f , Wherein F0 represents the tension data collected initially, and the interval time between the tension data collected initially and the pipeline tension data collected once is the same as the interval time between the pipeline tension data collected once and the pipeline tension data collected twice.

[0027] As a further description of the above technical solution: the speed regulation data for calculating the secondary tension based on the reference adjustment coefficient is specifically:

[0028] The speed adjustment data V1 of the hose reel when the first control signal is used to adjust and control the hose reel is collected, and the reference adjustment coefficient K is correlated based on the speed adjustment data V1 of the hose reel. f , calculate the constant speed data V of the secondary tension 2h ,in

[0029] Constant speed regulation data V based on secondary tension 2h Correlation calculation of secondary tension compensation speed regulation data V 2t , Where t represents the interval between the pipeline tension data collected once and the pipeline tension data collected twice;

[0030] Integrate the constant speed data of secondary tension V 2h And the compensation speed data V 2t Get the speed regulation data of secondary tension:

[0031] The secondary tension speed regulation data is:

[0032] As a further description of the above technical solution: based on the constant speed regulation data of the secondary tension, a second control signal is generated and transmitted to the controller, and the controller controls the hose reel to adjust the pipeline. The specific control process is: at the time node of the secondary collection of pipeline tension data, the speed of the hose reel is increased by V 2h +V 2t , when the hose reel has been running for time t, the speed of the hose reel is reduced by V 2t .

[0033] As a further description of the above technical solution: performing dynamic compensation processing on the collected pipeline tension information to obtain tension data specifically includes the following steps:

[0034] Collect historical training data of detection sensors in advance, and train the tension data dynamic deviation machine learning model based on the historical training data;

[0035] Input the currently collected pipeline tension information into the tension data dynamic deviation machine learning model to obtain a dynamic deviation value;

[0036] The dynamic deviation value is added to the currently collected tension data to obtain the actual tension data.

[0037] As a further description of the above technical solution: the historical training data of the detection sensor collected in advance is specifically:

[0038] The historical training data of the detection sensor collected is several groups of historical tension information of the detection sensor collected in the experimental environment; the experimental environment is a tester controlling the detection environment and state changes of the detection sensor to collect the tension information of each detection sensor;

[0039] The tension information data of the detection sensor includes actual tension data, tension data collected by the detection sensor, amplitude data during detection by the detection sensor, and frequency data.

[0040] As a further description of the above technical solution: Training the tension data dynamic deviation machine learning model based on historical training data is specifically:

[0041] The tension data collected by the detection sensor in each set of historical training data, the amplitude data during the detection by the detection sensor, and the frequency data are used as the input of the machine learning model. The dynamic deviation value of each set of historical training data is used as the output of the machine learning model. The difference between the actual tension data corresponding to each set of feature data and the tension data collected by the detection sensor is used as the prediction target. The minimized sum of prediction accuracies is used as the training target.

[0042] The calculation formula for prediction accuracy is: i =(A i -B i ) 2 , where i is the number of historical training data, k i is the prediction accuracy, A i is the predicted dynamic deviation value corresponding to the i-th group of historical training data, B i The machine learning model is trained based on the difference between the actual tension data corresponding to the i-th group of historical training data and the tension data collected by the detection sensor, and the training is stopped when the sum of the prediction accuracies reaches convergence.

[0043] In the above technical scheme, a method for synchronous winding and unwinding control of a hose reel provided by the present invention collects the real tension data of the pipeline once, generates a first adjustment control signal based on the primary tension deviation value to adjust the hose reel, collects the real tension data of the pipeline for a second time after an interval, calculates a reference adjustment coefficient by associating the pipeline tension data collected once and the pipeline tension data collected for the second time, obtains the constant speed regulation data of the secondary tension and the secondary tension compensation speed regulation data based on the reference adjustment coefficient, finally integrates the secondary tension speed regulation data, and generates a second control signal based on the secondary tension speed regulation data to adjust and control the hose reel. Compared with the traditional method of iteratively adjusting the speed of the unwinding and winding mechanism by adjusting the reel speed according to the experience of the staff or in a small range, the method is convenient to operate, can respond to the adjustment quickly, reduces the complexity of operation, improves the work efficiency, improves the protection effect on the pipeline, and realizes the adaptive control of the hose reel in a simple and efficient way;

[0044] Based on the actual working environment conditions of the detection sensor, historical training data is collected in advance to train a tension data dynamic deviation machine learning model, and the currently collected pipeline tension information is input into the tension data dynamic deviation machine learning model to obtain a dynamic deviation value. Based on the dynamic deviation value, the current collected tension data is compensated and adjusted to achieve compensation for the accuracy of the data collected by the detection sensor, significantly improving the accuracy of its dynamic collection data, thereby improving the accuracy and reliability of the feedback control reel adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0046] Figure 1 A flow chart of a method for controlling synchronous winding and unwinding of a hose reel is provided for an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of a reeling system corresponding to a synchronous reeling and unwinding control method of a hose reel is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0049] Example 1: Please refer to Figure 1-2 The embodiment of the present invention provides a technical solution: a method for controlling synchronous winding and unwinding of a hose reel, which is used to control winding and unwinding of a hose reel system. Specifically, the hose reel system includes a hose reel and a boom, a pipeline is wound on the hose reel, and the end of the pipeline is connected to the end device of the boom. When the boom is lifted or telescopically adjusted, the hose reel is controlled to reel in or release the pipeline to automatically adapt to the boom movement, including the following steps:

[0050] S01: a tension monitoring unit is set on the pipeline, and the tension information of the pipeline is collected in real time through the tension monitoring unit; and the collected pipeline tension information is dynamically compensated to obtain real tension data;

[0051] S02: Collecting the real tension data of the pipeline once, and comparing the tension data with the preset tension threshold range, wherein the preset tension threshold range is a reasonable tension threshold range set by the technician according to factors such as the material, diameter, and use environment of the pipeline, which includes an upper threshold and a lower threshold, calculating a primary tension deviation value, determining the speed regulation data based on the primary tension deviation value, and generating a first regulation control signal based on the speed regulation data;

[0052] S03: Transmitting the first control signal to the controller. Specifically, the first control signal is transmitted to the controller in a preferential or wireless manner, and the controller controls the hose reel to adjust the pipeline to adjust the pipeline tension. The controller adjusts and controls the hose reel specifically as follows: the hose reel includes a winding mechanism and a servo drive motor, and the servo drive motor is connected to the winding mechanism through a coupling. After receiving the first control signal, the controller parses and executes corresponding control instructions, thereby controlling the servo motor to act to drive the winding mechanism to adjust.

[0053] S04: collecting pipeline real tension data for the second time, specifically, collecting pipeline tension information in real time through a tension monitoring unit at intervals t, and performing dynamic compensation processing on the collected pipeline tension information to obtain pipeline real tension data, associating the pipeline real tension data collected once and the pipeline real tension data collected twice to calculate a reference adjustment coefficient, and calculating constant speed regulation data of secondary tension based on the reference adjustment coefficient; and generating a second control signal based on the constant speed regulation data of secondary tension;

[0054] S05: transmitting the second control signal to the controller, controlling the hose reel through the controller to adjust and control the pipeline, collecting the adjusted pipeline tension data, and when the pipeline tension data meets the preset tension threshold range, it indicates that the regulation is completed;

[0055] S06: When the pipeline tension data does not meet the preset tension threshold range, repeat step S04 to perform continuous adjustment control so that the pipeline tension data remains within the tension threshold range.

[0056] Furthermore, the tension monitoring unit is arranged on the pipeline specifically as follows:

[0057] The tension detection unit includes a detection sensor, which is installed on the pipeline part pulled out downstream of the hose reel to measure the pipeline tension data, and the measuring point of the detection sensor presses down or pushes up the pipeline to the pre-tightening force through an elastic device.

[0058] Furthermore, the collected pipeline tension data is compared with the preset tension threshold range, and the tension deviation value is calculated as follows:

[0059] The calculation method of the primary tension deviation value is:

[0060] F c1 is the primary tension deviation value, F1 represents the pipeline tension data collected once, and F s Indicates the upper limit of the preset tension threshold range, F x Indicates the lower limit of the preset tension threshold range.

[0061] The speed regulation data is determined based on the primary tension deviation value, and the first regulation control signal is generated based on the speed regulation data as follows:

[0062] Preset tension deviation value to adjust comparison threshold F m 、F n , where F m >F n >0;

[0063] When F c1 <F n , generate first-level speed regulation data;

[0064] When F m >F c1 >F n , generate secondary speed regulation data;

[0065] When F c1 >F m , generate three-level unwinding speed regulation data;

[0066] A first adjustment control signal is generated based on the speed adjustment data.

[0067] The preset tension deviation value adjusts the comparison threshold F m 、F n Preset values ​​for technicians, making it easier to make corresponding adjustments when tension deviations occur.

[0068] Furthermore, the reference adjustment coefficient is calculated by associating the pipeline tension data collected once and the pipeline tension data collected twice as follows:

[0069] Calculate the reference adjustment coefficient K f , Wherein F0 represents the tension data collected initially, and the interval time between the tension data collected initially and the pipeline tension data collected once is the same as the interval time between the pipeline tension data collected once and the pipeline tension data collected twice.

[0070] Furthermore, the secondary tension speed regulation data is calculated based on the reference adjustment coefficient as follows:

[0071] The speed adjustment data V1 of the hose reel when the first control signal is used to adjust and control the hose reel is collected, and the reference adjustment coefficient K is correlated based on the speed adjustment data V1 of the hose reel. f , calculate the constant speed data V of the secondary tension 2h ,in

[0072] Constant speed regulation data V based on secondary tension 2h Correlation calculation of secondary tension compensation speed regulation data V 2t , Where t represents the interval between the pipeline tension data collected once and the pipeline tension data collected twice;

[0073] Integrate the constant speed data of secondary tension V 2h And the compensation speed data V 2t Get secondary tension speed regulation data:

[0074] The constant speed regulation data of tension is:

[0075] The second control signal is generated based on the constant speed regulation data of the secondary tension and transmitted to the controller. The controller controls the hose reel to adjust the pipeline. The specific control process is: at the time node of the secondary collection of pipeline tension data, the speed of the hose reel is increased by V 2h +V 2t , when the hose reel has been running for time t, the speed of the hose reel is reduced by V 2t .

[0076] The present embodiment provides a method for synchronous winding and unwinding control of a hose reel. After collecting the real tension data of the pipeline once, a first adjustment control signal is generated based on a primary tension deviation value to adjust the hose reel. After a certain period of time, the real tension data of the pipeline is collected for a second time. A reference adjustment coefficient is calculated by associating the pipeline tension data collected once and the pipeline tension data collected for the second time. Constant speed regulation data of the secondary tension and secondary tension compensation speed regulation data are calculated based on the reference adjustment coefficient. The secondary tension speed regulation data are finally integrated to obtain the secondary tension speed regulation data. A second control signal is generated based on the secondary tension speed regulation data to adjust and control the hose reel. Compared with the traditional method of iteratively adjusting the speed of the winding and unwinding mechanism by the staff according to experience or adjusting the reel speed in a small range, the method is easy to operate and can respond to adjustments quickly, thereby reducing the complexity of operation, improving work efficiency, and improving the protection effect on the pipeline, thereby realizing simple and efficient adaptive control of the hose reel.

[0077] Embodiment 2: Dynamic compensation processing of collected pipeline tension information to obtain tension data specifically includes the following steps:

[0078] Collect historical training data of detection sensors in advance, and train the tension data dynamic deviation machine learning model based on the historical training data;

[0079] The historical training data of the detection sensor collected in advance is as follows:

[0080] The historical training data of the detection sensor collected is several groups of historical tension information of the detection sensor collected in the experimental environment; it should be understood that the several groups of historical tension information of the detection sensor collected in the experimental environment are to simulate the actual working scene of the detection sensor in the experimental environment, and to collect the tension information of the detection sensor by adjusting the tension on the pipeline, and the experimental environment is a tester controlling the detection environment and state changes of the detection sensor to collect the tension information of each detection sensor;

[0081] The tension information data of the detection sensor includes actual tension data, tension data collected by the detection sensor, amplitude data during detection by the detection sensor, and frequency data;

[0082] The specific training model of the dynamic deviation of tension data based on historical training data is as follows:

[0083] The tension data collected by the detection sensor in each set of historical training data, the amplitude data during the detection by the detection sensor, and the frequency data are used as the input of the machine learning model. The dynamic deviation value of each set of historical training data is used as the output of the machine learning model. The difference between the actual tension data corresponding to each set of feature data and the tension data collected by the detection sensor is used as the prediction target. The minimized sum of prediction accuracies is used as the training target.

[0084] The calculation formula for prediction accuracy is: i =(A i -B i ) 2 , where i is the number of historical training data, k i is the prediction accuracy, A i is the predicted dynamic deviation value corresponding to the i-th group of historical training data, B i The machine learning model is trained based on the difference between the actual tension data corresponding to the i-th group of historical training data and the tension data collected by the detection sensor, and the training is stopped when the sum of the prediction accuracies reaches convergence.

[0085] Input the currently collected pipeline tension information into the tension data dynamic deviation machine learning model to obtain a dynamic deviation value; wherein the collected pipeline tension information includes tension data collected by the detection sensor, amplitude data during detection by the detection sensor, and frequency data;

[0086] The dynamic deviation value is added to the currently collected tension data to obtain the actual tension data.

[0087] It should be noted that the tension of the pipeline is detected in real time by the detection sensor, and the feedback control reel is used for adjustment. However, the dynamic performance of the detection sensor is poor when detecting the tension of the pipeline. The vibration generated by the movement of the pipeline causes large fluctuations in the data collected by the detection sensor, affecting the accuracy and effect of the control and adjustment. It is also easy to cause damage to the pipeline and reduce the service life of the pipeline. Based on the actual working environment conditions of the detection sensor, historical training data is collected in advance to train a tension data dynamic deviation machine learning model, and the currently collected pipeline tension information is input into the tension data dynamic deviation machine learning model to obtain a dynamic deviation value; based on the dynamic deviation value, the currently collected tension data is compensated and adjusted to compensate for the accuracy of the data collected by the detection sensor, which significantly improves the accuracy of its dynamic collection data, thereby improving the accuracy and reliability of the feedback control reel adjustment.

[0088] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for controlling synchronous winding and unwinding of a hose reel, characterized in that: The following steps are involved: S01: A tension monitoring unit is set on the pipeline, and the tension information of the pipeline is collected in real time through the tension monitoring unit; And dynamically compensate the collected pipeline tension information to obtain real tension data; S02: collecting real tension data of the pipeline once, comparing the tension data with a preset tension threshold range, calculating a primary tension deviation value, determining speed regulation data based on the primary tension deviation value, and generating a first regulation control signal based on the speed regulation data; S03: transmitting the first control signal to the controller, and controlling the hose reel through the controller to adjust the pipeline to adjust the tension of the pipeline; S04: collecting pipeline real tension data for a second time, associating the pipeline real tension data collected once and the pipeline real tension data collected twice to calculate a reference adjustment coefficient, and calculating secondary tension speed regulation data based on the reference adjustment coefficient; and generating a second control signal based on the secondary tension speed regulation data; S05: transmitting the second control signal to the controller, controlling the hose reel through the controller to adjust and control the pipeline, collecting the adjusted pipeline tension data, and when the pipeline tension data meets the preset tension threshold range, it indicates that the regulation is completed; S06: When the pipeline tension data does not meet the preset tension threshold range, repeat step S04 to perform continuous adjustment control so that the pipeline tension data remains within the tension threshold range.

2. A method for controlling synchronous winding and unwinding of a hose reel according to claim 1, characterized in that: The specific steps of setting up a tension monitoring unit on the pipeline are as follows: The tension detection unit includes a detection sensor, which is installed on the pipeline part pulled out downstream of the hose reel to measure the pipeline tension data, and the measuring point of the detection sensor presses down or pushes up the pipeline to the pre-tightening force through an elastic device.

3. A method for controlling synchronous winding and unwinding of a hose reel according to claim 1, characterized in that: Compare the collected pipeline tension data with the preset tension threshold range and calculate the tension deviation value as follows: The calculation method of the primary tension deviation value is: F c1 is the primary tension deviation value, F1 represents the pipeline tension data collected once, and F s Indicates the upper limit of the preset tension threshold range, F x Indicates the lower limit of the preset tension threshold range.

4. A method for controlling synchronous winding and unwinding of a hose reel according to claim 3, characterized in that: The speed regulation data is determined based on the primary tension deviation value, and the first regulation control signal is generated based on the speed regulation data as follows: Preset tension deviation value to adjust comparison threshold F m 、F n , where F m >F n >0; When F c1 <F n , generate first-level speed regulation data; When F m >F c1 >F n , generate secondary speed regulation data; When F c1 >F m , generate three-level unwinding speed regulation data; A first adjustment control signal is generated based on the speed adjustment data.

5. A method for controlling synchronous winding and unwinding of a hose reel according to claim 1, characterized in that: The reference adjustment coefficient calculated by associating the pipeline tension data collected once and the pipeline tension data collected twice is as follows: Calculate the reference adjustment coefficient K f , Wherein F0 represents the tension data collected initially, and the interval time between the tension data collected initially and the pipeline tension data collected once is the same as the interval time between the pipeline tension data collected once and the pipeline tension data collected twice.

6. A method for controlling synchronous winding and unwinding of a hose reel according to claim 5, characterized in that: The secondary tension speed regulation data calculated based on the reference adjustment coefficient is as follows: The speed adjustment data V1 of the hose reel when the first control signal is used to adjust and control the hose reel is collected, and the reference adjustment coefficient K is correlated based on the speed adjustment data V1 of the hose reel. f , calculate the constant speed data V of the secondary tension 2h ,in Constant speed regulation data V based on secondary tension 2h Correlation calculation of secondary tension compensation speed regulation data V 2t , Where t represents the interval between the pipeline tension data collected once and the pipeline tension data collected twice; Integrate the constant speed data of secondary tension V 2h And the compensation speed data V 2t Get secondary tension speed regulation data: The secondary tension speed regulation data is:

7. A method for controlling synchronous winding and unwinding of a hose reel according to claim 6, characterized in that: The second control signal is generated based on the constant speed regulation data of the secondary tension and transmitted to the controller. The controller controls the hose reel to adjust the pipeline. The specific control process is: at the time node of the secondary collection of pipeline tension data, the speed of the hose reel is increased by V 2h +V 2t , when the hose reel has been running for time t, the speed of the hose reel is reduced by V 2t .

8. A method for controlling synchronous winding and unwinding of a hose reel according to claim 1, characterized in that: The process of dynamically compensating the collected pipeline tension information to obtain tension data specifically includes the following steps: Collect historical training data of detection sensors in advance, and train the tension data dynamic deviation machine learning model based on the historical training data; Input the currently collected pipeline tension information into the tension data dynamic deviation machine learning model to obtain a dynamic deviation value; The dynamic deviation value is added to the currently collected tension data to obtain the actual tension data.

9. A method for controlling synchronous winding and unwinding of a hose reel according to claim 8, characterized in that: The historical training data of the detection sensor collected in advance is as follows: The historical training data of the detection sensor collected is several groups of historical tension information of the detection sensor collected in the experimental environment; the experimental environment is a tester controlling the detection environment and state changes of the detection sensor to collect the tension information of each detection sensor; The tension information data of the detection sensor includes actual tension data, tension data collected by the detection sensor, amplitude data during detection by the detection sensor, and frequency data.

10. A method for controlling synchronous winding and unwinding of a hose reel according to claim 9, characterized in that: The specific training model of the dynamic deviation of tension data based on historical training data is as follows: The tension data collected by the detection sensor in each set of historical training data, the amplitude data during the detection by the detection sensor, and the frequency data are used as the input of the machine learning model. The dynamic deviation value of each set of historical training data is used as the output of the machine learning model. The difference between the actual tension data corresponding to each set of feature data and the tension data collected by the detection sensor is used as the prediction target. The minimized sum of prediction accuracies is used as the training target. The calculation formula for prediction accuracy is: i =(A i -B i ) 2 , where i is the number of historical training data, k i is the prediction accuracy, A i is the predicted dynamic deviation value corresponding to the i-th group of historical training data, B i The machine learning model is trained based on the difference between the actual tension data corresponding to the i-th group of historical training data and the tension data collected by the detection sensor, and the training is stopped when the sum of the prediction accuracies reaches convergence.

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