Gate lifting equipment operation monitoring system and method based on data analysis

Abstract

The invention discloses a gate lifting equipment operation monitoring system and method based on data analysis, and belongs to the field of lifting equipment operation. Lifting equipment operation data, swing data, water flow impact data and next-stage water flow prediction in the gate lifting process are comprehensively utilized to form a multi-step and multi-dimensional evaluation and early warning system; according to the method, comprehensive guarantee can be provided for the safety and stability of the gate lifting process, multi-dimensional analysis of the gate lifting process can be achieved by comprehensively utilizing the operation data, the swing data, the water flow impact data and the next-stage water flow prediction of the lifting equipment, and the evaluation accuracy is improved.

Description

Technical Field

[0001] The present application relates to the field of lifting equipment operation, and more specifically to a gate lifting equipment operation monitoring system and method based on data analysis. Background Art

[0002] Hydraulic gate lifting equipment is a key facility used to control water flow in water conservancy projects. Its function is to adjust the flow and direction of water flow by lifting and lowering the gate. These devices play an important role in water conservancy projects such as dams, rivers, and ports to ensure the effective use of water resources and flood control safety. During the operation of hydraulic gate lifting equipment, its status needs to be monitored in real time to avoid the impact of hydraulic gate lifting equipment failure on water conservancy work. At this time, a gate lifting equipment operation monitoring system is needed; However, although the existing gate lifting equipment operation monitoring system can realize basic monitoring and data collection of the equipment to a certain extent, there are still some problems that limit its performance and application effect. The existing system is mainly based on past data, lacks prediction capabilities based on deep learning or machine learning, and cannot realize early warning of equipment failures. The monitoring system usually relies on a single indicator (such as current, vibration) for evaluation, and cannot comprehensively analyze the operating status of the equipment from multiple dimensions. It fails to fully consider the impact of environmental factors such as water flow impact and weather changes on the gate lifting equipment, resulting in inaccurate evaluation results, lack of in-depth understanding of the equipment's failure mode, and difficulty in identifying potential complex failures. Most of the existing technologies have the above problems; In order to solve the problems raised by this background technology, the present application designs a gate lifting equipment operation monitoring system and method based on data analysis. Summary of the invention

[0003] In response to the shortcomings of the prior art, the present application proposes a gate lifting equipment operation monitoring system and method based on data analysis. The present application first performs a lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process, and then evaluates the lifting stability based on the swing data and water flow impact data during the gate lifting process. Then, based on the lifting stability assessment results and the water flow conditions in the next stage, an abnormal prediction of the gate lifting process in the next stage is performed. Finally, based on the abnormal prediction results of the gate lifting process in the next stage, an early warning of the lifting process is issued. The present application comprehensively utilizes the lifting equipment operation data, swing data, water flow impact data and water flow prediction for the next stage during the gate lifting process to form a multi-step, multi-dimensional evaluation and early warning system, which can provide comprehensive protection for the safety and stability of the gate lifting process. By comprehensively utilizing the lifting equipment operation data, swing data, water flow impact data and water flow prediction for the next stage, a multi-dimensional analysis of the gate lifting process can be achieved, thereby improving the accuracy of the evaluation.

[0004] To achieve the above purpose, the present application provides the following technical solution: a gate lifting equipment operation monitoring method based on data analysis, which includes the following specific steps: S1. Obtaining the operation data of the lifting equipment during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process; S2. Performing a health assessment of the lifting equipment operation based on the lifting equipment operation data during the gate lifting process; S3, evaluate the lifting stability based on the swing data and water flow impact data during the gate lifting process; S4, based on the lifting stability assessment results and the water flow conditions in the next stage, the abnormal prediction of the gate lifting process in the next stage is performed; S5. Based on the abnormal prediction results of the gate lifting process in the next stage, an early warning of the lifting process is issued to remind maintenance personnel to maintain the gate.

[0005] It should be noted here that as a preferred technical solution for the gate lifting equipment operation monitoring method based on data analysis, the lifting equipment operation data during the gate lifting process includes equipment torque, equipment voltage, equipment current and equipment temperature during the gate lifting process, etc., which reflect the equipment operation data; the swing data during the gate lifting process includes speed, swing frequency and swing amplitude during the gate lifting process, etc., which reflect the gate data during the gate lifting process; the water flow impact data includes water velocity and water level data of the water flow impacting the gate, etc., which reflect the water flow impact data.

[0006] It should be noted that, as a preferred technical solution of the gate lifting equipment operation monitoring method based on data analysis, the lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process includes the following specific steps: S21, obtaining the lifting equipment operation data during the gate lifting process at the corresponding time, and substituting it into the lifting equipment safety assessment formula at the corresponding time to perform the lifting equipment safety assessment at the corresponding time, wherein the lifting equipment safety assessment formula at the corresponding time is: , where n is the type of lifting equipment operation data, ci is the impact coefficient of the i-th lifting equipment operation data on safety, git is the value of the i-th lifting equipment operation data at time t, and gim is the median value of the safety range of the i-th lifting equipment operation data; S22, obtaining the relative height data of the gate and the moment data of the lifting device at the corresponding time, and obtaining the safety assessment result of the lifting device at the corresponding time, analyzing the difficulty of maintaining the equipment safely based on the relative height data of the gate and the weight and lifting resistance of the gate at the corresponding time, and performing the equipment health assessment at the corresponding time based on the safety assessment result of the lifting device and the difficulty of maintaining the equipment safely. It should be noted that the lifting resistance here includes water resistance and friction resistance; S23, obtaining the equipment health assessment result at each moment in the lifting process, integrating the time length and then dividing it by the lifting time to obtain the equipment health assessment result in the lifting process.

[0007] It should be noted that, as a preferred technical solution of the gate lifting equipment operation monitoring method based on data analysis, the evaluation of lifting stability based on the swing data and water flow impact data during the gate lifting process includes the following specific steps: S31, obtaining the swing data of the gate during the lifting and lowering process at the corresponding time, and obtaining the gate swing abnormality at the corresponding time based on the swing data, wherein the gate swing abnormality analysis formula at the corresponding time is: , where mt is the number of gate swings at the corresponding time, and fj is the average amplitude of the jth gate swing at the corresponding time; S32, based on the water flow impact data of the gate at the corresponding time and the gate swing abnormality analysis result at the corresponding time, perform the lifting stability evaluation at the corresponding time; S33, integrating the lifting stability at all moments in the lifting process over the time length and then dividing by the time length to obtain a lifting stability evaluation result in the corresponding lifting process.

[0008] It should be noted that, as a preferred technical solution for the gate lifting equipment operation monitoring method based on data analysis, the abnormal prediction of the gate lifting process in the next stage based on the lifting stability evaluation results and the water flow conditions in the next stage includes the following specific contents: S41, obtaining the water flow condition at the next stage, and evaluating the danger of the water flow at the next stage when the gate is raised or lowered based on the water flow condition at the next stage; S42, evaluating the danger of lifting in the next stage based on the danger of water flow in the next stage and the lifting stability evaluation results in the lifting process of the previous cycle; S43. Obtain the calculated results of the next stage lifting hazard assessment and the equipment health assessment during the lifting process, and obtain the abnormal prediction result of the gate lifting process in the next stage by weighted summing the inverse of the equipment health assessment result during the lifting process and the next stage lifting hazard assessment result.

[0009] It should be noted that, as a preferred technical solution for the gate lifting equipment operation monitoring method based on data analysis, the lifting process warning based on the abnormal prediction result of the gate lifting process in the next stage to remind the maintenance personnel to maintain the gate includes the following specific steps: The obtained abnormal prediction result of the gate lifting process in the next stage is compared with the set abnormal threshold of the gate lifting process. If the obtained abnormal prediction result of the gate lifting process in the next stage is greater than or equal to the set abnormal threshold of the gate lifting process, it means that the gate cannot be raised or lowered safely in the next stage, and the maintenance personnel are reminded to maintain the gate. If the obtained abnormal prediction result of the gate lifting process in the next stage is less than the set abnormal threshold of the gate lifting process, it means that the gate can be raised or lowered safely in the next stage.

[0010] The gate lifting equipment operation monitoring system based on data analysis is implemented based on the gate lifting equipment operation monitoring method based on data analysis, and specifically includes the following modules: Acquisition module: acquires the operation data of the lifting equipment during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process; Lifting equipment health assessment module: performs lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process; Lifting stability assessment module: Evaluate the lifting stability based on the swing data and water flow impact data during the gate lifting process; Lifting process abnormality prediction module: Based on the lifting stability evaluation results and the water flow conditions in the next stage, the abnormality of the gate lifting process in the next stage is predicted; The lifting process warning module issues a lifting process warning based on the abnormal prediction results of the gate lifting process in the next stage, reminding maintenance personnel to maintain the gate.

[0011] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned gate lifting equipment operation monitoring method based on data analysis by calling the computer program stored in the memory.

[0012] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the gate lifting equipment operation monitoring method based on data analysis as described above.

[0013] Compared with the prior art, the beneficial effects of this application are: This application firstly performs an evaluation on the health of the lifting equipment based on the lifting equipment operating data during the gate lifting process, and secondly evaluates the lifting stability based on the swing data and water flow impact data during the gate lifting process, and then predicts the abnormality of the gate lifting process in the next stage based on the lifting stability evaluation results and the water flow conditions in the next stage, and finally issues an early warning for the lifting process based on the abnormality prediction results of the gate lifting process in the next stage. This application comprehensively utilizes the lifting equipment operating data, swing data, water flow impact data and water flow prediction for the next stage during the gate lifting process to form a multi-step, multi-dimensional evaluation and early warning system, which can provide comprehensive protection for the safety and stability of the gate lifting process. By comprehensively utilizing the lifting equipment operating data, swing data, water flow impact data and water flow prediction for the next stage, a multi-dimensional analysis of the gate lifting process can be achieved, thereby improving the accuracy of the evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a schematic diagram of the overall process of the embodiment of the present application method; Figure 2 This is a schematic diagram of the process flow of step S2 of the method embodiment of the present application; Figure 3 This is a schematic diagram of the process flow of step S3 of the method embodiment of the present application; Figure 4 This is a schematic diagram of the process flow of step S4 of the method embodiment of the present application; Figure 5 It is a schematic diagram of the overall framework of the system embodiment of the present application. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0016] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

[0017] Example 1

[0018] In order to solve the technical problems raised in the background technology, the present application provides a preferred embodiment: Figure 1-Figure 4 As shown, the gate lifting equipment operation monitoring method based on data analysis includes the following specific steps: S1. Obtaining the operation data of the lifting equipment during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process; In this embodiment, the lifting equipment operation data during the gate lifting process includes equipment torque, equipment voltage, equipment current and equipment temperature during the gate lifting process, etc., which reflect the equipment operation data; the swing data during the gate lifting process includes gate speed, swing frequency and swing amplitude during the gate lifting process, etc., which reflect the gate data during the gate lifting process; the water flow impact data includes water velocity and water level data of the water flow impacting the gate, etc., which reflect the water flow impact data; in this embodiment, each parameter can be collected by a corresponding data sensor and stored in a corresponding storage module, for example, the equipment voltage is obtained by a voltage sensor; S2. Performing a health assessment of the lifting equipment operation based on the lifting equipment operation data during the gate lifting process; In this embodiment, the lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process includes the following specific steps: S21, obtaining the lifting equipment operation data during the gate lifting process at the corresponding time, and substituting it into the lifting equipment safety assessment formula at the corresponding time to perform the lifting equipment safety assessment at the corresponding time, wherein the lifting equipment safety assessment formula at the corresponding time is: , where n is the type of lifting equipment operation data, ci is the impact coefficient of the i-th lifting equipment operation data on safety, git is the value of the i-th lifting equipment operation data at time t, and gim is the median value of the safety range of the i-th lifting equipment operation data; S22, obtaining the relative height data of the gate and the moment data of the lifting device at the corresponding time, and obtaining the safety assessment result of the lifting device at the corresponding time, analyzing the difficulty of maintaining equipment safety based on the relative height data of the gate and the weight and lifting resistance of the gate at the corresponding time, and performing equipment health assessment at the corresponding time based on the safety assessment result of the lifting device and the difficulty of maintaining equipment safety. It should be noted that the lifting resistance here includes water resistance and friction resistance, and the equipment health assessment formula at the corresponding time is: , where Mz is the weight of the gate, ft is the resistance of the gate lifting at time t, Fm is the standard value of the lifting force, St is the distance between the gate lifting height and the lifting equipment, and Sm is the median value of the gate lifting height. is the resistance ratio weight, The height ratio weight is the weight of the gate. Since the resistance encountered by the gate when it rises at different heights and the torque output by the output shaft of the lifting equipment are different, the difficulty of lifting at different heights is also different. Therefore, it is necessary to remove the influence of these parameters that have a negative impact on the operation of the lifting equipment to obtain the equipment health assessment result at the corresponding moment. S23, obtaining the equipment health assessment result at each moment in the lifting process, integrating the time length and then dividing it by the lifting time to obtain the equipment health assessment result in the lifting process; S3, evaluate the lifting stability based on the swing data and water flow impact data during the gate lifting process; In this embodiment, the evaluation of the lifting stability based on the swing data and water flow impact data during the gate lifting process includes the following specific steps: S31, obtaining the swing data of the gate during the lifting and lowering process at the corresponding time, and obtaining the gate swing abnormality at the corresponding time based on the swing data, wherein the gate swing abnormality analysis formula at the corresponding time is: , where mt is the number of gate swings at the corresponding time, and fj is the average amplitude of the jth gate swing at the corresponding time; S32, based on the water flow impact data of the gate at the corresponding time and the gate swing abnormality analysis result at the corresponding time, the lifting stability evaluation at the corresponding time is performed, and the lifting stability evaluation formula at the corresponding time is: , where vt is the water velocity at the corresponding moment, Dt is the gate water depth at the corresponding moment, vm is the water velocity safety value corresponding to the gate, and Dm is the water level safety value at the gate position; S33, integrating the lifting stability at all moments in the lifting process over the time length and then dividing by the time length to obtain a lifting stability evaluation result in the corresponding lifting process; S4, based on the lifting stability assessment results and the water flow conditions in the next stage, the abnormal prediction of the gate lifting process in the next stage is performed; In this embodiment, the abnormal prediction of the gate lifting process in the next stage based on the lifting stability evaluation result and the water flow condition in the next stage includes the following specific contents: S41, obtaining the water flow condition at the next stage, and evaluating the danger of the water flow at the next stage when the gate is raised or lowered based on the water flow condition at the next stage, wherein the calculation formula for the danger of the water flow at the next stage is: ,in, is the duration of the lifting process in the next stage, vtc is the water velocity at time tc in the next stage, and Dtc is the water depth of the gate at time tc in the next stage; It should be noted here that the water flow conditions in the next stage are estimated by the upstream water level flow and weather conditions. The estimation method can be to build an estimation model through historical data (such as deep learning and other machine learning models). The estimation method is, for example: obtain the water level flow and weather conditions of the corresponding upstream position in history, and at the same time obtain the water flow conditions of the corresponding position in history, and construct a deep learning model with the water level flow and weather conditions of the corresponding upstream position as input and the water flow conditions of the corresponding position as output. The historical data is divided into training set, validation set and test set in chronological order, usually with a ratio of 60% training, 20% validation and 20% testing. Select appropriate model structure and hyperparameters (such as the number of layers, number of neurons, activation function, etc.), and define appropriate loss functions, such as mean square error (MSE) or root mean square error (RMSE). Select an optimizer, such as Adam or SGD, set the learning rate and batch size, train the model, monitor the training loss and validation loss, use the early stopping strategy to prevent overfitting, use the validation set to evaluate the model performance, calculate MSE, MAE, R-squared and other indicators, use the validation set results to perform grid search or random search, optimize the model hyperparameters, adjust the model structure according to the validation results, such as increasing the number of layers, adjusting the activation function, etc., to improve the estimation accuracy, use an independent test set to evaluate the generalization performance of the model, ensure that the model performs well on unseen data, make estimates on real data, and verify the effectiveness of the model in practical applications; S42, based on the danger of the water flow in the next stage and the lifting stability evaluation results in the previous cycle lifting process, the next stage lifting danger evaluation formula is: , where Mz is the lifting stability evaluation result in the lifting process of the previous cycle, and exp() is the power of the natural constant e; S43, obtaining the calculated next-stage lifting risk assessment result and the equipment health assessment result during the lifting process, and performing weighted summation of the inverse of the equipment health assessment result during the lifting process and the next-stage lifting risk assessment result to obtain the next-stage gate lifting process abnormality prediction result; S5. Based on the abnormal prediction results of the gate lifting process in the next stage, an early warning of the lifting process is issued to remind maintenance personnel to maintain the gate; In this embodiment, based on the abnormal prediction result of the gate lifting process in the next stage, the lifting process warning is performed to remind the maintenance personnel to maintain the gate, which includes the following specific steps: The obtained abnormal prediction result of the gate lifting process in the next stage is compared with the set abnormal threshold of the gate lifting process. If the obtained abnormal prediction result of the gate lifting process in the next stage is greater than or equal to the set abnormal threshold of the gate lifting process, it means that the gate cannot be lifted safely in the next stage, and the maintenance personnel are reminded to maintain the gate. If the obtained abnormal prediction result of the gate lifting process in the next stage is less than the set abnormal threshold of the gate lifting process, it means that the gate can be lifted safely in the next stage. It should be emphasized here that the value of the setting parameters in this embodiment is: the preferred value-taking method is: obtaining the historical operation data of the lifting equipment during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process, to obtain the judgment result of whether the lifting equipment in the next cycle can be safely lifted, and at the same time substitute the historical data into each step of this embodiment to calculate the abnormal prediction result of the gate lifting process in the next stage, and then import the calculation results and the judgment results into the fitting software to fit the data, and output the value of the setting parameter that meets the maximum judgment accuracy; The advantages of this embodiment over the prior art are as follows: first, an evaluation of the health of the operation of the lifting equipment is performed based on the operating data of the lifting equipment during the gate lifting process; secondly, the lifting stability is evaluated based on the swing data and water flow impact data during the gate lifting process; then, based on the lifting stability evaluation result and the water flow conditions in the next stage, an abnormal prediction of the gate lifting process in the next stage is performed; finally, based on the abnormal prediction result of the gate lifting process in the next stage, an early warning of the lifting process is issued. This application comprehensively utilizes the lifting equipment operating data, swing data, water flow impact data and water flow prediction for the next stage during the gate lifting process to form a multi-step, multi-dimensional evaluation and early warning system, which can provide comprehensive protection for the safety and stability of the gate lifting process. By comprehensively utilizing the lifting equipment operating data, swing data, water flow impact data and water flow prediction for the next stage, a multi-dimensional analysis of the gate lifting process can be achieved, thereby improving the accuracy of the evaluation.

[0019] Example 2

[0020] like Figure 5 As shown, the gate lifting equipment operation monitoring system based on data analysis is implemented based on the gate lifting equipment operation monitoring method based on data analysis, and specifically includes: an acquisition module: acquiring the lifting equipment operation data during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process; Lifting equipment health assessment module: performs lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process; Lifting stability assessment module: Evaluate the lifting stability based on the swing data and water flow impact data during the gate lifting process; Lifting process abnormality prediction module: Based on the lifting stability evaluation results and the water flow conditions in the next stage, the abnormality of the gate lifting process in the next stage is predicted; The lifting process warning module performs lifting process warning based on the abnormal prediction results of the gate lifting process in the next stage, reminding maintenance personnel to maintain the gate. The specific steps of the above modules in this embodiment are specifically described in the above method embodiment and will not be repeated in this embodiment.

[0021] Example 3

[0022] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned gate lifting equipment operation monitoring method based on data analysis by calling the computer program stored in the memory.

[0023] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement the gate lifting equipment operation monitoring method based on data analysis provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0024] Example 4

[0025] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device executes the above-mentioned gate lifting equipment operation monitoring method based on data analysis.

[0026] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0027] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A gate lifting equipment operation monitoring method based on data analysis, characterized in that: It includes the following specific steps: S1. Obtaining the operation data of the lifting equipment during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process; S2. Performing a health assessment of the lifting equipment operation based on the lifting equipment operation data during the gate lifting process; S3, evaluate the lifting stability based on the swing data and water flow impact data during the gate lifting process; S4, based on the lifting stability assessment results and the water flow conditions in the next stage, the abnormal prediction of the gate lifting process in the next stage is performed; S5. Based on the abnormal prediction results of the gate lifting process in the next stage, an early warning of the lifting process is issued to remind maintenance personnel to maintain the gate.

2. The gate lifting equipment operation monitoring method based on data analysis according to claim 1 is characterized in that: The lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process includes the following specific steps: Obtain the lifting equipment operation data during the gate lifting process at the corresponding time, and substitute it into the lifting equipment safety assessment formula at the corresponding time to conduct the lifting equipment safety assessment at the corresponding time; Obtain the gate's relative height data and the moment data on the lifting device at the corresponding moment, and simultaneously obtain the lifting device safety assessment result at the corresponding moment, analyze the difficulty of maintaining the equipment safely based on the gate's relative height data and the gate's weight and lifting resistance at the corresponding moment, and perform the equipment health assessment at the corresponding moment based on the lifting device safety assessment result and the difficulty of maintaining the equipment safely; The equipment health assessment results at each moment in the lifting process are obtained, the time length is integrated and then divided by the lifting time to obtain the equipment health assessment results in the lifting process.

3. The gate lifting equipment operation monitoring method based on data analysis according to claim 2 is characterized in that: The evaluation of the lifting stability based on the swing data and water flow impact data during the gate lifting process includes the following specific steps: Obtain the swing data of the gate during the lifting and lowering process at the corresponding moment, and obtain the gate swing abnormality at the corresponding moment based on the swing data; Based on the water flow impact data of the gate at the corresponding time and the gate swing abnormality analysis results at the corresponding time, the lifting stability evaluation at the corresponding time is performed; The lifting stability at all moments in the lifting process is integrated over the time length and then divided by the time length to obtain the lifting stability evaluation result in the corresponding lifting process.

4. The gate lifting equipment operation monitoring method based on data analysis according to claim 3 is characterized in that: Based on the results of the lifting stability assessment and the water flow conditions in the next stage, the abnormal prediction of the gate lifting process in the next stage includes the following specific contents: Obtain the water flow conditions at the next stage, and based on the water flow conditions at the next stage, assess the danger of the water flow at the next stage when the gate is raised or lowered; The next stage of lifting danger is evaluated based on the danger of the water flow in the next stage and the lifting stability evaluation results in the previous cycle of lifting; The calculated results of the next stage lifting hazard assessment and the equipment health assessment results during the lifting process are obtained. The inverse of the equipment health assessment result during the lifting process and the weighted sum of the next stage lifting hazard assessment results are used to obtain the abnormal prediction result of the gate lifting process in the next stage.

5. The gate lifting equipment operation monitoring method based on data analysis according to claim 4 is characterized in that: The method of providing an early warning of the gate lifting process based on the abnormal prediction result of the gate lifting process in the next stage to remind the maintenance personnel to maintain the gate includes the following specific steps: The obtained abnormal prediction result of the gate lifting process in the next stage is compared with the set abnormal threshold of the gate lifting process. If the obtained abnormal prediction result of the gate lifting process in the next stage is greater than or equal to the set abnormal threshold of the gate lifting process, it means that the gate cannot be raised or lowered safely in the next stage, and the maintenance personnel are reminded to maintain the gate. If the obtained abnormal prediction result of the gate lifting process in the next stage is less than the set abnormal threshold of the gate lifting process, it means that the gate can be raised or lowered safely in the next stage.

6. The gate lifting equipment operation monitoring method based on data analysis according to claim 5 is characterized in that: The lifting equipment operation data during the gate lifting process include the equipment torque, equipment voltage, equipment current and equipment temperature during the gate lifting process, which reflect the equipment operation data; the swing data during the gate lifting process include the speed, swing frequency and swing amplitude during the gate lifting process, which reflect the gate data during the gate lifting process; the water flow impact data include the water velocity and water level data of the water flow impacting the gate, which reflect the water flow impact data.

7. A gate lifting equipment operation monitoring system based on data analysis, which is implemented based on the gate lifting equipment operation monitoring method based on data analysis as claimed in any one of claims 1 to 6, characterized in that: It specifically includes the following modules: Acquisition module: acquires the operation data of the lifting equipment during the gate lifting process, as well as the swing data and water flow impact data during the gate lifting process; Lifting equipment health assessment module: performs lifting equipment operation health assessment based on the lifting equipment operation data during the gate lifting process; Lifting stability assessment module: Evaluate the lifting stability based on the swing data and water flow impact data during the gate lifting process; Lifting process abnormality prediction module: Based on the lifting stability evaluation results and the water flow conditions in the next stage, the abnormality of the gate lifting process in the next stage is predicted; The lifting process warning module issues a lifting process warning based on the abnormal prediction results of the gate lifting process in the next stage, reminding maintenance personnel to maintain the gate.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the gate lifting equipment operation monitoring method based on data analysis as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes the gate lifting equipment operation monitoring method based on data analysis as described in any one of claims 1-6.

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