Telescopic oil cylinder state monitoring system and method based on multi-source data fusion

Abstract

The invention discloses a telescopic oil cylinder state monitoring system and method based on multi-source data fusion, and relates to the technical field of equipment monitoring. The method comprises the following steps: constructing a simulation model of the telescopic oil cylinder, obtaining a first-class operation coefficient in combination with operation data, adjusting the first-class operation coefficient to obtain a second-class change coefficient, constructing an operation evaluation model according to different first-class operation coefficients and the second-class change coefficient thereof, and obtaining a first-class actual operation coefficient of the telescopic oil cylinder. Using the operation evaluation model to obtain a second-class evaluation change coefficient, setting a change coefficient threshold to judge whether operation abnormity exists, and generating operation abnormity information for feedback; the problem that a conventional state monitoring method neglects the influence of movement of a telescopic structure is solved, and whether the telescopic oil cylinder is abnormal or not can be accurately judged and fed back in time.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment monitoring, and in particular to a telescopic oil cylinder state monitoring system and method based on multi-source data fusion. Background Art

[0002] Telescopic cylinders, as key actuators in hydraulic systems, are widely used in engineering and mining machinery. Monitoring their condition is crucial for preventing failures and improving equipment efficiency and safety. Existing technical solutions often only monitor various internal state parameters of the telescopic cylinder in isolation, and then determine whether a fault exists through simple numerical comparisons.

[0003] This monitoring method ignores the influence of the movement of the telescopic structure on the state parameters of the telescopic cylinder. When the telescopic structure moves, its state parameters will often change accordingly. Therefore, the previous isolated and simple monitoring method is prone to misjudgment, resulting in a lack of accuracy in the monitoring results. In response to the shortcomings of the existing technology, the present invention provides a telescopic cylinder state monitoring system and method based on multi-source data fusion. Summary of the Invention

[0004] The object of the present invention is to provide a telescopic cylinder status monitoring system and method based on multi-source data fusion.

[0005] The purpose of the present invention can be achieved through the following technical solution: A telescopic cylinder status monitoring system based on multi-source data fusion, comprising the following modules:

[0006] The first construction module is used to obtain basic information of the telescopic cylinder and construct a corresponding physical model, obtain operating data of the telescopic cylinder, and construct a corresponding simulation model;

[0007] A data analysis module is used to obtain a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model, and adjust the first-class operating coefficient to obtain a corresponding second-class variation coefficient;

[0008] The second construction module is used to construct an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients;

[0009] A data evaluation module is used to obtain the first-class actual operation coefficient of the telescopic cylinder and obtain the corresponding second-class evaluation variation coefficient using the operation evaluation model;

[0010] The abnormality judgment module is used to set the variation coefficient threshold to determine whether there is an operation abnormality and generate corresponding operation abnormality information for feedback.

[0011] Furthermore, the process of obtaining basic information of the telescopic cylinder and building the corresponding physical model includes:

[0012] The basic information refers to the specification parameters of each component structure of the telescopic cylinder, which includes a fixed structure, a telescopic structure, a connecting structure, and a driving structure. The specification parameters include size, material, and weight. A three-dimensional modeling tool is used to construct a physical model of the telescopic cylinder based on the specification parameters of each component structure.

[0013] Furthermore, the process of obtaining the operating data of the telescopic cylinder and building the corresponding simulation model includes:

[0014] Setting a collection unit, including a first-class collection unit and a second-class collection unit, and obtaining the first-class operation data and the second-class operation data of the telescopic cylinder through the first-class collection unit and the second-class collection unit respectively;

[0015] The operating data includes first-class operating data and second-class operating data. The first-class operating data refers to the position, speed, acceleration, driving force and torque of the telescopic structure, and the second-class operating data refers to the temperature, amplitude and hydraulic pressure of the telescopic cylinder.

[0016] Using simulation software to obtain a digital twin model based on the physical model, a type of operating data is uploaded to the digital twin model for synchronization, and the values of simulation parameters are continuously adjusted during the simulation process. The simulation parameters refer to the inertia force, friction coefficient, hydraulic oil flow rate, and hydraulic oil viscosity in the telescopic cylinder;

[0017] Obtain the temperature, amplitude, and hydraulic pressure in the digital twin model under different numerical simulation parameters. When the temperature, amplitude, and hydraulic pressure are the same as the second type of operating data at the corresponding moment of the synchronized first type of operating data, the digital twin model at this time is used as the simulation model, and the simulation parameters with the corresponding numerical values are used as the digital twin parameters of the simulation model.

[0018] Furthermore, in the simulation model, the operation data is combined to obtain a first-class operation coefficient of the telescopic cylinder, and the process of adjusting the first-class operation coefficient to obtain the corresponding second-class variation coefficient includes:

[0019] Obtaining the cavity volume of the telescopic oil cylinder according to the position in a type of operating data in the simulation model, wherein the cavity volume refers to the volume of the cavity inside the telescopic oil cylinder when the telescopic structure moves;

[0020] According to the speed y in the next type of running data at the same time a , acceleration y b , driving force c , torque y d , cavity volume v k And the inertia force s in the digital twin parameters of the simulation model c , hydraulic oil flow s k Obtain a type of operating coefficient P of the telescopic cylinder at the corresponding moment;

[0021]

[0022] ω1, ω2, ω3, ω4, and ω5 are the preset weight values, y a0 、y b0 、y c0 、y d0 、v k0 are the maximum values allowed for speed, acceleration, driving force, torque, and cavity volume respectively;

[0023] In the simulation model, the values of various parameters in a type of operating data are continuously adjusted, and a type of operating coefficient corresponding to different values of the type of operating data, as well as the temperature, amplitude, and hydraulic pressure under different type of operating coefficients are obtained;

[0024] The difference between any two types of operating coefficients is taken as the difference between the two operating coefficients, and its change trend is obtained, including increase, decrease, and no change;

[0025] The difference between the temperature, amplitude, and hydraulic pressure corresponding to any two first-class operating coefficients is taken as the temperature difference, amplitude difference, and hydraulic pressure difference between the two, and their change trends are obtained respectively. The second-class change coefficient includes the temperature difference, amplitude difference, and hydraulic pressure difference.

[0026] Furthermore, the process of constructing an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients includes:

[0027] An operation evaluation set is generated based on the operating coefficient differences and change trends between different first-class operating coefficients and the temperature differences, amplitude differences, hydraulic pressure differences and various change trends in the corresponding second-class change coefficients, and is divided into a training set and a test set;

[0028] Construct a convolutional neural network, use the different operating coefficient differences and change trends in the training set as the input data of the convolutional neural network, and use the corresponding temperature differences, amplitude differences, hydraulic pressure differences and various change trends in the training set as the output data of the convolutional neural network;

[0029] The convolutional neural network is trained to obtain an initial convolutional neural network, and the initial convolutional neural network is model verified using the test set, and the initial convolutional neural network with a preset test error threshold is output as the running evaluation model.

[0030] Furthermore, the process of obtaining the first-class actual operation coefficient of the telescopic cylinder and obtaining the corresponding second-class evaluation variation coefficient using the operation evaluation model includes:

[0031] In actual application scenarios, the real-time actual operation coefficient of the telescopic cylinder is continuously obtained based on the current operation data of the telescopic cylinder and the digital twin parameters of the corresponding simulation model;

[0032] The difference between the current first-class actual operating coefficient of the telescopic cylinder and the first-class actual operating coefficient at the previous moment is taken as the actual operating coefficient difference, and its change trend is obtained. The actual operating coefficient difference and its change trend are input into the operation evaluation model to obtain the second-class evaluation change coefficient and its various change trends.

[0033] Furthermore, the process of setting a variation coefficient threshold to determine whether an operation abnormality exists and generating corresponding operation abnormality information for feedback includes:

[0034] The difference in temperature, amplitude, and hydraulic pressure between the current first-class actual operating coefficient of the telescopic cylinder and the first-class actual operating coefficient at the previous moment is taken as the second-class actual change coefficient, and their change trends are obtained respectively;

[0035] Compare the changing trends of the second-class actual variation coefficients at the same time with the changing trends of the second-class evaluation variation coefficients to obtain the second-class operating data with abnormal trends, including abnormal temperature trends, abnormal amplitude trends, and abnormal hydraulic trends;

[0036] Set a variation coefficient threshold, and compare the difference between the actual variation coefficient of each category II and its estimated variation coefficient of the category II at the same time with the corresponding variation coefficient threshold to obtain category II operating data with abnormal values, including abnormal temperature values, abnormal amplitude values, and abnormal hydraulic values;

[0037] The operation anomaly includes trend anomaly and numerical anomaly. According to the two types of operation data with trend anomaly and numerical anomaly, corresponding operation anomaly information is generated and fed back to relevant personnel, including trend anomaly information and numerical anomaly information.

[0038] A telescopic cylinder condition monitoring method based on multi-source data fusion includes the following steps:

[0039] Step S1: Obtain basic information of the telescopic cylinder and construct a corresponding physical model, obtain operating data of the telescopic cylinder and construct a corresponding simulation model;

[0040] Step S2: obtaining a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model, and adjusting the first-class operating coefficient to obtain a corresponding second-class variation coefficient;

[0041] Step S3: constructing an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients;

[0042] Step S4: obtaining the first-class actual operation coefficient of the telescopic cylinder, and using the operation evaluation model to obtain the corresponding second-class evaluation variation coefficient;

[0043] Step S5: Setting a variation coefficient threshold to determine whether there is an operation abnormality, and generating corresponding operation abnormality information for feedback.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] By constructing a physical model and a simulation model of the telescopic cylinder, the present invention can obtain changes in various state parameters under different working conditions. Based on this, an operation evaluation model of the telescopic cylinder can be constructed, which is conducive to obtaining changes in the state parameters of the telescopic cylinder during movement. This solves the problem of ignoring the influence of the telescopic structure movement in previous state monitoring. It can timely judge whether the change in state parameters caused by the telescopic structure movement exceeds the normal range and whether an abnormal change trend occurs. It can accurately judge whether there is an abnormality in the telescopic cylinder and provide timely feedback. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 Schematic diagram of the present invention. DETAILED DESCRIPTION

[0047] like Figure 1 As shown in the figure, a telescopic cylinder condition monitoring system based on multi-source data fusion includes the following modules:

[0048] The first construction module is used to obtain basic information of the telescopic cylinder and construct a corresponding physical model, obtain operating data of the telescopic cylinder, and construct a corresponding simulation model;

[0049] A data analysis module is used to obtain a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model, and adjust the first-class operating coefficient to obtain a corresponding second-class variation coefficient;

[0050] The second construction module is used to construct an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients;

[0051] A data evaluation module is used to obtain the first-class actual operation coefficient of the telescopic cylinder and obtain the corresponding second-class evaluation variation coefficient using the operation evaluation model;

[0052] The abnormality judgment module is used to set the variation coefficient threshold to determine whether there is an operation abnormality and generate corresponding operation abnormality information for feedback.

[0053] It should be further explained that, in the specific implementation process, the process of obtaining the basic information of the telescopic cylinder and building the corresponding physical model includes:

[0054] The basic information refers to the specifications of each component structure of the telescopic cylinder, including various relevant data required for building a physical model. The components include fixed structure, telescopic structure, connection structure, drive structure, etc. The specifications include size, material, weight, etc.

[0055] A three-dimensional modeling tool is used to construct a physical model of the telescopic cylinder based on the specification parameters of each component structure. The physical model constructed at this time is a physical model of the telescopic cylinder under ideal conditions, that is, it does not consider the impact of damage and aging of the telescopic cylinder in actual application scenarios.

[0056] It should be further explained that, in the specific implementation process, the process of obtaining the operating data of the telescopic cylinder and building the corresponding simulation model includes:

[0057] In actual application scenarios, different collection units are set for the telescopic cylinder, including a first-class collection unit and a second-class collection unit. The first-class collection unit collects the first-class operation data of the telescopic cylinder in real time, and the second-class collection unit collects the second-class operation data of the telescopic cylinder in real time;

[0058] The first type of operating data refers to the position, speed, acceleration, driving force, torque, etc. of the telescopic structure of the telescopic oil cylinder, and the second type of operating data refers to the temperature, amplitude, hydraulic pressure, etc. of the telescopic oil cylinder. The operating data includes the first type of operating data and the second type of operating data;

[0059] Using simulation software to simulate the working process of the telescopic cylinder based on the physical model to obtain the corresponding digital twin model, the obtained operating data is uploaded to the digital twin model for synchronization, and the values of different simulation parameters are continuously adjusted during the simulation process;

[0060] The simulation parameters refer to the inertia force, friction coefficient, hydraulic oil flow, hydraulic oil viscosity, etc. of the telescopic cylinder in the actual application scenario, and the temperature, amplitude, hydraulic pressure, etc. in the digital twin model under different numerical simulation parameters are obtained;

[0061] When the acquired temperature, amplitude, and hydraulic pressure are the same as the second type of operating data at the corresponding moment of the synchronized first type of operating data, the digital twin model at this time is used as the simulation model of the telescopic cylinder, and the simulation parameters of the corresponding values are used as the digital twin parameters of the simulation model.

[0062] It should be further explained that, in a specific implementation process, the process of obtaining a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model and adjusting the first-class operating coefficient to obtain the corresponding second-class variation coefficient includes:

[0063] Obtaining, in a simulation model, a cavity volume of the telescopic cylinder based on a position in a type of operating data, wherein the cavity volume refers to the volume of the cavity inside the telescopic cylinder when the telescopic structure moves, and the cavity volume includes the volume occupied by the hydraulic oil;

[0064] The speed, acceleration, driving force, torque and cavity volume of a type of operating data at the same time are respectively recorded as y a 、y b 、y c 、y d and v k The inertia force and hydraulic oil flow in the digital twin parameters of the simulation model are respectively denoted as s c 、s k , obtain a type of operating coefficient P of the telescopic cylinder at the corresponding moment;

[0065]

[0066] Among them, ω1, ω2, ω3, ω4, and ω5 are preset weight values, y a0 、y b0 、y c0 、y d0 、v k0 are the maximum values allowed for speed, acceleration, driving force, torque, and cavity volume respectively;

[0067] In the simulation model, the values of various parameters in a type of operating data are continuously adjusted, and a type of operating coefficient corresponding to a type of operating data with different values is obtained, and the temperature, amplitude, hydraulic pressure, etc. under different types of operating coefficients are obtained in the simulation model;

[0068] Number the adjusted first-class operating coefficients in chronological order, obtain the difference between any two first-class operating coefficients, record it as the operating coefficient difference, and compare any two first-class operating coefficients in chronological order to obtain their change trends, including increase, decrease, and no change;

[0069] Obtain the difference between the temperature, amplitude, and hydraulic pressure corresponding to any two first-class operating coefficients, record them as temperature difference, amplitude difference, and hydraulic pressure difference, and obtain their change trends respectively. The second-class change coefficients include temperature difference, amplitude difference, and hydraulic pressure difference.

[0070] It should be further explained that, in the specific implementation process, the process of constructing the telescopic cylinder operation evaluation model according to different first-class operation coefficients and their corresponding second-class variation coefficients includes:

[0071] An operation evaluation set is generated based on the operating coefficient differences and change trends between different first-class operating coefficients, and the temperature differences, amplitude differences, hydraulic pressure differences, and various change trends in the corresponding second-class change coefficients, and is divided into a training set and a test set.

[0072] Construct a convolutional neural network, use the different operating coefficient differences and change trends in the training set as the input data of the convolutional neural network, and use the corresponding temperature differences, amplitude differences, hydraulic pressure differences and various change trends in the training set as the output data of the convolutional neural network;

[0073] The convolutional neural network is trained to obtain an initial convolutional neural network, and the initial convolutional neural network is model verified using the test set, and the initial convolutional neural network with a preset test error threshold is output as the corresponding operation evaluation model.

[0074] It should be further explained that, in the specific implementation process, the process of obtaining the first-class actual operation coefficient of the telescopic cylinder and obtaining the corresponding second-class evaluation variation coefficient using the operation evaluation model includes:

[0075] In actual application scenarios, the real-time actual operation coefficient of the telescopic cylinder is continuously obtained based on the current operation data of the telescopic cylinder and the digital twin parameters of the corresponding simulation model;

[0076] The difference between the current actual operating coefficient of the telescopic cylinder and the actual operating coefficient of the previous moment is used as the actual operating coefficient difference, and its change trend is obtained. The actual operating coefficient difference and its change trend are input into the operation evaluation model;

[0077] The operation evaluation model is used to obtain two types of evaluation variation coefficients and their respective change trends corresponding to the actual operation coefficient difference. The two types of evaluation variation coefficients include evaluation temperature difference, evaluation amplitude difference, and evaluation hydraulic pressure difference.

[0078] It should be further explained that, in a specific implementation process, the process of setting a variation coefficient threshold to determine whether an operation anomaly exists and generating corresponding operation anomaly information for feedback includes:

[0079] The difference between the temperature, amplitude, and hydraulic pressure corresponding to the current first-class actual operating coefficient of the telescopic cylinder and the first-class actual operating coefficient at the previous moment is used as the second-class actual change coefficient, including the actual temperature difference, the actual amplitude difference, and the actual hydraulic pressure difference, and their change trends are obtained respectively;

[0080] Compare the changing trends of the actual variation coefficients of each category II at the same moment with the changing trends of its estimated variation coefficients of the category II. If they are consistent, no other operations will be performed on them.

[0081] If there is inconsistency, the second-category operating data corresponding to the inconsistent second-category actual change coefficients will be recorded as trend anomalies, including temperature trend anomalies, amplitude trend anomalies, and hydraulic trend anomalies. Corresponding trend anomaly information will be generated and fed back to relevant personnel.

[0082] Set corresponding variation coefficient thresholds for each type of second-class operating data, including temperature variation threshold, amplitude variation threshold, and hydraulic pressure variation threshold. Compare the actual variation coefficients of each type of second-class operating data at the same moment with their second-class evaluation variation coefficients. If the difference between the two is less than or equal to the corresponding variation coefficient threshold, no other operations are performed on it.

[0083] If the difference between the two is greater than the corresponding variation coefficient threshold, the second-category operating data corresponding to the second-category actual variation coefficient that is greater than the threshold will be recorded as a numerical abnormality, including temperature numerical abnormality, amplitude numerical abnormality, and hydraulic numerical abnormality. The corresponding numerical abnormality information will be generated and fed back to the relevant personnel.

[0084] An embodiment of the present invention also includes a telescopic cylinder state monitoring method based on multi-source data fusion, comprising the following steps:

[0085] Step S1: Obtain basic information of the telescopic cylinder and construct a corresponding physical model, obtain operating data of the telescopic cylinder and construct a corresponding simulation model;

[0086] Step S2: obtaining a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model, and adjusting the first-class operating coefficient to obtain a corresponding second-class variation coefficient;

[0087] Step S3: constructing an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients;

[0088] Step S4: obtaining the first-class actual operation coefficient of the telescopic cylinder, and using the operation evaluation model to obtain the corresponding second-class evaluation variation coefficient;

[0089] Step S5: Setting a variation coefficient threshold to determine whether there is an operation abnormality, and generating corresponding operation abnormality information for feedback.

[0090] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A telescopic cylinder status monitoring system based on multi-source data fusion, characterized in that: Includes the following modules: The first construction module is used to obtain basic information of the telescopic cylinder and construct a corresponding physical model, obtain operating data of the telescopic cylinder, and construct a corresponding simulation model; A data analysis module is used to obtain a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model, and adjust the first-class operating coefficient to obtain a corresponding second-class variation coefficient; The second construction module is used to construct an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients; A data evaluation module is used to obtain the first-class actual operation coefficient of the telescopic cylinder and obtain the corresponding second-class evaluation variation coefficient using the operation evaluation model; The abnormality judgment module is used to set the variation coefficient threshold to determine whether there is an operation abnormality and generate corresponding operation abnormality information for feedback.

2. The telescopic cylinder state monitoring system based on multi-source data fusion according to claim 1 is characterized in that: The process of obtaining basic information and building a physical model includes: The basic information refers to the specification parameters of each component structure of the telescopic cylinder, which includes a fixed structure, a telescopic structure, a connecting structure, and a driving structure. The specification parameters include size, material, and weight. A three-dimensional modeling tool is used to construct a physical model of the telescopic cylinder based on the specification parameters of each component structure.

3. The telescopic cylinder state monitoring system based on multi-source data fusion according to claim 2 is characterized in that: The process of obtaining operational data and building a simulation model includes: Setting a collection unit, including a first-class collection unit and a second-class collection unit, and obtaining the first-class operation data and the second-class operation data of the telescopic cylinder through the first-class collection unit and the second-class collection unit respectively; The operating data includes first-class operating data and second-class operating data. The first-class operating data refers to the position, speed, acceleration, driving force and torque of the telescopic structure, and the second-class operating data refers to the temperature, amplitude and hydraulic pressure of the telescopic cylinder. Using simulation software to obtain a digital twin model based on the physical model, a type of operating data is uploaded to the digital twin model for synchronization, and the values of simulation parameters are continuously adjusted during the simulation process. The simulation parameters refer to the inertia force, friction coefficient, hydraulic oil flow rate, and hydraulic oil viscosity in the telescopic cylinder; Obtain the temperature, amplitude, and hydraulic pressure in the digital twin model under different numerical simulation parameters. When the temperature, amplitude, and hydraulic pressure are the same as the second type of operating data at the corresponding moment of the synchronized first type of operating data, the digital twin model at this time is used as the simulation model, and the simulation parameters with the corresponding numerical values are used as the digital twin parameters of the simulation model.

4. The telescopic cylinder state monitoring system based on multi-source data fusion according to claim 3 is characterized in that: The process of obtaining the first-class operating coefficient and its second-class variation coefficient includes: Obtaining the cavity volume of the telescopic oil cylinder according to the position in a type of operating data in the simulation model, wherein the cavity volume refers to the volume of the cavity inside the telescopic oil cylinder when the telescopic structure moves; According to the speed y in the next type of running data at the same time a , acceleration y b , driving force c , torque y d , cavity volume v k And the inertia force s in the digital twin parameters of the simulation model c , hydraulic oil flow s k Obtain a type of operating coefficient P of the telescopic cylinder at the corresponding moment; ω1, ω2, ω3, ω4, and ω5 are the preset weight values, y a0 、y b0 、y c0 、y d0 、v k0 are the maximum values allowed for speed, acceleration, driving force, torque, and cavity volume respectively; In the simulation model, the values of various parameters in a type of operating data are continuously adjusted, and a type of operating coefficient corresponding to different values of the type of operating data, as well as the temperature, amplitude, and hydraulic pressure under different type of operating coefficients are obtained; The difference between any two types of operating coefficients is taken as the difference between the two operating coefficients, and its change trend is obtained, including increase, decrease, and no change; The difference between the temperature, amplitude, and hydraulic pressure corresponding to any two first-class operating coefficients is taken as the temperature difference, amplitude difference, and hydraulic pressure difference between the two, and their change trends are obtained respectively. The second-class change coefficient includes the temperature difference, amplitude difference, and hydraulic pressure difference.

5. The telescopic cylinder state monitoring system based on multi-source data fusion according to claim 4 is characterized in that: The process of building an operational assessment model for a telescopic cylinder includes: An operation evaluation set is generated based on the operating coefficient differences and change trends between different first-class operating coefficients and the temperature differences, amplitude differences, hydraulic pressure differences and various change trends in the corresponding second-class change coefficients, and is divided into a training set and a test set; Construct a convolutional neural network, use the different operating coefficient differences and change trends in the training set as the input data of the convolutional neural network, and use the corresponding temperature differences, amplitude differences, hydraulic pressure differences and various change trends in the training set as the output data of the convolutional neural network; The convolutional neural network is trained to obtain an initial convolutional neural network, and the initial convolutional neural network is model verified using the test set, and the initial convolutional neural network with a preset test error threshold is output as the running evaluation model.

6. The telescopic cylinder state monitoring system based on multi-source data fusion according to claim 5 is characterized in that: The process of obtaining the first-class actual operation coefficient and its second-class evaluation variation coefficient includes: In actual application scenarios, the real-time actual operation coefficient of the telescopic cylinder is continuously obtained based on the current operation data of the telescopic cylinder and the digital twin parameters of the corresponding simulation model; The difference between the current first-class actual operating coefficient of the telescopic cylinder and the first-class actual operating coefficient at the previous moment is taken as the actual operating coefficient difference, and its change trend is obtained. The actual operating coefficient difference and its change trend are input into the operation evaluation model to obtain the second-class evaluation change coefficient and its various change trends.

7. The telescopic cylinder state monitoring system based on multi-source data fusion according to claim 6 is characterized in that: The process of determining whether an operation anomaly exists and generating operation anomaly information includes: The difference in temperature, amplitude, and hydraulic pressure between the current first-class actual operating coefficient of the telescopic cylinder and the first-class actual operating coefficient at the previous moment is taken as the second-class actual change coefficient, and their change trends are obtained respectively; Compare the changing trends of the second-class actual variation coefficients at the same time with the changing trends of the second-class evaluation variation coefficients to obtain the second-class operating data with abnormal trends, including abnormal temperature trends, abnormal amplitude trends, and abnormal hydraulic trends; Set a variation coefficient threshold, and compare the difference between the actual variation coefficient of each category II and its estimated variation coefficient of the category II at the same time with the corresponding variation coefficient threshold to obtain category II operating data with abnormal values, including abnormal temperature values, abnormal amplitude values, and abnormal hydraulic values; The operation anomaly includes trend anomaly and numerical anomaly. According to the two types of operation data with trend anomaly and numerical anomaly, corresponding operation anomaly information is generated and fed back to relevant personnel, including trend anomaly information and numerical anomaly information.

8. A telescopic cylinder state monitoring method based on multi-source data fusion, which is implemented based on the telescopic cylinder state monitoring system according to any one of claims 1 to 7, characterized in that: The method comprises: Step S1: Obtain basic information of the telescopic cylinder and construct a corresponding physical model, obtain operating data of the telescopic cylinder and construct a corresponding simulation model; Step S2: obtaining a first-class operating coefficient of the telescopic cylinder in combination with the operating data in the simulation model, and adjusting the first-class operating coefficient to obtain a corresponding second-class variation coefficient; Step S3: constructing an operation evaluation model of the telescopic cylinder according to different first-class operation coefficients and their corresponding second-class variation coefficients; Step S4: obtaining the first-class actual operation coefficient of the telescopic cylinder, and using the operation evaluation model to obtain the corresponding second-class evaluation variation coefficient; Step S5: Setting a variation coefficient threshold to determine whether there is an operation abnormality, and generating corresponding operation abnormality information for feedback.

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