Hydraulic cylinder remaining service life prediction method and hydraulic cylinder health state monitoring system

Abstract

The invention discloses a method for predicting the remaining service life of a hydraulic cylinder and a corresponding hydraulic cylinder health state monitoring system. The method comprises the following steps that pressure parameters of the hydraulic cylinder, working state parameters representing the working state of a working device and operation state parameters representing the operation state of engineering machinery are obtained; calculating a hydraulic cylinder leakage parameter representing the leakage condition of the hydraulic cylinder based on the pressure parameter and the operation state parameter; calculating load parameters representing the actual load of the hydraulic cylinder based on the working state parameters; and predicting the residual service life of the hydraulic cylinder by means of a residual service life prediction model based on the hydraulic cylinder leakage parameter and the load parameter. According to the scheme, the residual service life of the hydraulic cylinder can be predicted through the model based on the neural network algorithm, and powerful support is provided for maintenance and management of the hydraulic cylinder.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering machinery detection, and in particular to a method for predicting the remaining service life of a hydraulic cylinder, a hydraulic cylinder health status monitoring system, and a computer-readable storage medium. Background Art

[0002] Hydraulic cylinders, key actuators in hydraulic transmission systems, are widely used in various types of construction machinery. However, due to the often harsh operating environments of construction machinery, hydraulic cylinders can experience wear and deformation after prolonged use, leading to performance degradation and even failure, impacting the entire construction machinery. Therefore, monitoring the health of hydraulic cylinders and predicting their remaining service life are crucial for ensuring stable operation, improving efficiency, and ensuring maintenance of construction machinery.

[0003] Because hydraulic cylinders operate in complex and ever-changing environments, their performance degradation and lifespan are affected by numerous factors, such as workload, temperature, and lubrication conditions. Consequently, accurately predicting the remaining useful life of hydraulic cylinders has always been a technical challenge. Existing hydraulic cylinder health monitoring systems can only provide information on the cylinder's current operating status, but are unable to accurately predict its remaining useful life.

[0004] Therefore, there is a need to further improve the existing hydraulic cylinder health status monitoring system and the remaining service life prediction method of the hydraulic cylinder. Summary of the Invention

[0005] The present invention proposes a method for predicting the remaining service life of a hydraulic cylinder and a corresponding hydraulic cylinder health status monitoring system, aiming to overcome one or more of the above-mentioned technical problems and / or other technical problems in the prior art.

[0006] According to one aspect of the present invention, a method for predicting the remaining service life of a hydraulic cylinder is provided, the method comprising the following steps:

[0007] S1: Acquire pressure parameters of the hydraulic cylinder, working state parameters representing the working state of the working device, and operating state parameters representing the operating state of the engineering machinery;

[0008] S2: Calculating a hydraulic cylinder leakage parameter representing a hydraulic cylinder leakage condition based on the pressure parameter and the operating state parameter;

[0009] S3: Calculating a load parameter representing an actual load of the hydraulic cylinder based on the working state parameter;

[0010] S4: Predicting the remaining service life of the hydraulic cylinder based on the hydraulic cylinder leakage parameter and the load parameter with the aid of a remaining service life prediction model.

[0011] According to another aspect of the present invention, a hydraulic cylinder health status monitoring system is proposed, which includes: a signal acquisition module and a computing device, the signal acquisition module includes a pressure sensor for detecting the pressure of the hydraulic cylinder and a working status sensor for detecting the working status parameters of the working device; wherein, the computing device is directly or indirectly connected to the signal acquisition module and the control module signal of the engineering machinery to obtain the pressure parameters of the hydraulic cylinder, the working status parameters characterizing the working status of the working device and the operating status parameters characterizing the operating status of the engineering machinery, wherein, the computing device is configured to implement any one of the above-mentioned embodiments of the method for predicting the remaining service life of the hydraulic cylinder.

[0012] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. The computer program includes executable instructions, which, when executed by a processor, implement any one of the above-mentioned embodiments of the method for predicting the remaining service life of a hydraulic cylinder.

[0013] In the method for predicting the remaining service life of a hydraulic cylinder and the corresponding hydraulic cylinder health status monitoring system proposed in the present invention, sensor technology is used to monitor the working status of the hydraulic cylinder in real time, thereby calculating the hydraulic cylinder leakage parameters. A model based on a neural network algorithm is then used to predict the remaining service life of the hydraulic cylinder based on the hydraulic cylinder leakage parameters and load parameters, providing strong support for the maintenance and management of the hydraulic cylinder. This is of great significance for ensuring the stable operation of construction machinery and improving the efficiency of equipment use. In addition, for construction machinery manufacturers, based on the remaining service life prediction results, they can promptly obtain the health status of the hydraulic cylinder and prepare spare parts management and schedule the corresponding after-sales service personnel in advance, thereby improving the quality and efficiency of after-sales service. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0015] Figure 1 is a flow chart of an embodiment of the method according to the present invention;

[0016] Figure 2 is a schematic diagram of an excavator with a hydraulic cylinder health status monitoring system;

[0017] Figure 3 1 is a schematic diagram of the architecture of a preferred embodiment of the hydraulic cylinder health status monitoring system according to the present invention. DETAILED DESCRIPTION

[0018] The exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the disclosure will be comprehensive and complete and will fully convey the concepts of the exemplary embodiments to those skilled in the art. In the drawings, the dimensions of some elements may be exaggerated or distorted for clarity. Identical reference numerals in the drawings represent identical or similar structures, and thus their detailed description will be omitted.

[0019] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present invention. However, those skilled in the art will appreciate that it is possible to practice the technical solution of the present invention without one or more of the specific details, or to adopt other methods, elements, etc. In other cases, known structures, methods or operations are not shown or described in detail to avoid blurring various aspects of the present invention.

[0020] Figure 1 1 is a flow chart of a preferred embodiment of a method for predicting the remaining service life of a hydraulic cylinder according to the present invention. As shown in the figure, the method includes the following steps:

[0021] S1: Acquire pressure parameters of the hydraulic cylinder, working state parameters representing the working state of the working device, and operating state parameters representing the operating state of the engineering machinery;

[0022] S2: Calculating a hydraulic cylinder leakage parameter representing a hydraulic cylinder leakage condition based on the pressure parameter and the operating state parameter;

[0023] S3: Calculating a load parameter representing an actual load of the hydraulic cylinder based on the working state parameter;

[0024] S4: Predicting the remaining service life of the hydraulic cylinder based on the hydraulic cylinder leakage parameter and the load parameter with the aid of a remaining service life prediction model.

[0025] Here, pressure parameters, working state parameters, and operating state parameters can be acquired in parallel or sequentially using corresponding sensors. Pressure parameters represent the pressure level in the corresponding hydraulic cylinder. Working state parameters characterize the operating state of the working device of the construction machinery, particularly the load condition. For example, these parameters may be angle parameters of the boom, arm, and bucket of an excavator. Operating state parameters include engine speed, hydraulic pump outlet pressure, and hydraulic oil temperature. Operating state parameters can be acquired from existing sensors in the construction machinery, as existing construction machinery is typically equipped with various sensors for detecting the aforementioned parameters.

[0026] The leakage of a hydraulic cylinder can be calculated by using pressure parameters over a period of time and the operating parameters of the construction machinery, thereby determining the corresponding hydraulic cylinder leakage parameters. For example, the Hilbert transform analysis method can be used to obtain the time domain characteristics of the hydraulic cylinder pressure, thereby reflecting the leakage status of the hydraulic cylinder.

[0027] The Hilbert transform is a commonly used technique in signal processing, used to extract phase information from real signals, thereby generating a complex analytic signal. Using the Hilbert transform is advantageous for analyzing hydraulic cylinder leakage. For example, if a hydraulic cylinder leak causes pressure fluctuations or flow rate variations, these signals can be processed using the Hilbert transform to extract relevant phase and frequency information. This information provides a deeper understanding of the dynamic characteristics of the leak, such as the leak rate and periodicity. In addition to the Hilbert transform, various other signal processing methods can be considered for analyzing hydraulic cylinder leakage, such as spectral analysis, time domain analysis, and statistical analysis. These methods primarily analyze various signals obtained from the hydraulic cylinder health monitoring system (such as pressure, engine speed, hydraulic pump outlet pressure, and hydraulic oil temperature) to reveal the characteristics and severity of the leak. For example, by performing spectral analysis on the hydraulic cylinder pressure signal, the energy distribution of the pressure signal at different frequencies can be extracted. Leakage typically causes the appearance or enhancement of certain frequency components. By observing and analyzing the changes in these frequency components, the presence and severity of the leak can be determined.

[0028] In addition, the actual load of the hydraulic cylinder can be calculated based on the angle parameters and pressure parameters combined with the known design parameters of the excavator (such as the size of each load-bearing component, the connection position relationship, etc.), so that the load parameters that characterize the actual load of the hydraulic cylinder can be obtained.

[0029] By combining hydraulic cylinder pressure and boom, arm, and bucket angle information collected by pressure and angle sensors with construction machinery operating parameters such as engine speed, hydraulic pump outlet pressure, and hydraulic oil temperature, a neural network model can be constructed to predict the remaining useful life. The goal of this model is to correlate load parameters and hydraulic cylinder leakage with the life loss of the hydraulic cylinder.

[0030] Based on the leakage parameters and load parameters of the hydraulic cylinder, the remaining service life of the hydraulic cylinder can be predicted with the help of a remaining service life prediction model. The remaining service life prediction model is, for example, an artificial intelligence model based on the BP (Back Propagation) neural network algorithm. The BP neural network algorithm is a multi-layer feedforward network trained according to the error back propagation algorithm. The advantages of the BP neural network algorithm are its powerful generalization ability, self-learning and self-adaptation ability, and its particular suitability for solving problems with complex internal mechanisms. The remaining service life prediction model can be pre-trained with the help of a large amount of experimental data and historical data. In addition, other algorithms can also be considered to construct a remaining service life prediction model, such as deep learning algorithms such as convolutional neural networks (CNN) and recurrent neural networks (RNN). Here, not only is real-time monitoring of the health status of the hydraulic cylinder of the construction machinery achieved, but also the load of the hydraulic cylinder is analyzed and modeled by combining big data analysis and deep learning, thereby achieving prediction of the remaining service life.

[0031] Preferably, the predicted remaining service life is transmitted to the control device of the construction machinery and displayed to the user on the display device of the construction machinery. Preferably, different lengths of remaining service life are displayed in different colors. For example, when the remaining service life is greater than 30 days, it is displayed in green. When the remaining service life is less than 30 days but greater than 15 days, it is displayed in yellow. When the remaining service life is less than 15 days, it is displayed in red. It is also possible to consider transmitting the predicted remaining service life to the mobile smart terminal of the construction machinery user, the manufacturer's remote monitoring platform, etc., so that the user can promptly know the remaining service life outside the construction machinery.

[0032] Furthermore, the remote monitoring platform preferably collects in real time the serial numbers of construction machinery whose remaining hydraulic cylinder life is less than a specified period, such as less than 30 days, and pushes this serial number and the location of the corresponding construction machinery to the corresponding dealer and / or service engineer. This allows the dealer and / or service engineer to manage spare parts and arrange travel schedules in advance, thereby improving the quality and efficiency of after-sales service.

[0033] Figure 2 A schematic diagram illustrates an engineering machine with a hydraulic cylinder health monitoring system. The engineering machine is an excavator. Obviously, the excavator is merely exemplary, and the engineering machine may also be a loader or other equipment.

[0034] An excavator primarily consists of a power unit, a traveling gear, a working device, and hydraulic and electrical systems. The traveling gear is the supporting part of the excavator, bearing the entire mass of the machine and the reaction force of the working device, while also enabling the excavator to travel short distances. Depending on their structure, traveling systems can be divided into two types: crawler-type and tire-type. The working device is the part of the excavator that directly performs excavation operations. Driven by the hydraulic system, the working device performs actions such as digging and loading.

[0035] like Figure 2 As shown, the working device includes a boom 1, an arm 4, and a bucket 6. The boom 1 is equipped with a boom hydraulic cylinder 2 and a boom sensor 9, which is used to detect the boom rotation angle. The arm 4 is equipped with an arm hydraulic cylinder 3 and an arm sensor 10, which is used to detect the arm inclination angle. The bucket 6 is equipped with a bucket hydraulic cylinder 5 and a bucket sensor 11, which is used to detect the bucket rotation angle. On the one hand, the piston of the bucket hydraulic cylinder 5 is hingedly connected to the bucket 6 by means of a push rod 7, and on the other hand, the piston of the bucket hydraulic cylinder 5 is hingedly connected to the arm 4 by means of a rocker arm 8, wherein the push rod 7 and the rocker arm 8 are hingedly connected to the piston of the bucket hydraulic cylinder 5 at the same hinge point. In addition, the boom hydraulic cylinder 2, the arm hydraulic cylinder 3, and the bucket hydraulic cylinder 5 are respectively equipped with pressure sensors (not shown) for detecting the pressure parameters of each hydraulic cylinder.

[0036] Therefore, the specific angle parameters are the boom angle, dipper arm tilt angle, and bucket angle. All angle and pressure parameters are transmitted to a cloud platform or remote server, such as the manufacturer's remote monitoring platform, using the construction machinery's communication module, such as the vehicle-mounted remote communication terminal T-Box. This remote monitoring platform includes a backend system that includes a remaining service life prediction model and various other algorithms. Since the dimensions and connection positions of the boom, dipper arm, and bucket are known, the actual load of each hydraulic cylinder in its operating state can be calculated based on the pressure and angle parameters, thereby deriving the corresponding load parameters.

[0037] Although not shown, the construction machine further includes a speed sensor for detecting engine speed, a temperature sensor for detecting hydraulic oil temperature, another pressure sensor for detecting hydraulic pump outlet pressure, and other necessary sensors. Signals from these sensors form operating state parameters that characterize the operating state of the construction machine and are preferably available from a control module of the construction machine via a CAN bus.

[0038] The operating status parameters are also transmitted, for example, via the communication module to a manufacturer's remote monitoring platform. Here, based on the operating status parameters and the aforementioned pressure parameters over a period of time, the hydraulic cylinder's leakage status can be determined using, for example, a Hilbert transform analysis method, and the corresponding hydraulic cylinder leakage parameter can be determined. Finally, the remaining service life prediction model is used to predict the hydraulic cylinder's remaining service life using the hydraulic cylinder leakage parameter and load parameters. The predicted results can also be transmitted to the construction machine via the communication module and displayed to the user.

[0039] In an exemplary embodiment of the present application, a computer-readable storage medium is further provided, on which a computer program is stored. The program includes executable instructions. When executed by, for example, a processor, the executable instructions can implement the steps of the method for predicting the remaining useful life of a hydraulic cylinder described in any of the aforementioned embodiments. In some possible implementations, various aspects of the present application can also be implemented in the form of a program product, which includes program code. When the program product is executed on a terminal device, the program code is used to cause the hydraulic cylinder health monitoring system to perform the steps described in the method for predicting the remaining useful life of a hydraulic cylinder according to various exemplary embodiments of the present application.

[0040] The computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein the readable program code is carried. The data signal propagated may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable storage medium other than an optical disc, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0041] The program code for performing the operations of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0042] Refer to the following Figure 3 A schematic diagram of the architecture of a preferred embodiment of the hydraulic cylinder health status monitoring system according to the present application is described below. Figure 3 The hydraulic cylinder health status monitoring system shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0043] like Figure 3 As shown, the hydraulic cylinder health monitoring system includes a signal acquisition module 14, a communication module 15, and a cloud platform 12. This system is independent of the vehicle's control system and can be installed separately on the construction machinery. Although the cloud platform 12 and the programs deployed on it are shown here, it is obviously also possible to consider abandoning the cloud platform and adopting a local computing model. That is, all programs are deployed locally, such as on the construction machinery's computer equipment, and the relevant calculations and storage are performed there. However, it should be noted that the use of the cloud platform 12 has significant advantages in terms of computing power and storage space.

[0044] The signal acquisition module 14 includes the various sensors mentioned above, such as pressure sensors and angle sensors. The communication module 15 can be, for example, a vehicle-mounted remote communication terminal (T-Box). The communication module 15 is signal-connected to the signal acquisition module 14, specifically directly or indirectly connected to each of the sensors in the signal acquisition module 14 to obtain pressure parameters and operating status parameters. The communication module also signals-connects to the construction machine's existing sensors, such as the engine speed sensor, hydraulic oil temperature sensor, and hydraulic pump outlet pressure sensor. Specifically, the communication module 15 signals-connects to the construction machine's control device 16 via, for example, the CAN bus, to obtain operating status parameters such as engine speed, hydraulic oil temperature, and hydraulic pump outlet pressure. The communication module 15 can obtain the construction machine's operating status parameters from the construction machine's control device 16 via the construction machine's CAN bus and / or transmit calculation results from the cloud platform 12, such as the predicted remaining service life, to the construction machine, such as the control device 16 in the cab. A display device can be provided in the cab to present the predicted remaining service life to the user via a display interface. Preferably, different colors are used to represent different remaining service lives.

[0045] The communication module 15 can transmit various sensor data to the remote server or cloud platform 12 via a remote communication network, such as Ethernet or a mobile communication network. Specifically, the remote server or cloud platform 12 indirectly connects to the signal acquisition module 14 and the construction machinery control device 16 via the communication module 15 to obtain hydraulic cylinder pressure parameters, operating parameters representing the working state of the working device, and operating parameters representing the operational state of the construction machinery. This sensor data is stored in a database 13 on the remote server or cloud platform 12. The database 13, the remaining useful life prediction model, and other possible computational programs are deployed on the remote server or cloud platform.

[0046] Despite Figure 3 The communication module 15 is shown, but it can also be omitted. Specifically, a computer device installed on the construction machinery serves as the computing device. The computing device is directly connected to the signal acquisition module and the construction machinery's control device to obtain hydraulic cylinder pressure parameters, operating state parameters representing the working state of the working device, and operating state parameters representing the operating state of the construction machinery. In this case, the computer device on the construction machinery is equipped with a trained remaining useful life prediction model.

[0047] Overall, the solution in this application, by collecting multiple parameters and combining them with machine learning algorithms, can more comprehensively reflect the operating status and performance changes of hydraulic cylinders, improving prediction accuracy. Furthermore, by collecting and distributing remaining service life information in real time, this invention can help dealers and service engineers manage spare parts and prepare for repairs in advance, reducing maintenance wait times and improving equipment operational efficiency.

[0048] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, server, or network device, etc.) to execute the method for predicting the remaining service life of a hydraulic cylinder according to the embodiments of the present application.

[0049] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the disclosure herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the appended claims.

Claims

1. A method for predicting the remaining service life of a hydraulic cylinder, the method comprising the following steps: Acquiring pressure parameters of the hydraulic cylinder, working state parameters representing the working state of the working device, and operating state parameters representing the operating state of the engineering machinery; Calculating a hydraulic cylinder leakage parameter representing a hydraulic cylinder leakage condition based on the pressure parameter and the operating state parameter; Calculating a load parameter representing an actual load of the hydraulic cylinder based on the working state parameter; Based on the hydraulic cylinder leakage parameter and load parameter, the remaining service life of the hydraulic cylinder is predicted with the help of a remaining service life prediction model, and the remaining service life prediction model is an artificial intelligence algorithm model.

2. The method according to claim 1, characterized in that The working state parameters include angle parameters of the boom, the dipper arm, and the bucket, and the operating state parameters include engine speed, hydraulic pump outlet pressure, and hydraulic oil temperature.

3. The method according to claim 1 or 2, characterized in that The Hilbert transform analysis method is used to determine the corresponding hydraulic cylinder leakage parameters through the pressure parameters and operating state parameters over a period of time.

4. The method according to claim 1 or 2, characterized in that The remaining useful life prediction model is an artificial intelligence algorithm model based on the BP neural network algorithm.

5. The method according to claim 1 or 2, characterized in that The predicted remaining service life is transmitted to a control device of the construction machine and displayed to a user on a display device of the construction machine.

6. The method according to claim 5, characterized in that Different colors show the remaining service life.

7. The method according to claim 1 or 2, characterized in that The machine serial number of the engineering machinery whose remaining service life of the hydraulic cylinder is less than the specified time and the geographical location information of the corresponding engineering machinery are pushed to the corresponding agent and / or service engineer.

8. The method according to claim 1 or 2, characterized in that The pressure parameter, the working state parameter and the operating state parameter are obtained in parallel, or the pressure parameter, the working state parameter and the operating state parameter are obtained in sequence.

9. A hydraulic cylinder health status monitoring system, the health status monitoring system comprising: Signal acquisition module and computing device; The signal acquisition module includes a pressure sensor for detecting the pressure of the hydraulic cylinder and a working status sensor for detecting the working status parameters of the working device; wherein the computing device is directly or indirectly connected to the signal acquisition module and the control module signal of the engineering machinery to obtain the pressure parameters of the hydraulic cylinder, the working status parameters characterizing the working status of the working device and the operating status parameters characterizing the operating status of the engineering machinery, wherein the computing device is configured to implement the method for predicting the remaining service life of the hydraulic cylinder according to any one of claims 1 to 8.

10. The hydraulic cylinder health status monitoring system according to claim 9, characterized in that: The health status monitoring system also includes a communication module, which is signal-connected to the signal acquisition module and the computing device respectively and is configured to send the pressure parameters, working status parameters and operating status parameters to the computing device and transmit the calculation results of the computing device to the engineering machinery.

11. The hydraulic cylinder health status monitoring system according to claim 10, characterized in that: The communication module is a vehicle-mounted remote communication terminal.

12. The hydraulic cylinder health status monitoring system according to any one of claims 9 to 11, characterized in that: The computing device is a cloud platform, a remote server, or a computer device installed on engineering machinery. 13 . A computer-readable storage medium having a computer program stored thereon, the computer program comprising executable instructions, which, when executed by a processor, implement the method for predicting the remaining service life of a hydraulic cylinder according to claim 1 .

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