Model-free self-adaptive control method for electro-hydraulic servo system of drilling machine based on data driving

Abstract

The invention discloses a model-free self-adaptive control drilling machine electro-hydraulic servo system method and system based on data driving, and relates to the technical field of self-adaptive control drilling machine electro-hydraulic servo, and the method comprises the steps: obtaining real-time data of a drilling machine electro-hydraulic servo system, and carrying out the preprocessing; finding out the correlation between the environmental parameters and the system performance indexes by using a data mining and statistical analysis method; adjusting system control parameters in real time according to the real-time data collected in real time and the association obtained through analysis; and according to the actual operation effect of the system and the new real-time data, the strategy of environment adaptation and fault prevention is continuously optimized and adjusted. The control parameters are adjusted based on real-time data and correlation obtained through analysis, compared with a traditional method, the drilling machine electro-hydraulic servo system can be controlled more accurately, the maintenance and replacement frequency of equipment is reduced, and therefore the operation cost is reduced, the strategy is optimized continuously according to the actual operation effect and new data, and the operation efficiency is improved. And the conditions of accidental shutdown and production interruption are reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of adaptive control of drilling rig electro-hydraulic servo, and in particular relates to a data-driven model-free adaptive control method of a drilling rig electro-hydraulic servo system. Background Art

[0002] In the modern industrial field, especially in the drilling industry, the performance and reliability of the drilling rig electro-hydraulic servo system are crucial. Traditional drilling rig electro-hydraulic servo system control methods often rely on accurate physical models, but due to the complexity and variability of actual working conditions, it becomes extremely challenging to establish accurate physical models. With the continuous improvement of data acquisition technology and computing power, data-driven control methods have gradually attracted attention. In the past, research on the control of drilling rig electro-hydraulic servo systems has mainly focused on model-based control strategies. However, these methods often show limitations when facing the nonlinearity, time-varying and uncertainty of the system. Due to changes in environmental factors, wear and aging of the system, model parameters may change, resulting in The control effect is not good. Some existing control methods are not flexible and accurate enough when dealing with the relationship between environmental parameters and system performance indicators. The system often cannot respond to changes in environmental parameters in a timely and effective manner, thus affecting the efficiency and quality of drilling operations. In terms of fault prevention, traditional methods are usually based on regular maintenance and experience judgment, lacking accurate monitoring and analysis of the real-time operating status of the system, making it difficult to provide early warning and timely processing. In order to improve the control performance, adaptability and reliability of the drilling rig electro-hydraulic servo system, there is an urgent need for a data-driven model-free adaptive control method that can handle complex changes in the system in real time and optimize environmental adaptation and fault prevention strategies to meet the high requirements of modern drilling operations.

[0003] However, the common solutions currently available have many shortcomings, including: traditional methods rely on precise physical models, while actual operating conditions are complex and changeable, making model construction difficult and inaccurate, which makes it difficult for model parameters to adapt to environmental changes, system wear and aging, and other situations, and the control effect is unstable; existing control strategies lack flexibility and accuracy when dealing with the relationship between environmental parameters and system performance indicators. They cannot capture the dynamic changes of the environment in a timely and effective manner, and are slow to respond to the impact on system performance, thereby reducing the efficiency and quality of drilling operations; in terms of fault prevention, traditional methods rely more on regular maintenance and experience-based judgment, and cannot accurately monitor and analyze based on the real-time operating results of the system and new real-time data, which makes it difficult to warn and deal with faults in advance, increasing the risk of system failures and maintenance costs. Summary of the invention

[0004] The purpose of the present invention is to provide a method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system, which is suitable for solving the problem that existing control strategies lack flexibility and accuracy when dealing with the association between environmental parameters and system performance indicators. They cannot capture the dynamic changes of the environment in a timely and effective manner, and are slow to respond to the impact on system performance, thereby reducing the efficiency and quality of drilling operations.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for controlling a drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control comprises the following steps:

[0007] S1: obtain the real-time data of the drilling rig electro-hydraulic servo system and perform pre-processing;

[0008] S2: Use data mining and statistical analysis methods to find the correlation between environmental parameters and system performance indicators;

[0009] S3: According to the real-time data collected in real time and the correlation obtained by analysis in S2, the control parameters of the drilling rig electro-hydraulic servo system are adjusted in real time;

[0010] S4: Continuously optimize and adjust environmental adaptation and fault prevention strategies based on the actual operating results of the drilling rig’s electro-hydraulic servo system and new real-time data.

[0011] Preferably, the real-time data include hydraulic pressure, flow, rotation speed, current and voltage; the environmental parameters include temperature, humidity and air pressure; and the system performance indicators include control accuracy, response speed, dynamic performance and energy efficiency.

[0012] Preferably, the specific formula of the data mining and statistical analysis method in S2 is as follows:

[0013]

[0014] Among them, R is the quantitative result of the correlation between environmental parameters and system performance indicators; E is the set of environmental parameters, E j is the value of the jth environmental parameter, m is the number of environmental parameters; S is the set of system performance indicators, S k is the value of the kth system performance indicator, l is the number of system performance indicators, p is the index used to calculate the sum of products, and q is the number of environmental parameters and system performance indicators involved in calculating the sum of products.

[0015] Preferably, based on the quantitative result R of the correlation degree between real-time data and environmental parameters and system performance indicators, the control parameters of the drilling rig electro-hydraulic servo system are adjusted to obtain adjustment values, and based on the adjustment values ​​and new real-time data, the strategies for environmental adaptation and fault prevention are continuously adjusted to obtain result values.

[0016] Preferably, the specific formula of the adjustment value L1 is as follows:

[0017]

[0018] Among them, L1 is the adjustment value, R is the quantitative result of the correlation between the environmental parameters and the system performance indicators, D is the real-time data, and T, S, and U are the corresponding summation times.

[0019] Preferably, the result value L t The specific formula is as follows:

[0020]

[0021] Among them, L t is the result value; L1 is the adjustment value; n is the number of data; D new is the new real-time number.

[0022] Preferably, a data acquisition module is used to collect real-time data of the drilling rig electro-hydraulic servo system; a data analysis module is used to mine the relationship between environmental parameters and system performance indicators; a parameter adjustment module is used to adjust system control parameters in real time; and an optimization adjustment module is used to continuously optimize and adjust environmental adaptation and fault prevention strategies.

[0023] A computer device comprises a memory and a processor, wherein the memory stores a computer program and the processor executes the steps of a method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system.

[0024] A computer-readable storage medium stores a computer program, which, when executed by a processor, is a method for adaptively controlling a drilling rig electro-hydraulic servo system based on data-driven model-free control.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention adjusts control parameters based on real-time data and the association obtained through analysis. Compared with traditional methods, it can control the drilling rig electro-hydraulic servo system more accurately and reduce errors. Since it can prevent faults and optimize system performance in time, it reduces the frequency of equipment maintenance and replacement, thereby reducing operating costs. It continuously optimizes strategies based on actual operating results and new data, so that the system remains stable and reliable in long-term operation, and reduces unexpected downtime and production interruptions. This data-driven model-free adaptive control method is in line with the development trend of modern industrial intelligence and automation, and provides strong support for technological upgrading in the drilling industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flowchart for implementing embodiment 1 of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] Example 1

[0029] Reference Figure 1 , which is the first embodiment of the present invention, provides a method for controlling a drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control, comprising the following steps:

[0030] S1: Obtain the real-time data of the drilling rig electro-hydraulic servo system and perform preprocessing. The real-time data includes hydraulic pressure, flow, speed, current, voltage and other real-time data. The preprocessing ensures the quality and consistency of the data by preprocessing the vehicle driving data and real-time data on the edge node in real time, including data cleaning, noise reduction and standardization.

[0031] S2: Use data mining and statistical analysis methods to find the relationship between environmental parameters and system performance indicators. Environmental parameters include temperature, humidity and air pressure, and system performance indicators include control accuracy, response speed, dynamic performance and energy efficiency.

[0032] The specific formulas of data mining and statistical analysis methods are as follows:

[0033]

[0034] Among them, R is the quantitative result of the correlation between environmental parameters and system performance indicators; E is the set of environmental parameters, E jis the value of the jth environmental parameter, m is the number of environmental parameters; S is the set of system performance indicators, S k is the value of the kth system performance indicator, l is the number of system performance indicators, p is the index used to calculate the sum of products, and q is the number of environmental parameters and system performance indicators involved in calculating the sum of products.

[0035] S3: Adjust the system control parameters in real time according to the real-time data collected in real time and the correlation obtained by analysis in S2. Based on the quantitative results of the correlation between the real-time data and environmental parameters and the system performance indicators, adjust the system control parameters to obtain the adjustment value. Based on the adjustment value and the new real-time data, continuously adjust the environmental adaptation and fault prevention strategies to obtain the result value.

[0036] The specific formula for adjusting the value L1 is as follows:

[0037]

[0038] Among them, L1 is the adjustment value; R is the quantitative result of the correlation between the environmental parameters and the system performance indicators; D is the real-time data; T, S, and U are the corresponding summation times.

[0039] S4: Continuously optimize and adjust environmental adaptation and fault prevention strategies based on the actual operating results of the system and new real-time data.

[0040] Furthermore, the result value L t The specific formula is as follows:

[0041]

[0042] Among them, L t is the result value; L1 is the adjustment value; n is the number of data; D new For new real-time data.

[0043] This embodiment also provides a data-driven model-free adaptive control drilling rig electro-hydraulic servo system, including: a data acquisition module, used to collect real-time data of the drilling rig electro-hydraulic servo system; a data analysis module, used to mine the relationship between environmental parameters and system performance indicators; a parameter adjustment module, used to adjust the system control parameters in real time; an optimization adjustment module, used to continuously optimize and adjust the environmental adaptation and fault prevention strategies.

[0044] This embodiment also provides a computer device, which is suitable for a method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system as proposed in the above embodiment.

[0045] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0046] The present embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, a method for realizing a data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system is implemented as proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, disk or optical disk.

[0047] In summary, the present invention adjusts control parameters based on real-time data and the association obtained through analysis. Compared with traditional methods, it can control the drilling rig electro-hydraulic servo system more accurately and reduce errors. Since it can prevent faults and optimize system performance in time, it reduces the frequency of equipment maintenance and replacement, thereby reducing operating costs. It continuously optimizes strategies based on actual operating results and new data to keep the system stable and reliable in long-term operation and reduce unexpected downtime and production interruptions. This data-driven model-free adaptive control method is in line with the development trend of modern industrial intelligence and automation, and provides strong support for technological upgrading in the drilling industry.

[0048] Example 2

[0049] Referring to Tables 1 to 3, which are the second embodiment of the present invention, this embodiment is different from the first embodiment in that, in order to verify its beneficial effects, operating data and related instructions of the present invention in an actual environment are provided.

[0050] As shown in Table 1, the detailed performance differences in drilling speed, drilling speed, drilling accuracy and drilling depth between our invention and the prior art using different control methods in this example are shown.

[0051] Table 1 Drilling performance comparison table

[0052]

[0053] As shown in Table 2, the energy consumption data of our invention and the prior art using different control methods in different working time periods are compared in this example, and the energy-saving effects of the two control methods are clearly compared.

[0054] Table 2 Energy consumption comparison table

[0055]

[0056] As shown in Table 3, the number of different types of faults, the number of motor faults and the duration of faults during the test period are compared between our invention and the prior art in this example, which deeply reflects the remarkable effectiveness of the two control methods in fault prevention and handling.

[0057] Table 3 Fault Condition Comparison Table

[0058]

[0059] It can be seen from the above table that the present invention has good performance in key areas such as drilling performance, energy consumption control and fault prevention, and provides a highly competitive and innovative solution for the efficient, stable and energy-saving operation of the drilling rig electro-hydraulic servo system.

[0060] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A data-driven model-free adaptive control method for drilling rig electro-hydraulic servo system, characterized in that: The following steps are involved: S1: obtain the real-time data of the drilling rig electro-hydraulic servo system and perform pre-processing; S2: Use data mining and statistical analysis methods to find the correlation between environmental parameters and system performance indicators; S3: According to the real-time data collected in real time and the correlation obtained by analysis in S2, the control parameters of the drilling rig electro-hydraulic servo system are adjusted in real time; S4: Continuously optimize and adjust environmental adaptation and fault prevention strategies based on the actual operating results of the drilling rig’s electro-hydraulic servo system and new real-time data.

2. The method for controlling a drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control according to claim 1, characterized in that: The real-time data includes hydraulic pressure, flow, speed, current and voltage; the environmental parameters include temperature, humidity and air pressure; and the system performance indicators include control accuracy, response speed, dynamic performance and energy efficiency.

3. The method for controlling a drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control according to claim 1, characterized in that: The specific formula of the data mining and statistical analysis method described in S2 is as follows: Among them, R is the quantitative result of the correlation between environmental parameters and system performance indicators; E is the set of environmental parameters, E j is the value of the jth environmental parameter, m is the number of environmental parameters; S is the set of system performance indicators, S k is the value of the kth system performance indicator, l is the number of system performance indicators, p is the index used to calculate the sum of products, and q is the number of environmental parameters and system performance indicators involved in calculating the sum of products.

4. The method for controlling a drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control according to claim 3 is characterized in that: Based on the quantitative result R of the correlation degree between real-time data and environmental parameters and system performance indicators, the control parameters of the drilling rig electro-hydraulic servo system are adjusted to obtain the adjustment value. Based on the adjustment value and new real-time data, the environmental adaptation and fault prevention strategies are continuously adjusted to obtain the result value.

5. The method for controlling the drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control according to claim 4, characterized in that: The specific formula of the adjustment value L1 is as follows: Among them, L1 is the adjustment value, R is the quantitative result of the correlation between the environmental parameters and the system performance indicators, D is the real-time data, and T, S, and U are the corresponding summation times.

6. The method for controlling the drilling rig electro-hydraulic servo system based on data-driven model-free adaptive control according to claim 4, characterized in that: The result value L t The specific formula is as follows: Among them, L t is the result value; L1 is the adjustment value; n is the number of data; D new is the new real-time number.

7. A method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system according to claims 1-6, characterized in that: include: Data acquisition module, used to collect real-time data of the drilling rig's electro-hydraulic servo system; Data analysis module, used to mine the correlation between environmental parameters and system performance indicators; The parameter adjustment module is used to adjust the system control parameters in real time; the optimization adjustment module is used to continuously optimize and adjust the strategies for environmental adaptation and fault prevention.

8. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method implements the steps of a method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a method for data-driven model-free adaptive control of a drilling rig electro-hydraulic servo system as described in any one of claims 1 to 7 are implemented.

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