Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Petroleum machinery winch cable tension intelligent control method

A petroleum machinery and intelligent control technology, applied in the direction of mechanical pressure/force control, adaptive control, general control system, etc., can solve the problems of error uncertainty, easy oscillation, single parameter, etc., to eliminate transmission error and friction High precision of torque and control, and the effect of reducing the number of iterations

Pending Publication Date: 2022-06-24
SOUTHWEST PETROLEUM UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Most domestic winch tension control still relies on the experience of winch workers to manually operate by observing the parameters on the display, and constantly correct the hydraulic pump pressure or motor parameters to control the tension. This kind of open-loop control without feedback and detection links has a lot of problems. Errors and uncertainties, and in severe cases, misoperation may lead to safety accidents
Due to the very complicated downhole working conditions during drilling and logging, the radius of the drawworks is constantly changing during the winding process of the cable or wire rope, and the cable tension control system is very complicated. The real-time control requirements of the tension control system are difficult to meet the response speed and control accuracy requirements of the tension control, and there are uncertainties

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Petroleum machinery winch cable tension intelligent control method
  • Petroleum machinery winch cable tension intelligent control method
  • Petroleum machinery winch cable tension intelligent control method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0024] An intelligent control method for the cable tension of a petroleum machinery winch in this embodiment 1, combined with figure 1 Examples of the present invention will be described.

[0025] For the 7000-meter electric drive logging vehicle as the object, as shown in the attached figure 1 As shown in the figure, the fuzzy PID control algorithm is written into the S7-1200 CPU in the form of PLC language, and the tension signal of the tensiometer is transmitted to the PLC for self-adaptive PID parameter setting. Automatic control process.

[0026] For the closed-loop control of the tension of the cable winch, it is first necessary to establish a mathematical model of the tension PID control. If the cable is in the lifting state, the real-time radius after the cable is wound around the drum is R, and the angular velocity of the winch drum is ω w , the cable tension is F, and the winch driving torque M w , the viscous friction torque M of the winch drum f , J w It is t...

Embodiment 2

[0049] The difference between this implementation and Example 1 is that, in order to describe the cable tension nonlinear control system, improve the stability, and have better generalization ability, the neural network is combined with the PID controller, and the self-learning of the neural network is fully utilized. Ability to continuously self-learn and self-tune the adjustable parameters of the PID controller, so as to independently find the best combination that can optimize the control performance of the PID controller. The details are as follows:

[0050] Taking into account the operating efficiency and control performance requirements of the tension control system, the "4-5-3" three-layer BP neural network structure is adopted, that is, the input layer is 4 neural nodes, the hidden layer is 5 neural nodes, and the output layer is 3 neural nodes. The learning algorithm uses the gradient descent method to continuously update the weights between layers through error backp...

Embodiment 3

[0055] The difference between this implementation and Example 1 and Example 2 is that, in order to combine the advantages of fuzzy logic and neural network control, the fuzzy system has the learning ability and the physical meaning of each node of the neural network is clear. The knowledge of tension approximate dynamics model and manual debugging experience are used to construct the framework to speed up the learning process. The self-learning ability of the fuzzy neural network can be used to correct the adjustable parameters of the PID online. The details are as follows:

[0056] Fuzzy logic has a set of rule bases based on expert experience, which can express knowledge with fewer rules; neural network has strong learning ability and parallel processing ability, and can generate rules without expressing knowledge. And both can be applied to the system where the input-output relationship is a nonlinear mapping. The FNN-PID controller is composed of a fuzzy neural network and...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an intelligent control method for cable tension of a petroleum mechanical winch. A tension feedback signal is directly transmitted to a controller in real time through a tensiometer which is independently and separately arranged between a ground pulley and a roller, the controller outputs a control signal to a driving motor through a frequency converter, the driving motor transmits motion to the roller, the output torque of the driving motor is dynamically adjusted, and a full-closed-loop tension control system is established. The control method comprises the following steps: calculating a layer index of hierarchical control according to the total length of a cable and the size of a roller, optimizing an initial value of a control parameter for each layer by combining analysis modeling and prior experience, and adaptively correcting a PID (Proportion Integration Differentiation) regulation value by using fuzzy control, a neural network or a fuzzy neural network intelligent control algorithm. The method can be used for cable car tension intelligent control of the winch for petroleum drilling, well logging, well repairing and the like, the tension control precision can be improved, the labor amount of operators is reduced, and a foundation is laid for achieving an intelligent winch system.

Description

technical field [0001] The invention relates to the field of oil drilling and well logging, in particular to a tension control method for a winch cable, which can provide technical support for a cable or wire rope tension control system for drilling, logging and workover. Background technique [0002] In the fields of petroleum equipment, marine equipment, pipeline maintenance, etc., some tasks are often involved in the use of winch drums to drive cables or wire ropes to wind or release. During the working process of the winch, the tension control of cables or wire ropes is very critical. For example, the logging truck is an important equipment in the exploitation of oil and gas fields, and the cable tension is the most important parameter in the lifting and lowering process of the logging instrument. Constant tension control can make the logging instrument run stably, prevent downhole accidents such as cable breakage, ensure the accuracy of logging data, and improve the eff...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04G05D15/01B66D1/60B66D1/40B66D1/22B66D1/12
CPCG05B13/04G05D15/01B66D1/60B66D1/40B66D1/12B66D1/22
Inventor 李炳林杨双业樊勇利秦羿涵夏辉王议张彦伟王洪
Owner SOUTHWEST PETROLEUM UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products