Air pressure grinding wheel blade self-adaptive grinding device and method based on multi-sensor feedback

Abstract

The invention discloses an air pressure grinding wheel blade self-adaptive grinding device and method based on multi-sensor feedback. The device comprises a mechanical arm and an air pressure grinding wheel tail end executing mechanism installed at the tail end of the mechanical arm. The air pressure grinding wheel tail end executing mechanism comprises an air pressure grinding wheel grinding head, a pressure adjusting connector, a six-dimensional force sensor, a driving motor and a sealing shell. The sealing shell is provided with a pressure regulating interface; the air pressure grinding wheel grinding head is rotationally connected to the outer end of the sealing shell. An inner cavity of the air pressure grinding wheel grinding head is communicated with the pressure regulating interface on the sealing shell through a flow channel; the air pressure grinding wheel attached with the soft fixed grinding material is used for machining the blade, the air pressure grinding wheel serves as a flexible grinding end effector, the machining requirement of the complex curved surface of the blade can be met, and stress concentration and damage during machining are reduced. In addition, state parameters such as grinding force can be dynamically corrected, and the blade grinding precision is improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent manufacturing, and in particular relates to a pneumatic grinding wheel blade adaptive grinding device and method based on multi-sensor feedback. Background Art

[0002] Aircraft engine blades are typical thin-walled, complex free-form surface parts. The materials used are difficult to process and have the characteristics of low thermal conductivity and elastic modulus. Factors such as thermal deformation and stress deformation directly affect their processing quality.

[0003] In addition to aircraft engine blades, blades are also key parts of industrial turbines such as compressors, axial flow fans, and gas turbines. They are widely used in energy and electricity, rail transit, petrochemicals, national defense and military industries, and other fields.

[0004] Grinding and polishing are essential and key links in the blade manufacturing process. Through rough polishing, semi-finishing polishing, fine polishing and other processes, the blade's machining allowance can be removed, the shape and size can be trimmed, and the surface roughness can be improved to achieve a blade shape and surface mirror gloss that meets the technical requirements.

[0005] At present, the polishing of various blades in China is basically done by manual operation, which has low polishing efficiency and occupies a large amount of human resources. In addition, a large amount of dust is generated during manual polishing, which seriously affects the health of operators. At present, my country has gradually shown a shortage of skilled blade polishing workers. Blade polishing has become a bottleneck in the development of the blade industry, restricting the improvement of the finishing capabilities of blade production enterprises and affecting the sustainable development of blade production enterprises. It is urgent to develop technologies and systems for automatic and intelligent blade polishing, gradually realize the replacement of manual polishing technology, realize the replacement of polishing machines, and reduce the occupation of enterprise human resources by blade polishing. At the same time, it is necessary to improve the grinding execution tools to improve the processing efficiency and quality consistency of blade polishing. Summary of the invention

[0006] The purpose of the present invention is to provide a pneumatic grinding wheel blade adaptive grinding device and method based on multi-sensor feedback to solve the problems of poor precision, low surface positioning accuracy, low grinding efficiency and poor effect in traditional blade grinding.

[0007] In a first aspect, the present invention provides a pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback, comprising a mechanical arm, and a pneumatic grinding wheel end actuator installed at the end of the mechanical arm; the pneumatic grinding wheel end actuator comprises a pneumatic grinding wheel grinding head, a pressure regulating interface, a six-dimensional force sensor, a driving motor and a sealed housing;

[0008] A pressure regulating interface is provided on the sealed shell; the pneumatic grinding wheel grinding head is rotatably connected to the outer end of the sealed shell; the inner cavity of the pneumatic grinding wheel grinding head is connected to the pressure regulating interface on the sealed shell through a flow channel; the driving motor is used to drive the pneumatic grinding wheel grinding head to rotate; the six-dimensional force sensor is used to detect the grinding force of the pneumatic grinding wheel grinding head; the pressure regulating interface is used to adjust the internal pressure of the pneumatic grinding wheel grinding head.

[0009] Preferably, the pneumatic grinding wheel grinding head comprises a wrapping layer, a granular filler in the wrapping layer, and abrasive grains attached to the outer surface of the wrapping layer, and the rigidity of the pneumatic grinding wheel grinding head is changed by adjusting the internal pressure of the wrapping layer.

[0010] Preferably, the pneumatic grinding wheel blade adaptive grinding device further comprises an inertial sensor; the inertial sensor is fixed on the sealed housing and is used to detect the acceleration of the pneumatic grinding wheel grinding head.

[0011] Preferably, the base of the six-dimensional force sensor is fixed to the end of the robotic arm; the housing of the drive motor is installed on the detection part; the sealed housing and the housing of the drive motor.

[0012] Preferably, a rotating body-shaped inner cavity is provided in the sealed shell; the inner cavity of the sealed shell coincides with the axis of the output shaft of the drive motor; the inner end of the pneumatic grinding wheel grinding head is coaxially fixed with the output shaft of the drive motor in the inner cavity of the sealed shell.

[0013] Preferably, the grinding area of ​​the pneumatic grinding wheel grinding head is hemispherical.

[0014] Preferably, it further comprises an infrared temperature sensor; the infrared temperature sensor is installed at the end of the sealed housing.

[0015] In a second aspect, the present invention provides a pneumatic grinding wheel blade adaptive control method based on multi-sensor feedback, which is used to control the aforementioned pneumatic grinding wheel blade adaptive grinding device; the pneumatic grinding wheel blade adaptive control method comprises the following steps:

[0016] Step 1: Predict the prior estimate of the current state vector through the state transfer equation and the prior covariance matrix

[0017] Step 2: Calculate the Kalman gain K k ; Correct the prior estimate by Kalman gain Get the state vector estimate and covariance P k ;

[0018] Step 3: Estimate the value based on the state vector The position and internal pressure of the pneumatic grinding wheel grinding head are controlled with the expected value of the state vector.

[0019] Preferably, the Kalman gain K k The expression is as follows:

[0020]

[0021] Where H is the Jacobian matrix for the state vector; R k is the matrix covariance.

[0022] Preferably, the state vector estimate and covariance P k The expression is as follows:

[0023]

[0024] Among them, Z(k) is the observation vector.

[0025] Preferably, the state vector estimate Including grinding force F E (k); grinding force F E (k) inputting an active disturbance rejection controller; the active disturbance rejection controller comprises a tracking differentiator, an extended state observer and a nonlinear state error feedback;

[0026] The discrete form of the tracking differentiator is:

[0027] F E (k+1)=F E (k)+T′F′ E (k)

[0028] F′ E (k+1)=F′ E (k)+Tfst(F E (k)-F Ed ,F′ E (k),r,T)

[0029] Among them, F E (k), F E (k+1) are the grinding forces at the current moment and the next moment respectively; F′ E (k), F′ E (k+1) are the grinding force change rates at the current moment and the next moment respectively; T' is the integration step; r is the speed factor; F Ed is the expected grinding force, and fst(·) is the most nonlinear weighted sum function.

[0030] The present invention has the beneficial effects:

[0031] 1. The present invention uses a pneumatic grinding wheel with soft fixed abrasive to process blades. The pneumatic grinding wheel, as a flexible grinding end effector, can adapt to the complex curved surface processing requirements of blades and reduce stress concentration and damage during processing. In addition, the present invention can dynamically correct state parameters such as grinding force to improve the grinding accuracy of blades.

[0032] 2. The present invention uses a six-dimensional force sensor to calculate and adjust the grinding angle and force direction in real time, ensuring that the pneumatic grinding wheel and the blade surface always maintain an optimal working posture, thereby improving the blade grinding quality.

[0033] 3. The present invention monitors the temperature of the machining surface and adaptively adjusts the rotation and feed speeds, thereby extending the tool life and improving the machining efficiency.

[0034] 4. The present invention optimizes the key influencing factors in the surface grinding process by extending the Kalman filter, especially in the high-noise and dynamically changing grinding environment, reduces the interference of sensor noise on the control system, integrates multiple sensors to build an anti-disturbance control system, and improves control accuracy and system stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0036] Figure 2 It is a structural schematic diagram of the pneumatic grinding wheel end actuator in the present invention.

[0037] Figure 3 Flowchart of grinding for the present invention.

[0038] Figure 4 This is a system block diagram of the adaptive grinding control of the present invention.

[0039] Figure 5 System block diagram of the active disturbance rejection controller used in the adaptive grinding control of the present invention. DETAILED DESCRIPTION

[0040] The present invention is further described below in conjunction with the accompanying drawings.

[0041] like Figure 1 As shown, a pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback includes a mechanical arm 2 and a pneumatic grinding wheel end actuator 1 installed at the end of the mechanical arm 2.

[0042] like Figure 2As shown, the pneumatic grinding wheel end actuator 1 includes a pneumatic grinding wheel grinding head 1-1, an infrared temperature sensor 1-2, a pressure regulating interface 1-3, a six-dimensional force sensor 1-4, a drive motor 1-5, an inertial sensor and a sealed housing 1-6. The base of the six-dimensional force sensor is fixedly connected to the end of the robot arm through a flange; the main body of the drive motor is connected to the detection part of the six-dimensional force sensor through a flange; the sealed housing 1-6 is fixed on the main body of the drive motor. The inertial sensor is fixed on the sealed housing 1-6.

[0043] A rotating body-shaped inner cavity is provided in the sealed shell 1-6; the inner cavity of the sealed shell 1-6 coincides with the axis of the output shaft of the driving motor 1-5. A pressure regulating interface 1-3 is provided on the sealed shell 1-6. The pneumatic grinding wheel grinding head 1-1 is coaxially rotatably connected to the outer end of the sealed shell 1-6. The inner end of the pneumatic grinding wheel grinding head 1-1 is coaxially fixed with the output shaft of the driving motor 1-5 in the inner cavity of the sealed shell 1-6. The pneumatic grinding wheel grinding head 1-1 includes a wrapping layer, a granular filler in the wrapping layer, and abrasive particles attached to the outer surface of the wrapping layer, and the rigidity of the pneumatic grinding wheel grinding head 1-1 is changed by adjusting the internal pressure of the wrapping layer.

[0044] The interior of the pneumatic grinding wheel grinding head 1-1 is connected to the pressure regulating interface 1-3 through a slip ring flow channel. The pressure regulating interface 1-3 is connected to an external air source or a negative pressure source, so as to adjust the internal pressure of the rotating pneumatic grinding wheel grinding head 1-1, thereby changing the stiffness of the pneumatic grinding wheel grinding head 1-1.

[0045] Due to the complex grinding curved surface of the blade, this embodiment uses a hemispherical pneumatic grinding wheel grinding head 1-1 with attached soft consolidated abrasive for grinding. At the same time, since the distribution of grinding speed has an important influence on the processing effect and surface quality during the grinding process. Since the pneumatic grinding wheel grinding head 1-1 is hemispherical, it is necessary to make the pneumatic grinding wheel and the grinding surface form a certain angle to ensure that the force and speed distribution in the processing area are more uniform. It can be seen that the essence of grinding control in this embodiment is to ensure that the pressure and processing angle during the surface grinding process are within the error range.

[0046] like Figure 3 and Figure 4 As shown, the control method of the pneumatic grinding wheel blade adaptive grinding device includes the following steps:

[0047] Step 1: Establish the discrete time state equation of the state vector of the pneumatic grinding wheel grinding head 1-1 as follows:

[0048] X(k)=f(X(k-1))+w(k-1)

[0049] Among them, X(k-1) and X(k) are the state vectors of the previous iteration and the current moment; is the error vector.

[0050] In this embodiment, the state vector X is as follows:

[0051] X=[xv F s F E Mz θ] T

[0052] Wherein, x is the mass center position of the pneumatic grinding wheel grinding head 1-1; v is the mass center speed of the pneumatic grinding wheel grinding head 1-1; F S is the force measured by the six-dimensional force sensor; F E is the force applied to the pneumatic grinding wheel grinding head 1-1; θ is the angle between the normal line of the machining surface and the axis of the pneumatic grinding wheel grinding head 1-1; Mz is the torque around the z-axis applied to the six-dimensional force sensor.

[0053] f(·) is the nonlinear discrete-time state transfer matrix, which is expressed as follows:

[0054]

[0055] Wherein, T is the sampling time; m is the mass of the pneumatic grinding wheel end actuator 1;

[0056] w(k-1) is the noise vector, and its expression is:

[0057]

[0058] in, w θ (k-1), w θ (k-1) are the process noises of the four state parameters. All the four process noises obey the normal distribution.

[0059] Step 2: Initialize the force measured by the six-dimensional force sensor 1-4. When the pneumatic grinding wheel grinding head 1-1 contacts the surface to be processed, set the initial value of the state vector And the initial error covariance matrix P 0 The axis of the pneumatic grinding wheel grinding head 1-1 is controlled to reach a desired angle with the tangent plane of the processed position. In this embodiment, the desired angle is 20°.

[0060] Step 3: Predict the prior estimate of the current state vector through the state transition equation and the prior covariance matrix

[0061] Prior covariance matrix The expression is as follows:

[0062]

[0063] Step 4: Calculate the Kalman gain K k , the expression is as follows:

[0064]

[0065] Where H is the Jacobian matrix for the state vector X; R k is the matrix covariance.

[0066] Correcting the state vector estimate by the Kalman gain and covariance P k as follows:

[0067]

[0068]

[0069] Among them, Z(k) is the observation vector, and its value is detected by inertial sensors and six-dimensional force sensors.

[0070] The expression of the observation vector Z(k) is:

[0071] Z(k)=[xv F s F E M z θ] T

[0072] The observation vector Z(k) and the state vector X(k) satisfy the following relationship:

[0073] Z(k)=HX(k)+V(k)

[0074] Among them, V(k)~N(0,R k ), is the observation noise vector; HX(k) is the observation function obtained after the observation noise vector eliminates the noise.

[0075] The expression of the observation function HX(k) is:

[0076]

[0077] Step 5: Transmit the grinding force to the subsequent ADRC controller. Since the grinding force has a greater impact on the grinding quality than the grinding speed distribution, and the ADRC of the grinding angle is relatively complex, which will reduce the robustness of the system, only the magnitude of the grinding force is considered in the ADRC, that is, the internal air pressure of the grinding wheel is controlled. The overall control method is as follows:

[0078] If only the anti-disturbance control of grinding force is considered, the system can be simplified to a second-order system. The system state includes the current grinding force F E (k) and grinding force change rate F′ E (k). Grinding force FE (k) is the estimated value of the state vector obtained by the extended Kalman filter above

[0079] like Figure 5 As shown, the active disturbance rejection controller includes a tracking differentiator (TD), an extended state observer (ESO) and a nonlinear state error feedback (NLSEF). Figure 5 In the figure, v is the expected grinding force of the system; v 1 To track the grinding force; v 2 To track the grinding force change rate; e 1 and e 2 are the error signals of grinding force and grinding force change rate respectively; u 0 is the output control signal; w(t) is the external disturbance; b is the compensation coefficient; z 1 To observe the grinding force; 2 is the observed acceleration; z 3 The actual grinding force is transmitted from the extended Kalman filter data to the extended state observer output z 1 、z 2 、z 3 .

[0080] The current grinding force F E (k) Input the extended state observer ESO. The error between the observed grinding force output by the extended state observer and the expected grinding force is input into the nonlinear state error feedback device. The nonlinear state error feedback device outputs a control signal to control the pneumatic grinding wheel after compensation.

[0081] The desired grinding force is input through the tracking differentiator, where the discrete form of the tracking differentiator is:

[0082] F E (k+1)=F E (k)+T′F′ E (k)

[0083] F′ E (k+1)=F′ E (k)+Tfst(F E (k)-F Ed ,F′ E (k),r,T)

[0084] Where T' is the integration step; r is the speed factor; F Ed is the expected grinding force, fst(·) is the most nonlinear weighted sum function, and is also the main component of the nonlinear state error feedback, which is described as follows:

[0085]

[0086] Where, d = rT'; d 0 =Td;y=F E +TF' E ; F d is the desired grinding force; r is the speed factor; h is the filter factor; d is the differentiator gain.

[0087] Step 6: Iteration number k = k + 1, re-execute steps 3 and 4 to achieve the estimated value of the state vector The grinding force after each filtering is iteratively updated and passed to the subsequent ADRC.

Claims

1. A pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback, comprising a mechanical arm (2), and a pneumatic grinding wheel end actuator (1) installed at the end of the mechanical arm (2); characterized in that: The pneumatic grinding wheel end actuator (1) comprises a pneumatic grinding wheel grinding head (1-1), a pressure regulating interface (1-3), a six-dimensional force sensor (1-4), a driving motor (1-5) and a sealed housing (1-6); The sealed housing (1-6) is provided with a pressure regulating interface (1-3); the pneumatic grinding wheel grinding head (1-1) is rotatably connected to the outer end of the sealed housing (1-6); the inner cavity of the pneumatic grinding wheel grinding head (1-1) is connected to the pressure regulating interface (1-3) on the sealed housing (1-6) through a flow channel; the driving motor (1-5) is used to drive the pneumatic grinding wheel grinding head (1-1) to rotate; the six-dimensional force sensor (1-4) is used to detect the grinding force of the pneumatic grinding wheel grinding head (1-1); and the pressure regulating interface (1-3) is used to adjust the internal pressure of the pneumatic grinding wheel grinding head (1-1).

2. The pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback according to claim 1 is characterized in that: The pneumatic grinding wheel grinding head (1-1) comprises a wrapping layer, granular fillers in the wrapping layer, and abrasive grains attached to the outer surface of the wrapping layer. The rigidity of the pneumatic grinding wheel grinding head (1-1) is changed by adjusting the internal pressure of the wrapping layer.

3. The pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback according to claim 1 is characterized in that: The base of the six-dimensional force sensor is fixed to the end of the mechanical arm; the housing of the driving motor is installed on the detection part; The sealed housing (1-6) and the housing of the driving motor.

4. The pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback according to claim 1 is characterized in that: A rotating body-shaped inner cavity is provided in the sealing shell (1-6); the inner cavity of the sealing shell (1-6) coincides with the axis of the output shaft of the driving motor (1-5); The inner end of the pneumatic grinding wheel grinding head (1-1) and the output shaft of the driving motor (1-5) are coaxially fixed in the inner cavity of the sealed housing (1-6).

5. The pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback according to claim 1, characterized in that: It also comprises an inertial sensor which is fixed on the sealed housing (1-6) and is used to detect the acceleration of the pneumatic grinding wheel grinding head (1-1).

6. The pneumatic grinding wheel blade adaptive grinding device based on multi-sensor feedback according to claim 1, characterized in that: It also comprises an infrared temperature sensor (1-2); the infrared temperature sensor (1-2) is installed at the end of the sealed housing (1-6).

7. An adaptive control method for pneumatic grinding wheel blade grinding based on multi-sensor feedback, characterized in that: Used to control the pneumatic grinding wheel blade adaptive grinding device as claimed in claim 1; the pneumatic grinding wheel blade adaptive grinding control method comprises the following steps: Step 1: Predict the prior estimate of the current state vector through the state transfer equation and the prior covariance matrix Step 2: Calculate the Kalman gain K k ; Correct the prior estimate by Kalman gain Get the state vector estimate and covariance P k ; Step 3: Estimate the value based on the state vector The position and internal pressure of the pneumatic grinding wheel grinding head (1-1) are controlled with the expected value of the state vector.

8. The method for adaptive control of pneumatic grinding wheel blade grinding based on multi-sensor feedback according to claim 7, characterized in that: The Kalman gain K k The expression is as follows: Where H is the Jacobian matrix for the state vector; R k is the matrix covariance.

9. The method for adaptive control of pneumatic grinding wheel blade grinding based on multi-sensor feedback according to claim 7, characterized in that: The state vector estimate and covariance P k The expression is as follows: Among them, Z(k) is the observation vector.

10. The method for adaptive control of pneumatic grinding wheel blade grinding based on multi-sensor feedback according to claim 7, characterized in that: The state vector estimate Including grinding force F E (k); grinding force F E (k) inputting an active disturbance rejection controller; the active disturbance rejection controller comprises a tracking differentiator, an extended state observer and a nonlinear state error feedback; The discrete form of the tracking differentiator is: F E (k+1)=F E (k)+T′F E ′(k) F E ′(k+1)=F E ′(k)+Tfst(F E (k)-F Ed ,F E ′(k),r,T) Among them, F E (k), F E (k+1) are the grinding forces at the current moment and the next moment respectively; F E ′(k), F E ′(k+1) is the grinding force change rate between the current moment and the next moment; T' is the integration step; r is the speed factor; F Ed is the expected grinding force, and fst(·) is the most nonlinear weighted sum function.

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