A method for identifying the damping coefficient of nonlinear process in titanium alloy

Abstract

The present invention belongs to the technical field related to metal manufacturing and process, and discloses a method for identifying the damping coefficient of a titanium alloy nonlinear process. The method comprises the following steps: S1 constructs a damping solution model of a titanium alloy workpiece in a low-speed nonlinear machining process, and solves the modal parameters and frequency response functions of the tool and the titanium alloy workpiece; S2 constructs a cutting stability boundary lobe diagram of the titanium alloy workpiece, determines the stability boundary finite amplitude machining parameters, and obtains the finite amplitude corresponding to the machining parameters; S3 selects the initial value of the immersion coefficient of the titanium alloy workpiece, and uses the finite amplitude corresponding to the machining parameters to iteratively solve the immersion coefficient of the titanium alloy workpiece, and substitutes the immersion coefficient and the finite amplitude into the damping solution model to solve and obtain the required damping coefficient, thereby realizing the identification of the damping coefficient of the titanium alloy nonlinear process. Through the present invention, the problem of complex damping coefficient solution and low precision is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field related to metal manufacturing and technology, and more specifically, relates to a method for identifying the damping coefficient of a titanium alloy nonlinear process. Background Art

[0002] With the development needs of aviation, aerospace and national key manufacturing fields, titanium alloys, a type of material with excellent performance, are widely used, especially in the processing and manufacturing of key parts such as aircraft engines. However, due to the difficult-to-cut characteristics of titanium alloys, such as poor thermal conductivity, small elastic modulus, severe work hardening, and large cutting force per unit area, chatter and tool wear are prone to occur during the processing of titanium alloys, which will lead to problems such as low processing efficiency and poor precision. In the process of processing core parts with complex shapes and thin walls in aircraft engines, in order to reduce the adverse effects of chatter problems, the spindle speed is usually reduced. In the low-speed processing process, process damping will have an important impact on the cutting dynamics and chatter stability of titanium alloys. Therefore, the rapid identification of the process damping coefficient in the nonlinear process damping model is of great significance.

[0003] Since the cutting state mechanism caused by process damping is complex, it is difficult to establish an accurate analytical model of process damping. In current research, in order to solve the nonlinear process damping coefficient, it is usually necessary to design complex and time-consuming experiments, which requires expensive testing equipment and has extremely high requirements for the precise acquisition of the stability boundary in the experimental test, making the measurement difficult. Summary of the invention

[0004] In view of the above defects or improvement needs of the prior art, the present invention provides a method for identifying the damping coefficient of a titanium alloy nonlinear process, which solves the problem that the damping coefficient is complex and has low precision.

[0005] To achieve the above object, according to the present invention, a method for identifying the damping coefficient of a titanium alloy nonlinear process is provided, the method comprising the following steps:

[0006] S1 builds a damping solution model for titanium alloy workpieces during low-speed nonlinear machining, and conducts hammer tests on the tool and titanium alloy workpiece to solve the modal parameters and frequency response functions of the tool and titanium alloy workpiece;

[0007] S2 uses the obtained modal parameters of the tool to construct a cutting stability boundary lobe diagram for the titanium alloy workpiece, determines the stability boundary finite amplitude machining parameters from the lobe diagram, and measures the vibration amount of the tool end along the radial direction of the titanium alloy workpiece under the finite amplitude machining parameters, so as to obtain the finite amplitude A corresponding to the machining parameters. m ;

[0008] S3 selects the initial value of the immersion coefficient of the titanium alloy workpiece, and uses the finite amplitude A corresponding to the processing parameters m Iterative solution to obtain the immersion coefficient k of titanium alloy workpiece d , the immersion coefficient k d and finite amplitude A m Substitute into the damping solution model to obtain the required damping coefficient c p , so as to realize the identification of the damping coefficient of the nonlinear process of titanium alloy.

[0009] Further preferably, in step S1, the damping solution model is performed according to the following relationship:

[0010]

[0011] Among them, c p represents the process damping coefficient, k d represents the immersion force coefficient, A m represents the finite amplitude value and I represents the immersed volume.

[0012] Further preferably, the immersion volume I is carried out according to the following relationship:

[0013]

[0014] Among them, f c represents the tool modal frequency; t represents the time; U(t) represents the immersion area at time t.

[0015] Further preferably, the immersion area U(t) at time t is calculated according to the following relationship:

[0016]

[0017] Among them, U1(t) and U2(t) represent the two components of the immersed area U(t) at time t.

[0018] Further preferably, U1(t) and U2(t) are respectively performed according to the following relationship:

[0019]

[0020]

[0021] Among them, V l represents the linear speed of the tool; L represents the wavelength of the workpiece surface fluctuation; X c represents the coordinates of the contact point where the tool cuts into the workpiece; W represents the width of the wear zone on the tool back face; γ represents the tool back angle; s represents the arc length.

[0022] Further preferably, the tool linear speed V lThe relationship between the wavelength L of the workpiece surface fluctuation is as follows:

[0023] V l =ΩπD / 60

[0024] L=V l / f c

[0025] Among them, Ω represents the spindle speed and D represents the tool diameter.

[0026] Further preferably, in step S2, the stability boundary lobe map is acquired by using a full discrete method.

[0027] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0028] 1. The present invention adopts a hybrid form of experimental and theoretical models, designs experiments to realize the limited amplitude working condition of cutting processing, and measures the limited amplitude experimental value under this working condition. Combined with the tool vibration modal frequency obtained by modal analysis, the immersion force coefficient in the process damping model is iteratively solved, and then the process damping theoretical modeling knowledge is integrated to realize the rapid identification of the nonlinear process damping coefficient.

[0029] 2. The damping coefficient identification method provided by the present invention does not require the design of complex and time-consuming experiments, does not require expensive testing equipment, and does not have extremely high requirements for the accurate acquisition of the stability boundary in the experimental test. The measurement difficulty is small and the measurement results are accurate;

[0030] 3. Based on the process damping identification method proposed in the present invention, it is helpful to improve the cutting stability model of titanium alloy workpieces. According to the stability model boundary considering process damping, the influence of the tool axis vector on the material removal rate is analyzed to guide the actual processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of a method for identifying the damping coefficient of a titanium alloy nonlinear process constructed according to a preferred embodiment of the present invention;

[0032] Figure 2 It is a scene diagram of the frequency response of the tool end measured by the hammering method constructed according to the preferred embodiment of the present invention;

[0033] Figure 3 It is a hammering method for measuring the frequency response of titanium alloy workpiece end and a scene diagram of M+P and PC end real-time signal acquisition constructed according to the preferred embodiment of the present invention;

[0034] Figure 4 is a comparison diagram of the frequency response functions of the tool and the workpiece end constructed according to the preferred embodiment of the present invention;

[0035] Figure 5 is a titanium alloy cutting stability boundary lobe diagram constructed according to a preferred embodiment of the present invention;

[0036] Figure 6 It is a scene diagram of the vibration displacement test of the cutting processing experiment constructed according to the preferred embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0038] The present invention proposes a method for identifying the damping coefficient of a nonlinear process of a titanium alloy. In the field of aerospace high-performance manufacturing and processing, titanium alloys are often used in the manufacture of key parts such as aeroengines. However, due to the poor cutting performance of titanium alloys, it is very easy to cause chatter and tool wear during the processing process, and it is impossible to ensure that the processed parts can obtain good surface quality. Therefore, a lower speed is required in the milling process of titanium alloys. In the low-speed processing of titanium alloys, the process damping effect is an important factor affecting the processing stability, and solving the process damping coefficient is the key to establishing a stability model considering process damping. In current research, in order to solve the nonlinear process damping coefficient, it is usually necessary to design complex and time-consuming experiments, expensive testing equipment is required, and the precise acquisition of the stability boundary in the experimental test has extremely high requirements, and the measurement is difficult. In view of the problems existing in the solution of the nonlinear process damping coefficient in the low-speed processing of titanium alloys, this patent proposes a method for identifying the nonlinear process damping coefficient of a titanium alloy based on a finite amplitude stable region, and obtains the finite amplitude stability region through experiments to achieve rapid identification of the nonlinear process damping coefficient.

[0039] First, the stability lobe diagram is obtained through hammering test, and the machining parameter combination under finite amplitude is determined; then the finite amplitude A measured by cutting experiment is used to determine the stability lobe diagram. m Iterative solution of immersion coefficient k d ; Finally, the damping coefficient c of the process is realized by solving the immersion area U p The application scenario of this patent is to obtain the machining parameter combination that produces the limited amplitude stable area according to the stability lobe diagram during the low-speed machining of titanium alloy, and to carry out cutting experiments to obtain the limited amplitude A m , solve for the immersion coefficient k d , and then realize the nonlinear process damping coefficient c pIdentification.

[0040] Specifically, Figure 1 As shown, the method comprises the following steps:

[0041] (1) The application object of this patent is titanium alloy, and the application scenario is a low-speed machining process. It is necessary to obtain the machining parameter combination in the limited amplitude region near the machining stability boundary through hammering experiments.

[0042] (2) According to the combination of machining parameters in the finite amplitude region, the finite amplitude is accurately measured by cutting experiments, and the immersion force coefficient is iteratively solved. The nonlinear process damping coefficient is then solved using the solved immersion force coefficient.

[0043] Step (1) further comprises the following steps:

[0044] (1-1) Using a force hammer and an accelerometer, a hammer test is performed on the tool end to measure and obtain the tool modal parameters; a hammer test is then performed on the titanium alloy workpiece end to analyze and compare the frequency response functions of the tool and the titanium alloy workpiece;

[0045] (1-2) Based on the tool modal parameters, the machining stability lobe diagram is drawn using the full discrete method;

[0046] (1-3) According to the machining stability lobe diagram, the machining parameter combination in the limited amplitude region of the cutting experiment is analyzed and determined.

[0047] Step (2) further comprises the following steps:

[0048] (2-1) Through the determined combination of machining parameters under finite amplitude, cutting experiments were carried out. A laser displacement sensor was used to measure the vibration value of the tool end during the machining process, and this was used as the finite amplitude value A for titanium alloy machining. m ;

[0049] (2-2) Setting the initial immersion force coefficient based on experience Combined with the measured finite amplitude value A m , tool modal frequency f c , iteratively solve the immersion force coefficient k in the titanium alloy processing process d .

[0050] (2-3) According to the established process damping coefficient identification model, the immersion force coefficient k d Substitute it and solve the immersion area U during the processing, and finally realize the nonlinear process damping coefficient c of titanium alloy p Identification.

[0051] The present invention will be further described below with reference to specific embodiments.

[0052] 1.1 Establishing the process damping coefficient solution model

[0053]

[0054] Among them, c p represents the process damping coefficient, k d represents the immersion force coefficient, A m Represents the finite amplitude value, I represents the immersed volume, and the specific solution formula is as follows:

[0055]

[0056] Among them, f c represents the tool modal frequency; t represents the time; U(t) represents the immersion area at time t, and its calculation formula is as follows:

[0057]

[0058] Among them, U1(t) and U2(t) represent the two components of the immersed area U(t) at time t, and their expressions are as follows:

[0059]

[0060]

[0061] Among them, V l represents the linear speed of the tool; L represents the wavelength of the workpiece surface fluctuation; X c = represents the coordinates of the contact point where the tool cuts into the workpiece; W represents the width of the wear zone on the tool back face; γ represents the tool back angle; s represents the arc length. Tool linear velocity V l The expressions of the wave wavelength L of the workpiece surface are as follows:

[0062] V l =ΩπD / 60

[0063] L=V l / f c

[0064] Among them, Ω represents the spindle speed and D represents the tool diameter.

[0065] 1.2 Determine the combination of machining parameters in the limited amplitude region near the machining stability boundary

[0066] The hammer method was used, and the tool and workpiece modal measurement equipment M+P was used to hit the tool tip and the titanium alloy workpiece with a hammer, respectively. Figure 2 and Figure 3 As shown in the figure, a personal computer PC is used to collect the response signals of the tool and the titanium alloy workpiece in real time.

[0067] After the hammer test, the frequency response function of the turning tool is obtained, and then the modal parameters of the turning tool can be calculated, where the modal frequency is f c =552.3995Hz. By hammering method, the modal parameters of tool end and workpiece end are solved and the frequency response functions are plotted respectively, such as Figure 4 After comparing the rigidity between the workpiece and the tool, it is found that the rigidity of the workpiece is much greater than that of the tool. Therefore, in actual cutting processing, the vibration displacement caused by the workpiece end can be ignored. Only the vibration value of the tool end needs to be measured and used as the limited amplitude value A. m , so to solve the immersion coefficient k d .

[0068] The full discrete method is used to solve the tool end modal parameters obtained by the hammering method and construct the cutting stability boundary lobe diagram of titanium alloy, as shown in Figure 5 shown.

[0069] according to Figure 5 , select Ω=800rpm as the machining speed under limited amplitude judgment, and the machining parameter combination under the limited amplitude area is determined as follows: spindle speed Ω=800rpm, cutting depth a p =2.5mm, feed rate f t =0.02mm / r.

[0070] 1.3 Obtain finite amplitude, solve immersion force coefficient, and identify nonlinear process damping coefficient

[0071] In the processing parameter combination: spindle speed Ω = 800rpm, cutting depth a p =2.5mm, feed rate f t =0.02mm / r, the vibration of the tool end along the radial direction of the titanium alloy was measured by a KEYENCE laser displacement sensor (composed of an LK-G5001 controller and an LK-H050 laser head).

[0072] like Figure 6 As shown in the figure, after experiments and data processing, the vibration amplitude of the tool end along the radial direction of the titanium alloy is 46μm, so the limited amplitude under this processing condition is A m =46μm. According to literature experience, the initial value of the titanium alloy immersion coefficient is selected as After 306 iterations, the stability eigenvalue reaches the stability boundary, and the iterative solution of the titanium alloy immersion coefficient is k d =3.05×10 13 N / m 3 At this time, the finite amplitude of titanium alloy and the modal frequency of titanium alloy cutting are A m =46μm and f c=552.3995Hz. The model can be further solved by the process damping coefficient to realize the process damping coefficient c in the titanium alloy cutting process. p Rapid identification.

[0073] In summary, by combining the experimental acquisition of finite amplitude with the process damping mechanism model, this patent realizes the rapid identification of the damping coefficient of a titanium alloy nonlinear process.

[0074] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying the damping coefficient of a titanium alloy nonlinear process, characterized in that: The method comprises the following steps: S1 builds a damping solution model for titanium alloy workpieces during low-speed nonlinear machining, and conducts hammer tests on the tool and titanium alloy workpiece to solve the modal parameters and frequency response functions of the tool and titanium alloy workpiece; S2 uses the obtained modal parameters of the tool to construct a cutting stability boundary lobe diagram for the titanium alloy workpiece, determines the stability boundary finite amplitude machining parameters from the lobe diagram, and measures the vibration amount of the tool end along the radial direction of the titanium alloy workpiece under the finite amplitude machining parameters, so as to obtain the finite amplitude A corresponding to the machining parameters. m ; S3 selects the initial value of the immersion coefficient of the titanium alloy workpiece, and uses the finite amplitude A corresponding to the processing parameters m Iterative solution to obtain the immersion coefficient k of titanium alloy workpiece d , the immersion coefficient k d and finite amplitude A m Substitute into the damping solution model to obtain the required damping coefficient c p , so as to realize the identification of the damping coefficient of the nonlinear process of titanium alloy.

2. A titanium alloy nonlinear process damping coefficient identification method as claimed in claim 1, characterized in that: In step S1, the damping solution model is performed according to the following relationship: Among them, c p represents the process damping coefficient, k d represents the immersion force coefficient, A m represents the finite amplitude value and I represents the immersed volume.

3. A titanium alloy nonlinear process damping coefficient identification method as claimed in claim 2, characterized in that: The immersion volume I is carried out according to the following relationship: Among them, f c represents the tool modal frequency; t represents the time; U(t) represents the immersion area at time t.

4. A titanium alloy nonlinear process damping coefficient identification method as claimed in claim 3, characterized in that: The immersion area U(t) at time t is calculated according to the following relationship: Among them, U1(t) and U2(t) represent the two components of the immersed area U(t) at time t.

5. A titanium alloy nonlinear process damping coefficient identification method as claimed in claim 4, characterized in that: The U1(t) and U2(t) are respectively carried out according to the following relations: Among them, V l represents the linear speed of the tool; L represents the wavelength of the workpiece surface fluctuation; X c represents the coordinates of the contact point where the tool cuts into the workpiece; W represents the width of the wear zone on the tool back face; γ represents the tool back angle; s represents the arc length.

6. A titanium alloy nonlinear process damping coefficient identification method as claimed in claim 5, characterized in that: The tool linear speed V l The relationship between the wavelength L of the workpiece surface fluctuation is as follows: V l =ΩπD / 60 L=V l / f c Among them, Ω represents the spindle speed and D represents the tool diameter.

7. A titanium alloy nonlinear process damping coefficient identification method as claimed in claim 1 or 2, characterized in that: In step S2, the stability boundary lobe diagram is obtained by using a full discretization method.

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