Method for analyzing machinability of laser metal deposition layer based on vibration analysis

Abstract

The invention relates to the technical field of machining and vibration analysis, and discloses a laser metal deposition layer machinability analysis method based on vibration analysis. According to the method, a vibration acceleration signal in the cutting process is collected through an acceleration sensor installed on a machine tool machining platform, a time domain signal is converted into a frequency domain signal in combination with fast Fourier transform, and a cutting vibration resistance index of a sedimentary layer is quantified based on a root mean square value (RMS) algorithm of the vibration acceleration. And non-destructive on-line evaluation of the machinability of the laser metal deposition layer is realized by analyzing the correlation between the vibration spectrum characteristics and the deposition layer microdefects. The method solves the problems of low efficiency and insufficient dynamic characteristic characterization of traditional destructive detection, significantly improves the optimization efficiency of process parameters and the cutting adaptability of the complex deposited layer, and has the characteristics of low test cost and simplicity and convenience in operation.

Description

Technical Field

[0001] The present invention relates to the technical fields of machining and vibration analysis, and particularly to a method for analyzing the machinability of a laser metal deposition layer based on vibration analysis. Background Art

[0002] Laser metal deposition is an additive manufacturing technology that melts metal powder or wire layer by layer through a high-energy laser beam, and is widely used in the repair of complex parts and the manufacture of high-performance components in the fields of aerospace and energy equipment. However, the metal deposition layer formed by laser metal deposition usually has problems such as uneven microstructure, large residual stress, and high surface roughness, resulting in increased tool wear and unstable machining surface quality during subsequent machining (such as turning, milling), and even may cause machining defects such as vibration chatter. Therefore, how to quickly and accurately evaluate the machinability of the laser metal deposition layer has become a key challenge for improving the efficiency of additive-subtractive hybrid manufacturing.

[0003] Traditional methods mainly rely on empirical trial cutting or destructive testing (such as hardness testing, metallographic analysis), which have the defects of low efficiency, high cost, and inability to provide real-time feedback on the cutting state. Due to the problems of residual stress and uneven microstructure caused by rapid solidification in the laser metal deposition layer, traditional inspections (such as metallography, hardness) are difficult to provide real-time feedback on cutting adaptability. Therefore, there is a lack of quantitative evaluation methods for the connection between the laser metal deposition layer and cutting machining.

[0004] In summary, the following problems exist in the evaluation of the machinability of the laser metal deposition layer:

[0005] 1. Limitations of existing technologies relying on destructive testing: Traditional methods (such as metallographic sectioning, hardness testing) require physical destruction sampling of the deposition layer, resulting in material waste and inability to guide the adjustment of machining parameters in real time, especially with extremely low applicability to complex curved surfaces or thin-walled structural parts;

[0006] 2. Insufficient characterization of the dynamic characteristics during the cutting process: Existing research mostly predicts cutting performance based on static mechanical property parameters (such as tensile strength, elongation), but ignores the sudden changes in cutting vibration (high-frequency chatter, instantaneous load fluctuations) caused by heterogeneous structures (such as alternating distribution of columnar crystals / equiaxed crystals) in the LMD layer, resulting in too high prediction errors and easy occurrence of tool edge chipping or surface tearing during actual machining;

[0007] 3. Inefficient optimization of process parameters: The traditional trial-and-error method needs to compare the results such as chip morphology and tool wear amount through multiple rounds of cutting tests. Each single test takes a long time, and it is difficult to quantify the mapping relationship between vibration signals and machining quality, resulting in an extended process development cycle;

[0008] 4. Lack of adaptability in cutting complex deposition layers: The existing technologies lack targeted analysis of the cutting vibration characteristics of special structures such as gradient materials and multi-pass overlapping areas in laser metal deposition, resulting in poor universality of processing parameters and affecting the consistency of batch manufacturing.

[0009] Therefore, the present invention proposes an analysis method for the machinability of laser metal deposition layers based on vibration analysis to solve the above technical problems. Summary of the Invention

[0010] To solve the above technical problems, the present invention provides an analysis method for the machinability of laser metal deposition layers based on vibration analysis. This method uses vibration analysis technology to establish a quantitative relationship between vibration intensity and the machinability of the deposition layer by utilizing the spectral characteristics of dynamic signals during the cutting process, thereby solving the limitations of traditional methods.

[0011] The analysis method for the machinability of laser metal deposition layers based on vibration analysis provided by the present invention includes the following steps:

[0012] Step 1: Install an acceleration sensor on the machine tool processing platform to obtain the vibration acceleration signal v(n) of the machine tool bed.

[0013] The processing parameters adopted during the cutting process are as follows: The spindle speed of the milling machine is set at 800 to 2000 r / min, the feed per tooth is set at 0.03 to 0.1 mm, the cutting speed is set at 60 to 120 m / min, and the diameter of the milling cutter is 2 to 6 mm. During the milling process, it can be considered that the vibration intensity of the system is proportional to the effective value of the maximum vibration acceleration. Since the vibration intensity can be used to evaluate the quality of the system vibration state during the milling process with reference to the vibration standard; therefore, when measuring the vibration on the machine work platform, the effective value of the vibration acceleration can be measured, and it is measured in three directions: horizontal, vertical, and axial near the cutting position, and finally the maximum value is taken as the vibration intensity.

[0014] Step 2: Perform a fast Fourier transform on the acceleration signal obtained in Step 1 to convert the time-domain signal v(n) obtained by the sensor into a frequency-domain signal v(f).

[0015] Step 3: The actual measurement value of the vibration intensity in the present invention uses the root mean square value (RMS) of the vibration acceleration. Its expression is as shown in Formula 1:

[0016]

[0017] In the formula: N represents the length of the measured signal; v(f) represents the vibration acceleration of the object.

[0018] Substitute the vibration signal after the fast Fourier transform into Formula (1) to calculate the root mean square value (RMS) of the vibration acceleration of the vibration signal.

[0019] Based on the data obtained from the above steps, on the MATLAB software, the vibration spectrum during the deposition layer processing and the maximum RMS values in the three directions of horizontal, vertical, and axial are obtained based on the following algorithm. The RMS extreme value of the processed sample is greater than 0.1 mm / s 2 , the more uneven the vibration spectrum, the greater the vibration of the processing system during cutting, and the worse the machining performance of the deposition layer surface. On the contrary, the machining performance is better.

[0020] The relevant algorithm is as follows:

[0021] clear all;

[0022] close all;

[0023] clc;

[0024] DD = load('1.txt');

[0025] x = DD(:,1);

[0026] fs = 10;

[0027] M = 800;

[0028] N = 20;

[0029] df = fs / N;

[0030] T = length(x) / fs;

[0031] OVER = (M-length(x) / N) / (M-1);

[0032] w = flattopwin(N);

[0033] W = sum(w);

[0034] for i = 1:M

[0035] a = 1+(i-1)*N*(1-OVER);

[0036] t(i) = fix(a+(N-1) / 2) / length(x)*T;

[0037] x1 = x(fix(a):fix(N-1+a));

[0038] y1 = fft(x1.*w,N);

[0039] y = 2*abs(y1 / W).*abs(y1 / W);

[0040] RMS(i,:) = sqrt(y);

[0041] end

[0042] f1 = df:df:fs;

[0043] EE = 10 / fs * N;

[0044] f = f1(1:EE);

[0045] RMSC = RMS(:,1:EE);

[0046] waterfall(f,t,RMSC);

[0047] max(max(RMSC))

[0048] zlim([0 max(max(RMSC))])

[0049] ylim([0 max(t)])

[0050] xlabel('Frequency[Hz]')

[0051] ylabel('Time[s]')

[0052] zlabel('RMS[mm / s^2]')

[0053] Compared with the related technologies, the method for analyzing the machinability of a laser metal deposition layer based on vibration analysis provided by the present invention has the following beneficial effects:

[0054] 1. Non-destructive on-line evaluation: By using the vibration acceleration signals collected during the cutting process and combining with vibration analysis algorithms, the cutting vibration resistance indexes (such as vibration energy density) of the laser metal deposition layer are quantified, and the surface quality of the deposition layer can be evaluated without damaging the workpiece;

[0055] 2. Dynamic cutting mechanism analysis: Establish the correlation between the vibration spectrum characteristics and the microscopic defects of the LMD layer, and reveal the dynamic failure mechanism of the deposition layer under the cutting load. Brief Description of the Drawings

[0056] Figure 1 The following figure is a schematic diagram of the installation positions of the milling machine processing system and the acceleration sensor in the present invention;

[0057] Figure 2 It is the cutting vibration spectrogram of the deposition layer: (a) Coating A; (b) Coating B; (c) Coating C; (d) Coating D.

[0058] Reference numerals: 1. Milling machine processing platform; 2. Substrate part of the deposition layer; 3. Deposition layer; 4. Acceleration sensor; 5. Milling cutter. Detailed implementation mode

[0059] The present invention will be further described below in conjunction with the accompanying drawings and the implementation mode.

[0060] During the milling process of the laser metal deposition layer, due to the extrusion and friction of the tool on the machining surface, large plastic deformation is generated. In addition, due to the tearing effect when the tool forces the chip to separate from the workpiece, the surface roughness value increases. Generally speaking, the greater the tendency of material plastic deformation, the greater the surface roughness of the machined surface. Whether it is the introduction of external vibration, the vibration of internal moving parts of the machine tool, or the cutting vibration generated by the mechanical system under certain specific conditions, it will seriously deteriorate the surface roughness of the workpiece.

[0061] Taking the vibration analysis of the milling process of a certain laser metal deposition layer as an example, the present invention monitors and analyzes the cutting process based on the vibration signal of the machine tool bed during the milling process.

[0062] A method for analyzing the machinability of a laser metal deposition layer based on vibration analysis proposed by the present invention includes the following steps:

[0063] Step 1: Install an acceleration sensor on the machine tool processing platform to obtain the vibration acceleration signal v(n) of the machine tool bed.

[0064] In this embodiment, 4 different deposition layers are cut, and are respectively named deposition layer A (FeCoNi alloy), B (FeCoNiTi alloy), C (FeCoNiCrTiMn alloy) and D (FeCoNiCrTiAl alloy).

[0065] The machining parameters adopted during the cutting process are as follows: the spindle speed of the milling machine is set at 1000 r / min, the feed per tooth is set at 0.05 mm, the cutting speed is set at 100 m / min, and the diameter of the milling cutter is 4 mm. The cutting process and the installation position of the sensor are as Figure 1 shown. Measurements are carried out in the horizontal, vertical, and axial directions near the cutting position to obtain vibration signal data.

[0066] Step 2: Perform a fast Fourier transform on the acceleration signal obtained in Step 1 to convert the time-domain signal v(n) obtained by the sensor into a frequency-domain signal v(f).

[0067] Step 3: The actual measurement value of the vibration intensity in the present invention uses the root mean square value (RMS) of the vibration acceleration. Its expression is as shown in Formula 1:

[0068]

[0069] Where: N represents the length of the measured signal; v(f) represents the vibration acceleration of the object.

[0070] Substitute the vibration signal after fast Fourier transform into formula (1) to calculate the root mean square value (RMS) of the vibration acceleration of the vibration signal.

[0071] Based on the data obtained from the above steps, on the MATLAB software, the vibration spectra and RMS values in the horizontal, vertical, and axial directions during the deposition layer processing are obtained based on the following algorithm. Take the maximum RMS values in the horizontal, vertical, and axial directions as the effective RMS values, and obtain the corresponding vibration spectra. The larger the RMS extreme value of the processed sample, the more uneven the vibration spectrum, indicating that the vibration of the processing system during cutting is greater and the processing performance of the deposition layer surface is poorer. On the contrary, the processing performance is better.

[0072] The related algorithm is as follows:

[0073] clear all;

[0074] close all;

[0075] clc;

[0076] DD = load('1.txt'); % Raw data

[0077] x = DD(:,1); % Acceleration data in the Z direction

[0078] fs = 10; % Sampling frequency

[0079] M = 800; % Number of data points for the spectrum

[0080] N = 20; % Value taken for fast Fourier transform

[0081] df = fs / N;

[0082] T = length(x) / fs;

[0083] OVER = (M - length(x) / N) / (M - 1);

[0084] w = flattopwin(N);

[0085] W = sum(w);

[0086] for i = 1:M

[0087] a = 1 + (i - 1) * N * (1 - OVER);

[0088] t(i) = fix(a + (N - 1) / 2) / length(x) * T;

[0089] x1 = x(fix(a):fix(N - 1 + a));

[0090] y1 = fft(x1.*w, N);

[0091] y = 2 * abs(y1 / W).*abs(y1 / W);

[0092] RMS(i, :) = sqrt(y);

[0093] end

[0094] f1 = df:df:fs;

[0095] EE = 10 / fs * N;

[0096] f = f1(1:EE);

[0097] RMSC = RMS(:, 1:EE);

[0098] waterfall(f, t, RMSC);

[0099] zlim([0 max(max(RMSC))])

[0100] ylim([0 max(t)])

[0101] xlabel('Frequency[Hz]')

[0102] ylabel('Time[s]')

[0103] zlabel('RMS[mm / s^2]')

[0104] The maximum RMS values of the A, B, C, and D deposition layers obtained through the above steps are 0.3366 mm / s 2 , 0.4238 mm / s 2 , 0.09149 mm / s 2 , and 0.4571 mm / s 2 . The results show that the RMS extreme value of the C deposition layer is less than 0.1 mm / s 2 . At the same time, the corresponding vibration spectrogram of the deposition layer during the cutting process can also be obtained through the above steps. As Figure 2 shown, the energy spectrum results show that the smaller the RMS extreme value, the more uniform the vibration distribution, the gentler the vibration, and the better the machinability of the deposition layer.

[0105] To verify the rationality of this method in evaluating the machinability of laser deposition layers, roughness tests were conducted on the surfaces of the deposited layers after cutting. The surface roughness values of deposited layers A, B, C, and D after cutting were 1.85 μm, 1.93 μm, 1.01 μm, and 1.96 μm, respectively. Figure 2 Figure 2 shows the vibration characteristics during the coating machining process. It can be seen that the vibration RMS of coating D is relatively concentrated, with the highest vibration intensity. The vibration distribution of coating C is more dispersed, and the RMS value is the smallest. This indicates that this coating is more likely to disperse the cutting force during cutting, thus ensuring good surface machining quality. This trend is consistent with the surface roughness values of the deposited layers after cutting.

[0106] The above are only embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A method for analyzing the machinability of laser metal deposition layers based on vibration analysis, characterized in that: The following steps are involved: S1. Install an acceleration sensor on the machine tool processing platform to obtain the vibration acceleration signal of the bed during the cutting process; S2, converting the vibration acceleration signal into a frequency domain signal by fast Fourier transform; S3. Based on the root mean square (RMS) algorithm of vibration acceleration, the vibration intensity index is calculated, and the correlation between the vibration spectrum characteristics and the cutting performance of the deposited layer is analyzed.

2. The laser metal deposition layer machinability analysis method based on vibration analysis according to claim 1, characterized in that: In the step S1, the acceleration sensor is installed near the cutting position to measure in the horizontal, vertical and axial directions, and the maximum RMS value in the three directions is taken as the vibration severity evaluation index.

3. The laser metal deposition layer machinability analysis method based on vibration analysis according to claim 1, characterized in that: In step S1, the milling processing parameters are: spindle speed 800-2000 r / min, feed per blade 0.03-0.1 mm, cutting speed 60-120 m / min, and milling cutter diameter 2-6 mm.

4. The laser metal deposition layer machinability analysis method based on vibration analysis according to claim 1, characterized in that: In step S3, the calculation expression of the vibration severity is: Where N is the length of the measured signal, v(f) represents the vibration acceleration of the object, and is a frequency domain vibration acceleration signal.

5. The laser metal deposition layer machinability analysis method based on vibration analysis according to claim 1, characterized in that: The step S3 also includes: analyzing the vibration energy distribution through the vibration spectrum, if the RMS extreme value is greater than 0.1 mm / s 2 , it is judged that the cutting performance of the deposited layer surface is poor; otherwise, it is judged that the cutting performance is good.

6. The laser metal deposition layer machinability analysis method based on vibration analysis according to claim 1, characterized in that: The method further includes: performing spectrum analysis on the vibration signal based on MATLAB software to generate a vibration spectrum to visualize the distribution of vibration energy over time.

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