Wavelet Analysis of Overcut in NC Machining of Free-form Surfaces

Molds use a large number of CNC machine tools and machining centers in the manufacturing process. The manufacturing cycle is long, and the operator is prone to fatigue. Once the fault occurs, it takes a few seconds from the human perception to the corresponding measures, which may lead to product scrapping. , causing serious economic losses, such as tool damage and machining fault diagnosis in general parts processing, and many other domestic and foreign research reports, most of which focus on acoustic emission, cutting force or vibration monitoring, etc., and have made great progress but complicated processing Molds and other workpieces with free-form surface features, but also lack of effective monitoring technology, the reason is that the over-cut signal is difficult to identify another to provide an effective means for real-time monitoring, this paper uses the current signal processing is a very powerful tool - wavelet analysis, "Focus-type" scanning of different time periods and frequency bands of the original signal to accurately extract the over-cut signal from the time-frequency space. 1 Wavelet analysis concept Wavelet analysis is the development of Fourier analysis. It uses a Xu Shuxin, etc.: Free-form surface NC Over-cut wavelet analysis in processing, elastic wavelet basis function kb t) As an integral transformation function, for different frequencies, according to the expansion and contraction of the scale parameter a, when the high-frequency characteristic is analyzed and detected (a is reduced), the time window is automatically narrowed, and the frequency window is automatically widened; when the low-frequency characteristic is analyzed and detected ( a increase), the time window is automatically widened, the frequency window is automatically narrowed, and the adaptive change of the time-frequency window is realized. For different time periods, the basis function can be slid along the time axis, so that the signal can be analyzed at any time. detail.

2 In the free-form surface machining, the over-cut signal wavelet analysis principle In the NC machining, the intersection of the tool end face and the workpiece surface is called overcutting. It belongs to abnormal cutting. When the workpiece free surface is overcut, the cutting force suddenly changes, resulting in The cutting power changes, and the motor current that drives the tool will also change accordingly. Therefore, monitoring the motor current as a function of the cutting force can indirectly monitor the tool state to extract the current signal from the spindle motor. The simplest method is series resistance for I/. U conversion, output in the form of voltage, but the addition of the resistor changes the load characteristics of the motor itself, reducing the accuracy of the measurement. In addition, other instruments connected at both ends of the resistor must be equivalently transformed to suspend their potential, which undoubtedly increases the complexity of the measurement system. In view of this, this paper uses a magnetic balanced Hall current sensor. The sensor itself is connected to a DC power supply. A magnetic field is generated inside the Hall element. When the current input is connected to the sensor, current is generated at the output. It generates a balanced magnetic field inside the Hall element. If the motor current changes, the balanced magnetic field is affected. To the destruction, to achieve a new balance, the output current must be changed accordingly. Since the input and output of the Hall element have a good linear relationship, the fluctuation of the output signal can indirectly reflect the change of the motor current. For f(t), the continuous wavelet transform of f(t) can be defined as the multi-resolution approximation of the inner product of f(t) and ,)), and the corresponding scale function is 1, so the basis function of V/space should also be located. In the V/+i space, the normalized orthogonal basis of the V/+i space can be used to represent the approximation of 1 and 2', respectively, which is its orthogonal projection at V/+i and V/, according to the projection. The detail signal with a resolution of 2' should be the orthogonal projection of the original signal on the orthogonal complement space of V/V+1. Let the orthogonal complement space be W/, that is, the basis function of W/space 2 /(x-2/n) should also be in the V/+i space, so it can also be represented by the canonical orthogonal basis (5) of the V+1 space as the signal /(t)GV+ 1, then the above equation indicates The discrete approximation Af of f(t) can be obtained from the higher-order discrete approximation Ad+i/filter extraction, and the detail signal D/f of f(t) can also be obtained from the higher-order discrete approximation Ad+i/ Another filter is obtained. The filter h(n)g(n) is defined by the inner product of the scaling function h(t) and the wavelet function (1). If the original signal A0f has N samples, as long as the so-called a is given , b(t) - a wavelet basis function, when a > 1 (t) the waveform stretches, when a < 1 (t) waveform compression parameter a expansion and expansion and parameter b translation such as continuous value, called continuous In the practical application of wavelet transform, the binary discretization is performed, that is, the a= test is performed on the TRIACATC vertical machining center. The overcutting of the wave is mainly called the dip-wavelet change in the lap joint of the curved surface or the turning process of the tool. change.

For the digital signal obtained by sampling 9 computer, the binary is over-cut. The tool 2 workpiece is easy to occur. In order to simplify the test process and take into account the basic characteristics of overcutting, the paper has carried out the overcut simulation test as shown in the figure. The sampling frequency is 1 kHz. 3.1 The overcut test conditions are as follows: the cutter diameter is 8 mm. The cutting depth is 1mm, the spindle speed is n=500r/min, the feed speed is v=150mm/min, the overcut depth is Hg=0.05mm, the workpiece material is A3 steel, and the tool material is high speed steel. The measured signal, such as the over-cut signal and wavelet decomposition shown in S, can be seen from the time domain signal is more complex, there is no obvious over-cutting feature, such as observation from the frequency domain, because there is no time domain positioning, it can not achieve real-time monitoring the goal of. Therefore, the original measured signal is decomposed by wavelet, and the result of the transformation is listed in the transformation result. When the overcut occurs, the reflection on the small scale (high frequency) is not obvious, but the overcut feature on the fourth scale is obviously It shows that in the actual monitoring, a threshold can be set on the scale to identify the cutting state, and the overcut point is accurately positioned in the wavelet transform diagram in time-frequency and bidirectional, thus facilitating real-time monitoring of 3.2 overcut test. Two test conditions: milling cutter diameter is 10mm, cutting depth is = 0.5mm, spindle speed n=500r/min, feed speed v=150mm/min, overcutting depth Q1mm, workpiece material is A tide, tool material is high speed steel The measured signal and its wavelet decomposition can be seen from the figure. The overcut point is not obvious in the high frequency band. On the fourth scale, the overcut feature is obviously displayed. 4 Conclusion Wavelet transform is the time-frequency localization of the signal. Provides a mathematical basis using wavelet analysis method, which can analyze signals from time and frequency domains simultaneously, and perform precise time-frequency localization of points of interest in NC machining of workpiece free-form surfaces. Overcutting is common. The fault form, the entry point contains rich frequency information, but it is difficult to obtain the relevant information of the cut only from the time domain observation. The wavelet analysis can observe the signal at different times, and can accurately extract various kinds of frequency mutation points. Information The research in this paper shows that at the time, the space uses "focusing" scanning to observe the over-cut information. Although it is not obvious in some frequency bands, in other frequency bands, the wavelet coefficient value is prominent and can effectively identify the tool cutting in real time. Status, which lays the foundation for tool status monitoring

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