A vibration signal comprehensive evaluation method for determining a vibration sensor arrangement of a vertical spindle machine tool

Abstract

The present application provides a kind of vibration signal comprehensive evaluation method for determining vertical spindle machine tool vibration sensor arrangement scheme, it is related to the measurement processing technical field in the field of intelligent manufacturing, the present application generates multiple sensor position preselected scheme, selects the same vertical spindle machine tool of normal and appears chip problem, respectively arrange sensor;Normal and appear chip problem vibration signal;The steady-state response of normal constant speed idle vibration signal and the vibration interference of normal vibration signal when trial cutting are analyzed, and the standard scheme under normal condition is screened out;The nonlinear coupling inconsistency of constant speed idle vibration signal of the chip problem is analyzed, the corresponding index is generated;And the chip area identified based on the index, and compare its difference with real chip area, and the standard scheme under the chip problem is screened out;Select the scheme that is normal and normal under normal condition.

Description

Technical Field

[0001] This invention relates to the field of measurement and processing technology in intelligent manufacturing, specifically to a comprehensive evaluation method for vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool. Background Technology

[0002] In the field of intelligent manufacturing, sensors have become crucial tools for ensuring production quality, improving machining accuracy, and enhancing equipment stability. Vibration sensors play a particularly critical role, especially in high-precision and complex machining environments. Vibration data accurately reflects the equipment status and potential problems during machining, preventing malfunctions. When a malfunction occurs, the vibration sensor's ability to accurately identify the faulty component is also important. For vertical spindle machine tools, spindle vibration analysis is especially critical, as spindle vibration reflects machine tool problems. Chip clamping is the most common problem with vertical spindle machine tool spindles, and it can be identified by vibration sensors. However, traditional machine tool fault identification schemes typically only identify whether chip clamping has occurred, not its precise location. Since machine tools experiencing chip clamping often exhibit unique vibration patterns, multiple vibration sensors can be deployed to accurately locate the problem. However, improper sensor placement can lead to signal distortion or external noise interference, affecting data accuracy and consequently the effectiveness of the entire monitoring system.

[0003] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a comprehensive evaluation method for vibration signals in determining the arrangement scheme of vibration sensors for vertical spindle machine tools, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A comprehensive evaluation method for vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool, comprising the following steps:

[0007] Step 1: Generate multiple sensor position pre-selection schemes and form a pre-selection scheme set P0. Select two vertical spindle machine tools of the same model, one is a normal vertical spindle machine tool, and the other is a vertical spindle machine tool with chip clamping problems. Arrange sensors on the two vertical spindle machine tools according to the sensor position pre-selection schemes. Collect vibration signals under predetermined speed and tooth frequency, both under normal conditions and with chip clamping problems. The vibration signals include constant speed idle vibration signals and vibration signals during trial cutting.

[0008] Step 2: Analyze the steady-state response of the normal constant speed idling vibration signal and the vibration interference of the normal test cutting vibration signal respectively. Based on the analysis results, select the schemes that meet the standards for steady-state response and vibration interference from the scheme set P0 to form the scheme set P2.

[0009] Step 3: Based on the kurtosis of the constant-speed idle vibration signal where chip trapping occurs, determine the chip trapping judgment result, and select the scheme set P0 with the correct chip trapping judgment result from the scheme set P0. 01 The nonlinear coupling inconsistency of the constant speed idling vibration signal with chip clamping problem is analyzed by bispectral analysis, as well as the phase lag / lead of the signal, and corresponding nonlinear coupling inconsistency index and phase difference index are generated.

[0010] Step 4: Identify the chip-clamping regions based on both the asymmetry index and the phase difference index, analyze the differences between the identified chip-clamping regions and the actual chip-clamping regions, and use this information to select from the scheme set P. 01 Select solution set P 02 ;

[0011] Step 5: Combine solution set P2 and solution set P 02 The sensor location pre-selection scheme in the intersection is used as an alternative scheme.

[0012] Furthermore, the sensor position pre-selection scheme is used to arrange vibration sensors on the spindle surface of a vertical spindle machine tool, wherein five vibration sensors are arranged in the sensor position pre-selection scheme;

[0013] The vertical spindle machine tool that experienced chip clamping issues is a vertical spindle machine tool that has identified the chip clamping area. The vibration signal includes vibration signals collected by all sensors.

[0014] Furthermore, in chronological order, a period is selected in the signal. If the difference between the peak amplitude of the signal in the next six periods and the peak amplitude of the signal in the selected period is within a preset range, then the selected period and the next six periods are determined to be in steady state time. The peak amplitude of the signal in the selected period that is first defined as steady state time is taken as the steady state amplitude.

[0015] The maximum impact degree is calculated based on the maximum amplitude and steady-state amplitude of the constant-speed idle vibration signal, and is used to analyze whether the constant-speed idle vibration signal has an overshoot problem. The formula is:

[0016]

[0017] Among them, Mp i Amax represents the maximum impact level of the constant-speed idle vibration signal collected by the i-th vibration sensor. iAss represents the maximum peak amplitude of the constant-speed idle vibration signal acquired by the i-th vibration sensor. i Let be the steady-state amplitude of the constant-speed idle vibration signal collected by the i-th vibration sensor;

[0018] The steady-state difference is obtained by comparing the steady-state amplitude of the vibration signal with a preset standard value. This difference is used to analyze whether the vibration signal exhibits a large difference. The formula is as follows:

[0019]

[0020] in, Let Aref be the steady-state difference of the constant-speed idle vibration signal collected by the i-th vibration sensor, and Aref be the standard steady-state amplitude.

[0021] The maximum impact level and steady-state difference are compared with a preset threshold. If the difference is greater than the corresponding threshold, it is determined that the vibration sensor has overshoot or large difference. If the sensor has one or more of the problems of overshoot and large difference, it is called a problematic sensor. Schemes with a proportion of no more than 20% of problematic sensors are selected from the scheme set P0 and constitute the scheme set P1.

[0022] Furthermore, based on wavelet decomposition, the sum of the energy proportions of the tooth frequency and its harmonics in the vibration signal during the test cutting is obtained; a corresponding threshold is preset, and if the sum of the energy proportions is greater than the corresponding threshold, it is determined that the energy proportion of the corresponding sensor is normal. If the number of sensors with normal energy proportions in a sensor position pre-selection scheme is greater than 80%, it is determined that the vibration interference of the corresponding sensor position pre-selection scheme meets the standard. Schemes that meet the vibration interference standard are selected from scheme set P1 and constitute scheme set P2.

[0023] Furthermore, for constant-speed idle vibration signals exhibiting chip-clamping issues, the kurtosis of the constant-speed idle vibration signal is calculated, and a kurtosis threshold is preset. For schemes in scheme set P0, if there is a sensor with a kurtosis greater than the kurtosis threshold, the corresponding scheme is placed in scheme set P. 01 middle.

[0024] Furthermore, a bispectral slicing function is constructed based on the tooth frequency of the cutting tool. The bispectral slicing function is as follows:

[0025]

[0026] Among them, B(f) a f) is the value of the bispectral slice function, f a Let f be the tooth frequency of the tool, τ1 and τ2 be the time delay variables, and C3(τ1,τ2) be the third-order cumulative quantity.

[0027] Obtain the bispectral slice image f-|B(fa ,f)|;

[0028] When f > 0, obtain the frequency f corresponding to the first peak in the bispectral slice image. mod ,

[0029] The formula for obtaining the nonlinear coupling inconsistency index is:

[0030]

[0031] Where PB is the nonlinear coupling inconsistency index, {|B(f a ,f a )|,|B(f a ,f mod )|} max For |B(f) a ,f mod )| and |B(f a ,f a The maximum value in |).

[0032] The formula for obtaining the phase difference index is:

[0033]

[0034] Where XP is the phase difference index, k is the index of the peaks in the bispectral slice image, k is a positive integer, and f k This represents the frequency corresponding to the k-th peak in the bispectral slice image.

[0035] Furthermore, the nonlinear coupling inconsistency index and phase difference index of each vibration sensor are obtained. The distribution of the nonlinear coupling inconsistency index and phase difference index on the principal axis unfolding plane is inverted using radial basis function interpolation. Preset adjustment sideband asymmetry thresholds and phase difference thresholds. The set of points with nonlinear coupling inconsistency indices greater than the adjustment sideband asymmetry threshold is defined as the first chip-clamping region, and the set of points with phase difference indices greater than the phase difference threshold is defined as the second chip-clamping region. The overlapping portion of the first and second chip-clamping regions is identified as the chip-clamping region. Points in the chip-clamping regions form an identification chip-clamping point set, obtaining the actual chip-clamping region distribution. Points in the actual chip-clamping regions form an actual chip-clamping point set. The intersection-union ratio (IUU) of the identification chip-clamping point set and the actual chip-clamping point set is calculated, and a scheme set P is selected. 01 Schemes with a cross-sectional ratio greater than a preset threshold constitute a scheme set P. 02 .

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] This invention reduces signal distortion and external noise interference by rationally arranging vibration sensors. It also more accurately reflects the operating status of equipment, thus providing more reliable data support. This not only improves the accuracy of vibration monitoring and enhances the sensitivity of vibration data, but also allows early signs of abnormal vibration to be detected sooner, thereby enabling timely identification of potential faults and providing early warnings.

[0038] This invention analyzes the steady-state response of vibration signals during normal vertical spindle machine tool operation, selects schemes with good steady-state response, analyzes vibration signals during trial cutting, and selects schemes with less interference. Through multiple screenings, it can ensure that the layout scheme meets both steady-state accuracy and dynamic anti-interference requirements, significantly improving the accuracy and reliability of vibration signals during machining.

[0039] By analyzing the unique vibration signal characteristics of the spindle chip clamping problem (nonlinear coupling inconsistency and signal phase lag / lead), it is possible not only to identify whether a chip clamping fault has occurred, but also to accurately locate the chip clamping position. By studying the accuracy of chip clamping area identification under different sensor arrangements, a sensor arrangement scheme that meets the identification accuracy requirements can be selected, significantly enhancing the fault feature capture capability. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the overall method flow of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0042] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0043] Example:

[0044] Please see Figure 1 The present invention provides a technical solution:

[0045] A comprehensive evaluation method for vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool, comprising the following steps:

[0046] Step 1: Generate multiple sensor position pre-selection schemes and form a pre-selection scheme set P0. Select two vertical spindle machine tools of the same model, one is a normal vertical spindle machine tool, and the other is a vertical spindle machine tool with chip clamping problems. Arrange sensors on the two vertical spindle machine tools according to the sensor position pre-selection schemes. Collect vibration signals under predetermined speed and tooth frequency, both under normal conditions and with chip clamping problems. The vibration signals include constant speed idle vibration signals and vibration signals during trial cutting.

[0047] Furthermore, the sensor position pre-selection scheme is used to arrange vibration sensors on the spindle surface of a vertical spindle machine tool, wherein five vibration sensors are arranged in the sensor position pre-selection scheme;

[0048] The vertical spindle machine tool that experienced chip clamping issues is a vertical spindle machine tool that has identified the chip clamping area. The vibration signal includes vibration signals collected by all sensors.

[0049] Step 2: Analyze the steady-state response of the normal constant speed idling vibration signal and the vibration interference of the normal test cutting vibration signal respectively. Based on the analysis results, select the schemes that meet the standards for steady-state response and vibration interference from the scheme set P0 to form the scheme set P2.

[0050] Furthermore, in chronological order, a period is selected in the signal. If the difference between the peak amplitude of the signal in the next six periods and the peak amplitude of the signal in the selected period is within a preset range, then the selected period and the next six periods are determined to be in steady state time. The peak amplitude of the signal in the selected period that is first defined as steady state time is taken as the steady state amplitude.

[0051] Overshoot refers to the transient peak value of the system response (spindle vibration) exceeding the steady-state value before reaching steady state. The maximum impact degree is calculated based on the maximum amplitude and steady-state amplitude of the constant-speed idle vibration signal, and is used to analyze whether overshoot occurs in the constant-speed idle vibration signal. The formula is:

[0052]

[0053] Among them, Mp i Amax represents the maximum impact level of the constant-speed idle vibration signal collected by the i-th vibration sensor. i Ass represents the maximum peak amplitude of the constant-speed idle vibration signal acquired by the i-th vibration sensor. i Let be the steady-state amplitude of the constant-speed idle vibration signal collected by the i-th vibration sensor;

[0054] The maximum impact level of the constant speed idle vibration signal measures the relative difference between the maximum transient impact intensity and the steady-state operating level of the spindle before reaching steady state. It can be used to reflect whether excessive vibration fluctuations occur in the system from initial to steady state, and whether this impact is abnormal relative to the system's stable performance. The greater the maximum impact level, the larger the overshoot amplitude, and the more severe the peak impact, the more unstable the spindle system response is when reaching steady state, indicating that the sensor arrangement is not good enough.

[0055] The steady-state difference is obtained by comparing the steady-state amplitude of the vibration signal with a preset standard value. This difference is used to analyze whether the vibration signal exhibits a large difference. The formula is as follows:

[0056]

[0057] in, Let Aref be the steady-state difference of the constant-speed idle vibration signal collected by the i-th vibration sensor, and Aref be the standard steady-state amplitude.

[0058] The steady-state difference is used to assess whether the current system has an abnormal vibration offset phenomenon in the steady-state operation phase, and thus to determine whether the sensor arrangement is reasonable. The larger the value, the greater the difference between the amplitude of the system in the steady-state phase and the standard amplitude. Since the vibration data of a vertical spindle machine tool that is known to be normal is collected, a large value indicates that the collected vibration signal is inaccurate and the sensor arrangement is unreasonable.

[0059] A maximum impact threshold is preset. The maximum impact level is compared with this threshold. If the maximum impact level exceeds this threshold, the vibration sensor is considered to have overshoot. A steady-state difference threshold is also preset. The steady-state difference is compared with this threshold. If the steady-state difference exceeds this threshold, the sensor is considered to have a large difference problem. If a sensor exhibits one or more of the problems of overshoot and large difference, it is designated as a problematic sensor. Schemes with no more than 20% of problematic sensors are selected from scheme set P0 and form scheme set P1. Because it is determined before acquisition that the vibration signal is acquired in a normal vertical spindle machine tool and is a no-load vibration signal at a constant speed, the acquired vibration signal will not exhibit the overshoot and difference problems. If they do, it indicates that the sensor placement is unreasonable.

[0060] The maximum impact threshold and steady-state difference threshold are determined by experts in the field based on specific circumstances. For example, the maximum impact and steady-state difference of a normal vertical spindle machine tool and a vertical spindle machine tool with chip clamping problems can be calculated using the above method. Then, experts in the field can be invited to demonstrate the maximum impact and steady-state difference of the normal vertical spindle machine tool and the vertical spindle machine tool with chip clamping problems to determine the maximum impact threshold and steady-state difference threshold. This is existing technology and will not be elaborated here.

[0061] The selected scheme has two advantages, corresponding to the two threshold comparison results mentioned above. First, it can select stable signals without transient overshoot interference, ensuring that the idling vibration signal strictly converges to the steady-state value and guaranteeing the stability of the signal acquired under normal spindle operation. Second, it can ensure the accuracy of the acquired signal and select a sensor position pre-selection scheme with higher accuracy.

[0062] Furthermore, based on wavelet decomposition, the sum of the energy proportions of the tooth frequency and its harmonics in the vibration signal during the test cutting is obtained; a corresponding threshold is preset, and if the sum of the energy proportions is greater than the corresponding threshold, it is determined that the energy proportion of the corresponding sensor is normal. If the number of sensors with normal energy proportions in a sensor position pre-selection scheme is greater than 80%, it is determined that the vibration interference of the corresponding sensor position pre-selection scheme meets the standard. Schemes that meet the vibration interference standard are selected from scheme set P1 and constitute scheme set P2.

[0063] The threshold for the sum of energy proportions is determined by experts in the field based on the specific circumstances. For example, the sum of the energy proportions of a normal vertical spindle machine tool and a vertical spindle machine tool with chip clamping problems can be calculated using the above method. Then, experts in the field can be invited to demonstrate the sum of the energy proportions of the normal and vertical spindle machine tools with chip clamping problems in order to determine the threshold for the sum of energy proportions. This is existing technology and will not be elaborated here.

[0064] Because the tool tooth frequency directly affects the vibration signal frequency, a high proportion of energy from the tool tooth frequency and its harmonics indicates a low proportion of interference energy. A sum of energy proportions greater than the corresponding threshold indicates a low proportion of interference energy from the sensors in that arrangement.

[0065] Based on wavelet decomposition, the sum of the energy proportions of the tooth frequency and its harmonics in the vibration signal during trial cutting can be obtained using existing techniques, specifically:

[0066] The continuous vibration signal is discretized, and the db8 order is selected as the wavelet basis. db8 belongs to the higher order wavelets in the Daubechies series, which has good smoothness and tight support. It can better adapt to the local variation characteristics of tool impact signals and is convenient for detecting transient signals such as tooth frequency impact.

[0067] Set the sampling frequency, and based on the sampling frequency and the tooth frequency, locate the frequency band containing the tooth frequency component in the detail subband of a certain layer;

[0068]

[0069] Among them, J g The wavelet decomposition level corresponding to the g-th harmonic of the tooth frequency is given by fs, where fs is the sampling frequency, and g*f a The g-th harmonic of the tool tooth frequency; obtain Jg For g that is initially 0, we study the J corresponding to 1 to g-1. g The detail subband coefficients of the wavelet decomposition layers.

[0070] Using the db8 order as the wavelet basis, the discretized vibration signal is decomposed into J-level wavelet coefficients to obtain the approximation subband coefficients and detail subband coefficients of each level.

[0071] Calculate J i The sum of all detail subband coefficients of the wavelet decomposition layer is called the tooth frequency harmonic energy. The J values ​​corresponding to 1 to g⁻¹ are calculated. g The sum of the energy of the tooth frequency and its harmonics for each wavelet decomposition layer is calculated. The sum of the detail subband coefficients for all wavelet decomposition layers is then added together to obtain the total energy. The sum of the detail subband coefficients is divided by the total energy to obtain the sum of the energy percentage of the tooth frequency and its harmonics.

[0072] Step 3: Based on the kurtosis of the constant-speed idle vibration signal where chip trapping occurs, determine the chip trapping judgment result, and select the scheme set P0 with the correct chip trapping judgment result from the scheme set P0. 01 The nonlinear coupling inconsistency of the constant speed idling vibration signal with chip clamping problem is analyzed by bispectral analysis, as well as the phase lag / lead of the signal, and corresponding nonlinear coupling inconsistency index and phase difference index are generated.

[0073] Furthermore, for constant-speed idle vibration signals exhibiting chip-clamping issues, the kurtosis of the constant-speed idle vibration signal is calculated, and a kurtosis threshold is preset. For schemes in scheme set P0, if there is a sensor with a kurtosis greater than the kurtosis threshold, the corresponding scheme is placed in scheme set P. 01 middle.

[0074] The kurtosis threshold is determined by experts in the field based on the specific circumstances. For example, the kurtosis of a normal vertical spindle machine tool and a vertical spindle machine tool with chip clamping problems can be calculated using the above method. Then, experts in the field can be invited to demonstrate the kurtosis of the normal vertical spindle machine tool and the vertical spindle machine tool with chip clamping problems in order to determine the kurtosis threshold. This is existing technology and will not be elaborated here.

[0075] Furthermore, a bispectral slicing function is constructed based on the tooth frequency of the cutting tool. The bispectral slicing function is as follows:

[0076]

[0077] Among them, B(f) a f) is the value of the bispectral slice function, f a Let f be the tooth frequency of the tool, τ1 and τ2 be the time delay variables, and C3(τ1,τ2) be the third-order cumulative quantity.

[0078] Obtain the bispectral slice image f-|B(f a,f)|;

[0079] When f > 0, obtain the frequency f corresponding to the first peak in the bispectral slice image. mod The peaks in a bispectral slice image are called virtual peaks.

[0080] The formula for obtaining the nonlinear coupling inconsistency index is:

[0081]

[0082] Where PB is the nonlinear coupling inconsistency index, {|B(f a ,f a )|,|B(f a ,f mod )|} max For |B(f) a ,f mod )| and |B(f a ,f a The maximum value in |).

[0083] f a The tooth frequency of the cutting tool is the core frequency point for fault energy accumulation, f mod It is the frequency corresponding to the first peak in the bispectral slice image, which corresponds to the tooth frequency of the cutting tool, |B(f a ,f a | represents the tooth frequency self-coupling term (the nonlinear modulation strength between the main frequency and itself), which is the coupling strength under "ideal conditions", |B(f a ,f mod ||B(f) represents the coupling strength between the actual modulation frequency (the point of maximum asymmetry) and the tooth frequency; a ,f a )|-|B(f a ,f mod || represents the coupling strength deviation between frequency self-coupling and frequency modulation coupling, {|B(f a ,f a )|,|B(f a ,f mod )|} max For normalization, the vibration signal of a normally functioning vertical spindle machine tool's spindle is relatively stable due to minimal interference and relatively low nonlinear coupling. The deviation in coupling strength between frequency self-coupling and frequency modulation coupling is usually small. However, for the vibration signal in the chip-clamped region of a vertical spindle machine tool, the chip clamping problem causes amplitude and frequency modulation on the tooth frequency, resulting in strong nonlinear modulation. Therefore, the deviation in coupling strength between frequency self-coupling and frequency modulation coupling is usually larger, hence ||B(f a ,f a)|-|B(f a ,f mod The larger the value of the nonlinear coupling inconsistency index, the more severe the chip-entrapment problem. This index reflects the degree of nonlinear adjustment caused by chip-entrapment by measuring the deviation in coupling strength between the self-coupling and frequency-tuning coupling of the tooth frequency. A higher value indicates a greater degree of nonlinear adjustment and more severe chip-entrapment. This index quantifies the impact of chip-entrapment by analyzing the nonlinear adjustment of the system, providing an important theoretical basis for the identification and localization of chip-entrapment problems.

[0084] The formula for obtaining the phase difference index is:

[0085]

[0086] Where XP is the phase difference index, k is the index of the peaks in the bispectral slice image, k is a positive integer, and f k This represents the frequency corresponding to the k-th peak in the bispectral slice image.

[0087] For the vibration signal of a normally functioning vertical spindle machine tool, the tooth frequency and its harmonics of the cutting tool correspond one-to-one with the frequency of the virtual peak of the adjusted frequency. Usually, the numerical differences are small. However, when the spindle of the vertical spindle machine tool experiences chip clamping, the vibration mode of the vibration signal changes due to this problem. The tooth frequency and its harmonics of the cutting tool no longer correspond one-to-one with the frequency of the virtual peak of the adjusted frequency. The greater the difference, the greater the change in vibration mode, indicating a more severe chip clamping problem. This change in vibration mode is directly reflected in phase lead or lag. In the analysis, selecting the harmonics of the first five tooth frequencies of the cutting tool can represent the phase lead or lag of the vibration signal caused by the change in vibration mode. The phase difference index can quantify the change in signal vibration mode caused by chip clamping, and thus the resulting phase lead or lag of the vibration signal. This index can be used to identify and locate chip clamping problems, providing an important basis for sensor placement.

[0088] Step 4: Identify the chip-clamping regions based on both the asymmetry index and the phase difference index, analyze the differences between the identified chip-clamping regions and the actual chip-clamping regions, and use this information to select from the scheme set P. 01 Select solution set P 02 ;

[0089] Furthermore, the nonlinear coupling inconsistency index and phase difference index of each vibration sensor are obtained, and the distribution of the nonlinear coupling inconsistency index and phase difference index of the principal axis unfolding plane is inverted using the radial basis function interpolation method. Through radial basis function interpolation, the nonlinear index and phase difference index of the vibration sensor are inverted into a continuous two-dimensional distribution field, which overcomes the spatial blind zone problem caused by the sparse and irregular distribution of sensor points and can more accurately locate the specific area where the chip clamping anomaly occurs.

[0090] By setting preset thresholds for adjusting sideband asymmetry and phase difference, the set of points where the nonlinear coupling inconsistency index exceeds the adjusting sideband asymmetry threshold is defined as the first chip-clamping region, and the set of points where the phase difference index exceeds the phase difference threshold is defined as the second chip-clamping region. The overlapping portion of the first and second chip-clamping regions is identified as the chip-clamping region. By setting the nonlinear coupling inconsistency threshold and the phase difference threshold, abnormal points are divided into two categories (the first chip-clamping region and the second chip-clamping region), and the intersection of the two is taken to form the final chip-clamping identification region, which improves the specificity and accuracy of chip-clamping detection. Utilizing the overlapping region between indicators enhances the reliability of identification and reduces the risk of misjudgment based on a single indicator.

[0091] Points in the chip-clamping region are used to construct an identification chip-clamping point set. The actual chip-clamping region distribution is obtained, and points in the actual chip-clamping region are used to construct an actual chip-clamping point set. The intersection-union ratio (IUU) of the identification chip-clamping point set and the actual chip-clamping point set is calculated. A scheme set P is then selected. 01 Schemes with a cross-sectional ratio greater than a preset threshold constitute a scheme set P. 02 The recognition effect can be quantitatively evaluated by calculating the intersection-union ratio (IUU) between the identified chip-clamping point set and the actual chip-clamping point set, which facilitates the comparison of the recognition accuracy of different schemes.

[0092] The nonlinear coupling inconsistency threshold and phase difference threshold are determined by experts in the field based on specific circumstances. For example, the nonlinear coupling inconsistency index and phase difference index of a normal and chip-clamping vertical spindle machine tool can be calculated using the above method. Then, experts in the field are invited to verify the nonlinear coupling inconsistency index and phase difference index of the normal and chip-clamping vertical spindle machine tool to determine the nonlinear coupling inconsistency threshold and phase difference threshold. This is existing technology and will not be elaborated here. The radial basis function interpolation method can be used to invert the distribution of the nonlinear coupling inconsistency index on the spindle unfolded plane. Specifically, the spindle surface is unfolded into a plane, a rectangular coordinate system is established on the unfolded plane, the positions of the five sensors and the nonlinear coupling inconsistency index are marked, and the position coordinates of the five sensors and the nonlinear coupling inconsistency index are input into the radial basis function interpolation model to invert the distribution of the nonlinear coupling inconsistency index.

[0093] The radial basis function interpolation model is expressed as:

[0094]

[0095] PB(x,y) is the nonlinear coupling inconsistency index at position (x,y), where (x... i ,y i Let be the position coordinates of the i-th vibration sensor, and w be the position coordinates of the i-th vibration sensor. iLet φ(·) be the i-th weight, where i is the index of the vibration sensor, and φ(·) be the radial basis function. Since there are relatively few vibration sensors used for inversion in this embodiment, the radial basis function is selected as the Gaussian kernel function.

[0096] Substituting the known position coordinates of the five sensors and the nonlinear coupling inconsistency index into the above formula, we can obtain w. k This allows us to inversely derive the nonlinear coupling inconsistency index for each point in space.

[0097] The method for obtaining the phase difference index distribution is the same as that for obtaining the nonlinear coupling inconsistency index distribution, and will not be elaborated here.

[0098] Step 5: Combine solution set P2 and solution set P 02 The sensor location pre-selection scheme in the intersection is used as an alternative scheme.

[0099] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0100] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0101] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0102] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that cannot be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool, characterized in that, The specific steps include: Step 1: Generate multiple sensor position pre-selection schemes and form a pre-selection scheme set P0. Select two vertical spindle machine tools of the same model, one is a normal vertical spindle machine tool, and the other is a vertical spindle machine tool with chip clamping problems. Arrange sensors on the two vertical spindle machine tools according to the sensor position pre-selection schemes. Collect vibration signals under predetermined speed and tooth frequency, both under normal conditions and with chip clamping problems. The vibration signals include constant speed idle vibration signals and vibration signals during trial cutting. Step 2: Analyze the steady-state response of the normal constant speed idling vibration signal and the vibration interference of the normal test cutting vibration signal respectively. Based on the analysis results, select the schemes that meet the standards for steady-state response and vibration interference from the scheme set P0 to form the scheme set P2. Step 3: Based on the kurtosis of the constant-speed idle vibration signal where chip trapping occurs, determine the chip trapping judgment result, and select the scheme set P0 with the correct chip trapping judgment result from the scheme set P0. 01 The nonlinear coupling inconsistency of the constant speed idling vibration signal with chip clamping problem is analyzed by bispectral analysis, as well as the phase lag / lead of the signal, and corresponding nonlinear coupling inconsistency index and phase difference index are generated. Step 4: Identify the chip-clamping regions based on both the asymmetry index and the phase difference index, analyze the differences between the identified chip-clamping regions and the actual chip-clamping regions, and use this information to select from the scheme set P. 01 Select solution set P 02 ; Step 5: Combine solution set P2 and solution set P 02 The sensor location pre-selection scheme in the intersection is used as an alternative scheme.

2. The method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool according to claim 1, characterized in that: The sensor position pre-selection scheme is used to arrange vibration sensors on the spindle surface of a vertical spindle machine tool. The vibration sensors arranged in the sensor position pre-selection scheme are 5. The vertical spindle machine tool that experienced chip clamping issues is a vertical spindle machine tool that has identified the chip clamping area. The vibration signal includes vibration signals collected by all sensors.

3. The method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool according to claim 1, characterized in that: If a period is selected sequentially in the signal according to the time sequence, and the difference between the peak amplitude of the signal in the next six periods and the peak amplitude of the signal in the selected period is within a preset range, then the selected period and the next six periods are determined to be in steady state time, and the peak amplitude of the signal in the selected period that is first defined as steady state time is taken as the steady state amplitude. The maximum impact degree is calculated based on the maximum amplitude and steady-state amplitude of the constant-speed idle vibration signal, and is used to analyze whether the constant-speed idle vibration signal has an overshoot problem. The formula is: Among them, Mp i Amax represents the maximum impact level of the constant-speed idle vibration signal collected by the i-th vibration sensor. i Ass represents the maximum peak amplitude of the constant-speed idle vibration signal acquired by the i-th vibration sensor. i Let be the steady-state amplitude of the constant-speed idle vibration signal collected by the i-th vibration sensor; The steady-state difference is obtained by comparing the steady-state amplitude of the vibration signal with a preset standard value. This difference is used to analyze whether the vibration signal exhibits a large difference. The formula is as follows: in, Let Aref be the steady-state difference of the constant-speed idle vibration signal collected by the i-th vibration sensor, and Aref be the standard steady-state amplitude. The maximum impact level and steady-state difference are compared with a preset threshold. If the difference is greater than the corresponding threshold, it is determined that the vibration sensor has overshoot or large difference. If the sensor has one or more of the problems of overshoot and large difference, it is called a problematic sensor. Schemes with a proportion of no more than 20% of problematic sensors are selected from the scheme set P0 and constitute the scheme set P1.

4. The method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool according to claim 3, characterized in that: Based on wavelet decomposition, the sum of the energy proportions of the tooth frequency and its harmonics in the vibration signal during trial cutting is obtained; If the sum of the energy percentages is greater than the corresponding threshold, the energy percentage of the corresponding sensor is considered normal. If the number of sensors with normal energy percentages in a pre-selected sensor location scheme is greater than 80%, the vibration interference of the pre-selected sensor location scheme is considered to meet the standard. Schemes that meet the vibration interference standard are selected from scheme set P1 and form scheme set P2.

5. The method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool according to claim 2, characterized in that: For constant-speed idle vibration signals exhibiting chip trapping issues, the kurtosis of the constant-speed idle vibration signal is calculated, and a kurtosis threshold is preset. For each scheme in scheme set P0, if there is a sensor with a kurtosis greater than the kurtosis threshold, the corresponding scheme is placed in scheme set P. 01 middle.

6. The method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool according to claim 5, characterized in that: A bispectral slicing function is constructed based on the tooth frequency of the cutting tool. The bispectral slicing function is as follows: Among them, B(f) a f) is the value of the bispectral slice function, f a Let f be the tooth frequency of the tool, τ1 and τ2 be the time delay variables, and C3(τ1,τ2) be the third-order cumulative quantity. Obtain the bispectral slice image f-|B(f a ,f)|; When f > 0, obtain the frequency f corresponding to the first peak in the bispectral slice image. mod , The formula for obtaining the nonlinear coupling inconsistency index is: Where PB is the nonlinear coupling inconsistency index, {|B(f a ,f a )|,|B(f a ,f mod )|} max For |B(f) a ,f mod )| and |B(f a ,f a The maximum value in |). The formula for obtaining the phase difference index is: Where XP is the phase difference index, k is the index of the peaks in the bispectral slice image, k is a positive integer, and f k This represents the frequency corresponding to the k-th peak in the bispectral slice image.

7. The method for comprehensive evaluation of vibration signals in determining the arrangement scheme of vibration sensors for a vertical spindle machine tool according to claim 6, characterized in that: The nonlinear coupling inconsistency index and phase difference index of each vibration sensor are obtained. The distribution of the nonlinear coupling inconsistency index and phase difference index of the principal axis unfolding plane is inverted using the radial basis function interpolation method. The adjustment sideband asymmetry threshold and phase difference threshold are preset. The point set where the nonlinear coupling inconsistency index is greater than the adjustment sideband asymmetry threshold is defined as the first chip-clamping region, and the point set where the phase difference index is greater than the phase difference threshold is defined as the second chip-clamping region. The overlapping part of the first chip-clamping region and the second chip-clamping region is identified as the chip-clamping region. Points in the chip-clamping region are used to construct an identification chip-clamping point set. The actual chip-clamping region distribution is obtained, and points in the actual chip-clamping region are used to construct an actual chip-clamping point set. The intersection-union ratio (IUU) of the identification chip-clamping point set and the actual chip-clamping point set is calculated. A scheme set P is then selected. 01 Schemes with a cross-sectional ratio greater than a preset threshold constitute a scheme set P. 02 .

Images