Detection method for machine tool foundation thickness, internal defect and vibration isolation effect

Abstract

The invention discloses a method for detecting the thickness, internal defects and vibration isolation effect of a machine tool foundation, and aims to evaluate the effective thickness, internal defects and vibration isolation effect of the foundation, ensure that a machine tool spindle and a workbench are free from external vibration interference and provide a basis for machine tool layout. The method comprises the following steps: dividing grid measuring point areas on the surface of a machine tool foundation; calibrating the propagation velocity of the vibration wave by using two sensors; an excitation hammer with a single vibration mode and an obvious wave crest is selected according to the excitation waveform; exciting along the normal direction of the measuring point, and collecting a time-domain vibration signal at a sampling frequency not lower than 10kHz; extracting a dominant frequency through discrete Fourier transform, calculating an effective thickness, and identifying an abnormal harmonic peak to judge an internal defect; sensors are arranged on the vibration source side and the protected side, vibration signals are collected synchronously, and the vibration transmissibility is calculated to evaluate the vibration isolation effect.

Description

Technical Field

[0001] The present invention belongs to the field of numerical control machining, and particularly relates to a detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation. Background Art

[0002] The machining effect and service life of high-precision machine tools are both affected by the foundation. When the poured foundation is unqualified, it is easy for external vibrations to be transmitted to the machine tool through the foundation, resulting in resonance of the machine tool, thereby affecting the machining effect and service life of the machine tool. When the machine tool is transported to the customer's site, it is generally not known whether the foundation at the customer's place meets the machining accuracy requirements of the machine tool. When the machine tool is placed in an unknown area, once the machine tool foundation fails to meet the machining requirements, it will directly affect the machining accuracy and product quality of the customer, not only wasting the labor and time costs during installation and debugging, but also requiring the foundation to be thickened.

[0003] At present, most of the quality inspections of foundations or walls are detection methods used in the construction industry. The detection of the ground mainly focuses on detecting the maximum bearing capacity of the ground, and the detection of the wall mainly focuses on detecting the internal defects of the cavities in the wall. However, there is relatively little involvement in the effective thickness, cavities and internal defects inside the machine tool foundation, and there is no detection method for the vibration isolation effect. The traditional vibration detection method is difficult to effectively judge whether the vibrations of the spindle and the workbench are caused by interference from external vibration sources. Judging the vibration situation of the machine tool only through empirical methods lacks scientific and theoretical technical support and is unconvincing, thus unable to provide a reliable basis for the reasonable layout of the machine tool.

[0004] Therefore, by selecting a non-destructive testing method to detect the effective thickness and quality of the foundation, the most suitable location for placing the high-precision machine tool can be selected according to the evaluation results of the foundation quality at different positions in the customer's workshop. Summary of the Invention

[0005] The purpose of the present invention is to provide a detection method dedicated to the effective thickness, internal defects and vibration isolation effect of a high-precision machine tool foundation for the above-mentioned problems in the existing technology. This method can conveniently and quickly detect the effective thickness, internal defects and vibration isolation effect of the foundation in the workshop where the machine tool is placed, and use scientific means to select the most suitable location for placing the high-precision machine tool for the customer.

[0006] In order to achieve the above purpose, the technical solution adopted by the present invention includes the following steps: 1) Detection of foundation parameters based on the impact echo method: 1.1) On the surface of the machine tool foundation, divide the foundation measurement area according to the projected size of the machine tool base; 1.2) Calibrate the propagation speed of vibration waves in the area to be measured through two sensors on the surface of the area to be measured V P ; 1.3) Select the specification of the excitation hammer according to the excitation waveform of the excitation hammer on the ground to be measured; 1.4) Implement excitation along the normal direction of the measuring point, and collect the time-domain vibration signal through the acceleration vibration sensors arranged around the excitation point; 1.5) Extract the dominant frequency matrix of the direct wave and the reflected wave based on the frequency-domain signal after discrete Fourier transform F max , and calculate the effective thickness according to the formula H = V p * L / (2 F max * Δ t ). At the same time, identify the abnormal resonance peaks that can express the internal defect signals in the frequency band of 0.5 - 10 kHz through the spectrum analysis method; 2) Evaluation of the vibration isolation effect based on dual sensors, including: 2.1) Arrange the first and second acceleration vibration sensors on the vibration source side and the protected side adjacent to the machine tool foundation respectively. The distance between the two sensors is 0.7 m, and the excitation point is 0.1 m away from the first sensor; 2.2) Synchronously collect 5 groups of vibration signals, and calculate the percentage of the energy that can be isolated when the vibration is transmitted on the vibration source side and the protected side according to the vibration transmissibility η to evaluate the vibration isolation effect of the current foundation. E To further elaborate, in step 1), according to the projection size of the machine tool base and the size of the surrounding installation space, delimit the rectangular measurement area range on the foundation surface, and control the measurement area within 2 - 3 m²; arrange the measurement points in the measurement area according to the equal-spacing grid division method, and the measurement point spacing can be dynamically adjusted according to the length-width ratio of the base.

[0007] To further elaborate, in the area to be measured, by comparing and testing the frequency-domain signal characteristics of different specifications of excitation hammers, preferentially select the excitation hammer model with a single vibration mode, obvious wave peaks, and the least clutter as the excitation hammer for subsequent detection.

[0008] To further elaborate, vertically strike the excitation at the center position of each measurement point, and symmetrically arrange the acceleration vibration sensors 30 mm around the excitation point, and synchronously collect the time-domain vibration signal at a sampling frequency not lower than 10 kHz; the acquisition duration of each impact signal is ≥ 10 ms, and each measurement point is repeatedly collected 3 times and subjected to time-domain averaging processing.

[0009]

[0010] ​Further, perform discrete Fourier transform on the collected time-domain signals, and extract the main frequency peaks of the direct wave and the reflected wave within the frequency band of 0.5 - 10 kHz; calculate the effective thickness of each measuring point, and take the arithmetic mean after removing the outliers that deviate from the mean by ±8% as the regional average thickness; identify the abnormal resonance peaks in the frequency-domain signal with an amplitude exceeding the background noise by 20 dB and a Q factor > 50 through the matching pursuit algorithm, and determine it as the internal defect area in combination with a thickness distribution standard deviation ≥ 12%.

[0011] Further, in step 2), the vibration source side is the peripheral structure of the foundation, and the protected side is the contact area of the machine tool base. The two sensors are arranged 0.7 m apart along the vibration propagation direction, and an excitation is generated by hitting with an impact hammer. The energy loss of the vibration signal during transmission on the vibration source side and the protected side is collected through the two sensors.

[0012] Further, through the vibration transmissibility η = 20log(A2 / A1) to calculate the vibration isolation effect. When η ≤ -25 dB and the 1 / 3 octave band spectrum attenuation rate ≥ 15 dB, it is determined that the vibration isolation effect in this area meets the standard, where A1 and A2 are the effective values of the vibration acceleration on the vibration source side and the protected side respectively.

[0013] The present invention is a comprehensive detection method specifically developed for the foundation of high-precision CNC machine tools. Through innovative steps such as refined measuring point arrangement, optimized impact hammer selection, optimized sensor arrangement, spectrum analysis and abnormal resonance peak identification, and dual-sensor vibration isolation effect evaluation, it achieves the effects of improving detection accuracy, enhancing signal quality, strengthening defect detection ability, and improving the accuracy of vibration isolation performance evaluation, significantly improving the detection accuracy and efficiency of foundation thickness, internal defects, and vibration isolation effect, and providing a more reliable and effective method for foundation parameter detection and vibration isolation effect evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 Flow chart for realizing the detection of the thickness, internal defects, and vibration isolation effect of the machine tool foundation of the present invention; Figure 2 Composition structure of the machine tool foundation detection method of the present invention; Figure 3 Actual product of the machine tool foundation detection method of the present invention; Figure 4 Schematic diagram of the impact echo method of the present invention; Figure 5 Schematic diagram of the vibration isolation effect detection of the present invention; Figure 6 Schematic diagram of the division of the measuring point area of the present invention; Figure 7 Schematic diagram of the self-produced impact hammer of the present invention; Figure 8 Schematic diagram of the acquisition interface for the effective thickness and internal defects of the present invention; Figure 9 Schematic diagram of the vibration isolation effect acquisition interface of the present invention; Figure 10 Schematic diagram of the effective thickness and internal defect analysis interface of the present invention; Figure 11 Schematic diagram of the vibration isolation effect analysis interface of the present invention. Specific embodiments

[0015] The present invention will be further described in detail below with reference to the accompanying drawings.

[0016] See Figure 1 , the implementation process of a detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to the present invention is as follows: First, divide the measuring points, calibrate the wave velocity and select an impact hammer, then collect the foundation thickness, internal defects and vibration isolation data respectively, and finally use the developed analysis software to process and analyze the collected data and generate a detection report.

[0017] See Figure 2 and Figure 3 , the software and hardware composition of a detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to the present invention includes: data acquisition and analysis software, acquisition module, sensor, impact hammer and industrial control computer. After installing the detection system software on the industrial control computer and connecting the sensor and module, the effective thickness, internal defects and vibration isolation effect data of the foundation can be collected.

[0018] See Figure 4 , the impact echo method refers to using a short mechanical impact to generate stress waves. The stress waves propagate along the inside of the structure and are reflected and diffracted when encountering internal defects and the bottom boundary of the concrete, and are reflected back by the internal defects and the bottom boundary. The effective thickness, internal defects and vibration isolation effect of the component are calculated through the propagation speed, propagation time and frequency spectrum characteristics of the waves inside the component.

[0019] The principle of the effective thickness detection method is as follows: For the collected time-domain data x ( n ) directly perform discrete Fourier transform (DFT). The DFT is shown in Equation (1), X ( k ) is its transformation result, k is the number of measurement points, and then calculate according to Equation (2) X ( k ) power spectrum estimation to obtain the power spectrum estimation of various frequency signals in the vibration signal , find the frequency index corresponding to the maximum value in the power spectrum estimation k max , k max As shown in Equation (3), if the sampling frequency isf s , the main frequency of each percussion point is f max , and the main frequency position is the effective thickness frequency corresponding to the current ground thickness. The effective thickness frequency matrix of the ground can be expressed as F max . The thickness calculation formula of the foundation is shown in Equation (6);

[0020] H is the effective thickness of the current measurement area, f maxij is the i th row and the j th column of the peak frequency of the main frequency on the spectrum diagram of each measurement point. F max is the frequency matrix of 25 points, b is the shape coefficient. For materials such as plates, walls, and floors, b taking 0.96 is sufficient. V p is the propagation speed of the vibration wave in the foundation, L is the distance between two sensors when calibrating the wave speed, Δ t is the time difference between the signals received by the two sensors.

[0021] The principle of the internal defect detection method is as follows: During the frequency transformation process, each peak frequency represents a different meaning. Among them, the main frequency corresponding to the highest peak marks the reflection frequency when the longitudinal wave reaches the bottom of the structure, while the peak of the abnormal resonance peak reveals the reflection frequency and its specific position of the crack or void. By analyzing the frequency information of these different peaks, we can accurately calculate the depth and position of the cracks inside the tested structure. The frequency indicating the foundation defect in a single column is shown in Equation (7), and the calculation of the internal defect of the foundation is shown in Equation (8);

[0022] d is the depth of the concrete crack, F i is the i th column of the crack defect frequency, f i1 represents the frequency of the first point in the V p th column, a represents the straight-line distance between the impact point and the sensor.

[0023] See Figure 5, the principle of the vibration isolation effect detection method is as follows: By setting two measuring points 0.7 m apart on the foundation vibration source side and the protected side, arranging dual-channel vibration sensors at the two measuring points respectively, making the sensors closely coupled with the ground, using an impact hammer to strike the No. 1 measuring point, and using the dual-channel vibration sensors to capture the energy attenuation of the vibration source signal at the two measuring points, so as to evaluate the vibration isolation effect of the foundation. The vibration transmissibility η The calculation formula is shown in Equation (9), and its conversion to the vibration isolation effect is shown in Equation (10). A 1. A are the effective root mean square values of the vibration acceleration on the vibration source side and the protected side respectively, η represents the vibration transmissibility, and E represents the percentage of energy that can be isolated.

[0024] See Figure 6 and Figure 7 , a detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to the present invention, divides the area to be measured into 25 measuring points equally by 5*5 according to the measuring point division method 6, and uses an impact hammer 7 to sequentially collect data at the 25 measuring points in the measuring point area.

[0025] Integrate the hardware and software developed for the detection into a set of systems. The system hardware includes a vibration data acquisition module, sensors, an impact hammer and an industrial control computer; the system software integrates the above-mentioned related algorithms, including functions such as data acquisition and data processing.

[0026] See Figure 8 and Figure 9 , the functions of the effective thickness data acquisition interface 8 in the software include: acquisition of effective thickness and internal defect data; the function of the vibration isolation effect data acquisition interface 9 is to acquire the foundation vibration isolation data. The data acquisition interface has a total of 25 sampling points, and the vibration isolation acquisition interface has a total of 5 sampling points. The data acquisition steps are as follows: The first step: Open the foundation detection system software, connect the sensors and the data acquisition module, and keep the software and hardware in normal communication; The second step: Divide the measurement area into a 5*5 rectangular block, polish the ground at the measuring point and clean the dust on the ground to ensure that the sensor is closely coupled with the ground, and calibrate the propagation speed of the current ground vibration wave; The third step: Press the sensor tightly on the smooth and clean ground, use impact hammers of different models to strike the ground, and select the impact hammer with a single vibration mode and obvious wave peaks as the impact hammer for subsequent detection; Step 4: Thickness and defect data collection: On the data collection page, click on "Sampling Point 1" to "Sampling Point 25" respectively. During the sampling process, use a hammer to strike the ground at a distance of 3 - 5 cm from the sensor to collect the foundation vibration data. Use the left mouse button to check the box to select the effective vibration data with obvious amplitudes in the "Real-time Vibration Time Domain Diagram". After the data is automatically saved, the data collection is completed. Vibration isolation signal collection: Connect the dual-channel sensor. On the "Vibration Isolation Collection" interface, click on "Sampling Point 1" to "Sampling Point 5" in sequence and use the left mouse button to check the box to select the effective data with obvious amplitudes. After the data is automatically saved, the vibration isolation signal data collection is completed. If the amplitude of the data at a certain sampling point is not obvious, the amplitude is chaotic, or other abnormal errors occur during the sampling process, click on that sampling point repeatedly for repeated sampling. The system will delete the measurement data with errors, re-sample and save the data.

[0027] See Figure 10 and Figure 11 The operation process of the data analysis interface of this system is described as follows. The analysis steps are as follows: Step 1: Effective thickness analysis: After the data collection is completed, set the wave velocity on the defect analysis interface, and click on the effective thickness analysis to analyze and process the collected foundation data, automatically generate the foundation effective thickness cloud map, and output the average effective thickness of the foundation. Step 2: Internal defect analysis: On the defect analysis interface, select the data column that needs to be analyzed. After clicking on the defect analysis, analyze the data of the selected column and output the foundation internal defect cloud map. Whether there are obvious internal defects such as cavities and cracks in the foundation can be viewed through different color gamuts of the cloud map. Step 3: Vibration isolation effect analysis: On the vibration isolation detection interface, click on the analysis buttons of the five points in sequence to analyze the vibration isolation effects of each measurement point and output the average attenuation degree of the energy. The vibration isolation effect of the foundation can be evaluated through the energy attenuation degree.

[0028] The above content is only to illustrate the technical idea of the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention fall within the protection scope of the claims of the present invention.

Claims

1. A detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation, characterized in that It includes the following steps: Step 1, Detection of foundation parameters based on the impact echo method: 1.1) On the surface of the machine tool foundation, divide the foundation measurement area according to the projected size of the machine tool base; 1.2) Calibrate the propagation velocity of the vibration wave in the measured area through two sensors on the surface of the measured area V P ; 1.3) Select the specification of the impact hammer according to the excitation waveform of the impact hammer on the ground to be measured; 1.4) Implement excitation along the normal direction of the measurement point, and collect the time-domain vibration signal through the acceleration vibration sensors arranged around the excitation point; 1.5) Extract the dominant frequency matrix of the direct wave and the reflected wave based on the frequency-domain signal after discrete Fourier transform F max , according to the formula H = V p * L / (2 F max *Δ t ), calculate the effective thickness, where L is the distance between the two sensors when calibrating the wave velocity, Δt is the time difference between the signals received by the two sensors, and at the same time, identify the abnormal resonance peaks that can express the internal defect signals in the frequency band of 0.5 - 10 kHz through spectral analysis; Step 2, Evaluation of vibration isolation effect based on dual sensors, including: 2.1) Arrange the first and second acceleration vibration sensors on the vibration source side and the protected side adjacent to the machine tool foundation respectively. The distance between the two sensors is 0.7 m, and the excitation point is 0.1 m away from the first sensor; 2.2) Synchronously collect 5 groups of vibration signals, and calculate the percentage of energy that can be isolated when vibration is transmitted on the vibration source side and the protected side according to the vibration transmissibility η to evaluate the vibration isolation effect of the current foundation. E ​ 2. The detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to claim 1, characterized in that: Step 1.1) According to the projected size of the machine tool base and the size of the surrounding installation space, delimit the rectangular measurement area on the foundation surface, and control the area of the measurement area within 2 - 3 m²; arrange measurement points in the measurement area according to the equal-spacing grid division method, and the distance between measurement points can be dynamically adjusted according to the length-width ratio of the base.

3. The detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to claim 1, characterized in that: Step 1.3) In the area to be measured, by comparing and testing the frequency-domain signal characteristics of different specifications of impact hammers, preferentially select the impact hammer model with a single vibration mode, obvious wave peaks, and the least clutter as the impact hammer for subsequent detection.

4. The detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to claim 1, characterized in that: Step 1.4) Vertically strike the excitation at the center position of each measurement point, and symmetrically arrange the acceleration vibration sensors 30 mm around the excitation point, and synchronously collect the time-domain vibration signal at a sampling frequency not lower than 10 kHz; the acquisition duration of each impact signal is ≥10 ms, and each measurement point is repeatedly collected 3 times and subjected to time-domain averaging processing.

5. The detection method for the thickness, internal defects and vibration isolation effect of a machine tool foundation according to claim 1, characterized in that: Step 1.5) Perform discrete Fourier transform on the collected time-domain signal, extract the main frequency peaks of the direct wave and the reflected wave in the frequency band of 0.5 - 10 kHz; calculate the effective thickness of each measurement point, and after removing the abnormal values deviating from the mean value by ±8%, take the arithmetic mean as the regional average thickness; identify the abnormal resonance peaks in the frequency-domain signal with an amplitude exceeding the background noise by 20 dB and a Q factor > 50 through the matching pursuit algorithm, and judge as the internal defect area in combination with the standard deviation of the thickness distribution ≥12%.

6. The method for detecting the thickness, internal defects and vibration isolation effect of a machine tool foundation according to claim 1, characterized in that: Step 2.1) The vibration source side is the peripheral structure of the foundation, and the protected side is the contact area of the machine tool base. The two sensors are arranged 0.7 m apart along the vibration propagation direction. Use the impact hammer to strike to generate excitation, and collect the energy loss when the vibration signal is transmitted on the vibration source side and the protected side through the two sensors.

7. The method for detecting the thickness, internal defects and vibration isolation effect of a machine tool foundation according to claim 1, characterized in that: Step 2.2) Through the vibration transmissibility η = 20 log( A 2 / A 1) Calculate the vibration isolation effect. When η ≤ -25 dB and the 1 / 3 octave band spectrum attenuation rate ≥ 15 dB, it is determined that the vibration isolation effect in this area meets the standard, where A 1, A 2 are the effective values of the vibration acceleration on the vibration source side and the protected side respectively.

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