Machine tool broken tool monitoring method and system for 3C industry

Abstract

The invention provides a machine tool broken tool monitoring method and system for the 3C industry, and the method comprises the steps: storing vibration signals meeting a set condition into a storage queue, calculating the gravity center frequency of the storage queue meeting a calculation condition, and giving out a broken tool early warning if the gravity center frequency is smaller than a broken tool threshold value. By collecting the vibration signal of the cutter and analyzing the frequency characteristic of the cutter, the method does not simply depend on the magnitude of the vibration quantity, and is more suitable for the characteristics of small cutter size, weak electric power signal and small vibration signal amplitude of 3C products; by collecting and calculating the center-of-gravity frequency of the vibration signal in real time, the tool breaking abnormity is found in time, and the response speed of abnormity processing is increased.

Description

Technical Field

[0001] The invention relates to the field of machine tool control, and in particular to a machine tool broken tool monitoring method and system for the 3C industry. Background Art

[0002] With the development of modern manufacturing, the 3C (computer, communication and consumer electronics) industry has increasingly higher requirements for production efficiency and product quality. As an important production equipment in the 3C industry, the processing accuracy and stability of CNC machine tools directly affect the quality of products. However, during the long processing process, problems such as tool wear and breakage are inevitable. Once these problems occur, not only will the processing quality decline, but they may also cause equipment damage and even affect the operating efficiency of the entire production line.

[0003] Traditional tool status monitoring methods mostly rely on manual inspection or simple sensor detection, mainly monitoring the magnitude of vibration, setting the threshold of vibration, realizing over-threshold alarm, and monitoring the working status of the tool through threshold monitoring. However, for the machining of 3C products (3C products are also known as computers, communications and consumer electronics), the tool characteristics of 3C process are small size, less than 1 mm in diameter, weak power signal during machining, and small vibration signal amplitude. Therefore, the traditional monitoring method of vibration is not suitable for 3C product processing machine tools. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a machine tool broken tool monitoring method and system for the 3C industry.

[0005] The main contents of the present invention include:

[0006] A machine tool broken tool monitoring method for the 3C industry comprises the following steps:

[0007] According to the current processing procedure, the vibration signal V(x, y, z) of the tool is collected according to the set sampling interval Δt, a storage queue Qj is created and the timing is started, where j is the sequence number of the storage queue;

[0008] The vibration signal V(x, y, z) that meets the set conditions is stored in the created storage queue Qj according to the queue, as the current storage queue Q0, and the storage time of the current storage queue is recorded as the storage timing t; the length of a single storage queue Q is N;

[0009] In the current process, according to the set calculation interval ΔT, the storage timing t of the current storage queue and the full state of the current storage queue are obtained;

[0010] If the storage timing t is greater than the set calculation interval ΔT or the current storage queue is full, stop timing, obtain the frequency f of the current storage queue, calculate the average frequency spectrum density P0 of the current storage queue, and create a new storage queue.

[0011] Set the new storage queue as the current storage queue;

[0012] Calculate the average frequency spectrum density Pj corresponding to all storage queues;

[0013] According to the average frequency spectrum density P0 of the current calculation queue, the frequency f and the average frequency spectrum density Pi of all storage queues, the center frequency C of the current calculation queue is calculated; wherein, J is the number of storage queues;

[0014] The center-of-gravity frequency of the current calculation queue is compared with the tool-breaking threshold set for the current process. If the center-of-gravity frequency of the current calculation queue is less than the tool-breaking threshold, a tool-breaking alarm is issued.

[0015] Preferably, the vibration signal V(x, y, z) that meets the set conditions is stored in a created storage queue Qj according to a queue as the current storage queue Q0; including:

[0016] Calculate the mean square value RMS of the corresponding vibration signal;

[0017] If the mean square value RMS of the corresponding vibration signal is greater than the set energy threshold, it is considered to meet the set conditions, and the corresponding vibration signal is stored in the current storage queue according to the queue.

[0018] Preferably, collecting the vibration signal V(x, y, z) of the tool according to the set sampling interval Δt includes:

[0019] A high-frequency vibration sensor is used to collect the vibration signal of the tool in a sliding window manner, and the size of the sliding window is T.

[0020] Preferably, the full state of the current storage queue is that the number of vibration signals in the current storage queue is M=ΔT / Δt.

[0021] Preferably, if the storage time t is greater than the set calculation interval ΔT, the method further includes:

[0022] The number M of vibration signals in the current storage queue is obtained; if the number M of vibration signals in the current calculation queue is less than the set computable threshold ME, the current storage queue is used as the storage queue of the next sliding window.

[0023] Preferably, the knife-breaking threshold is obtained by simulation experiments or statistical analysis.

[0024] The present invention also proposes a machine tool broken tool monitoring system for the 3C industry, comprising a sampling module, a storage module, a processing module and a setting module, wherein the sampling module is used to collect the vibration signal V(x, y, z) of the tool according to a set sampling interval Δt; the storage module stores the vibration signals that meet the set conditions in a queue; the processing module is used to execute the above-mentioned machine tool broken tool monitoring method for the 3C industry; the setting module is used to set the broken tool threshold and sampling parameters.

[0025] Preferably, the broken knife threshold and sampling parameters are manually entered or output from a trained neural network model.

[0026] The beneficial effects of the present invention are as follows: a machine tool broken tool monitoring method and system proposed by the present invention for the 3C industry, by collecting the vibration signal of the tool and analyzing its frequency characteristics, does not simply rely on the size of the vibration amount, and is more suitable for the characteristics of 3C products with small tool size, weak electric power signal and small vibration signal amplitude; by real-time collection and calculation of the center of gravity frequency of the vibration signal, the broken tool abnormality is discovered in time, thereby improving the response speed of abnormality processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0028] The technical solution protected by the present invention is described in detail below with reference to the accompanying drawings.

[0029] Please combine Figure 1 The present invention discloses a machine tool tool breakage monitoring method and system for the 3C industry, which is proposed for the 3C industry because the tool size is small, the electric power signal is weak, the vibration signal amplitude is small, and the traditional tool breakage monitoring means are not suitable. Specifically, the machine tool tool breakage monitoring system proposed by the present invention includes a sampling module, a storage module, a processing module, and a setting module.

[0030] Among them, the sampling module includes a high-frequency vibration sensor, which can be set on the machine tool spindle or the tool. The high-frequency vibration sensor collects the vibration signal V(x, y, z) of the tool according to the set sampling interval Δt; in one embodiment, the sampling module performs data collection according to a sliding window of a set length, such as the length of the sliding window is 100ms, the sampling interval Δt is 10ms, that is, 10 vibration signals can be collected in one sliding window.

[0031] The storage module stores the vibration signals that meet the set conditions in a queue manner, that is, the storage module stores multiple storage queues according to the collection time, and the vibration signals in each storage queue are vibration signals that meet the set conditions that are screened out by the processing module. In one embodiment, the processing module obtains the vibration signals collected at the set sampling interval by the collection module, and calculates the mean square value RMS of the corresponding vibration signals. If the RMS of the corresponding vibration signal is greater than the set energy threshold, it is considered to meet the set conditions, and the processing module stores the corresponding vibration signal in the current storage queue according to the queue. The purpose of this is to filter out vibration signals with larger energy for subsequent frequency analysis and eliminate data with smaller energy, which reduces the amount of data processing on the one hand and ensures the accuracy of subsequent center of gravity frequency calculation on the other hand. The energy threshold can be manually input through the setting module, and the energy threshold can be obtained through a simulation method or through a large amount of data statistical analysis.

[0032] In addition, corresponding sampling parameters such as sampling interval and calculation interval are also set through the setting module.

[0033] The processing module stores the vibration signals that meet the set conditions into the corresponding storage queue, and performs frequency analysis on the corresponding storage queue according to the set calculation interval ΔT, that is, analyzes the frequency characteristics of a certain interval tool, and compares it with the frequency characteristics of the tool when the tool is broken, so as to determine whether the tool is broken.

[0034] Specifically, since tools of different machining processes have specific frequency characteristics, the processing module first collects the vibration signal V(x, y, z) of the tool according to the set sampling interval Δt based on the current machining process, creates a storage queue Qj and starts timing, where j is the sequence number of the storage queue; that is, when the vibration signal of the tool starts to be collected, a storage queue is created, and the storage queue has a set length; that is, the timing starts from the head of a sliding window, and after obtaining a vibration signal according to the sampling interval Δt, it is first determined whether it meets the set conditions, that is, its mean square value RMS is greater than the set energy threshold, and if so, it is stored in the corresponding storage queue; if it does not meet the conditions, the vibration signal of the next sampling point is obtained.

[0035] When the current storage queue is full, in this embodiment, the full state of the current storage queue is the number of vibration signals in the current storage queue M=ΔT / Δt, that is, all sampling points in a sliding window meet the set conditions, and the vibration signals in the sliding window are stored in the storage queue, and the length of the storage queue is set to N, that is, N=ΔT / Δt. At this time, it means that the current storage queue has been collected, and the frequency analysis of the sampling period can be performed.

[0036] In addition, the processing module simultaneously checks the accumulated timing stored in the current storage queue, recorded as storage timing t, and determines whether the storage timing is greater than the calculation interval ΔT, that is, before the next calculation interval ΔT starts, the data storage of the current storage queue is completed. When the number of vibration signals in the storage queue in a sliding window may be equal to the number of sampling points in a sliding window ΔT / Δt, or may be less than the number of sampling points in a sliding window ΔT / Δt, it means that a certain vibration signal in the sampling does not meet the set conditions. That is, when the current storage queue is not full, the processing module will continue to store the vibration signal in the next sampling period. When the next calculation interval arrives, if the storage timing t is greater than a sampling period, that is, greater than a sliding window, it also means that the storage queue has completed the collection, and the frequency analysis of the storage queue can be performed.

[0037] That is, if the storage timing t is greater than the set calculation interval ΔT or the current storage queue is full, the timing is stopped, the frequency f of the current storage queue is obtained, the average frequency spectrum density P0 of the current storage queue is calculated, and a new storage queue is created, and the new storage queue is used as the current storage queue; at the same time, the average frequency spectrum density Pj corresponding to all storage queues is calculated.

[0038] Next, the center of gravity frequency C of the current calculation queue is calculated according to the average frequency spectrum density P0 of the current calculation queue, the frequency f, and the average frequency spectrum density Pi of all storage queues; wherein, J is the number of storage queues.

[0039] Finally, the center of gravity frequency of the current calculation queue is compared with the tool breaking threshold set for the current process. If the center of gravity frequency of the current calculation queue is less than the tool breaking threshold, a tool breaking alarm is issued.

[0040] In one embodiment, a high-frequency vibration sensor is used to collect the vibration signal of the tool in a sliding window manner, and the size of the sliding window is T, T=ΔT.

[0041] In other embodiments, if the storage time t is greater than the set calculation interval ΔT, the method further includes:

[0042] The number M of vibration signals in the current storage queue is obtained; if the number M of vibration signals in the current calculation queue is less than the set computable threshold ME, the current storage queue is used as the storage queue of the next sliding window.

[0043] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A machine tool broken tool monitoring method for 3C industry, characterized in that: The steps include: According to the current processing procedure, the vibration signal V(x, y, z) of the tool is collected according to the set sampling interval Δt, a storage queue Qj is created and the timing is started, where j is the sequence number of the storage queue; The vibration signal V(x, y, z) that meets the set conditions is stored in the created storage queue Qj according to the queue, as the current storage queue Q0, and the storage time of the current storage queue is recorded as the storage timing t; The length of a single storage queue Q is N; In the current process, according to the set calculation interval ΔT, the storage timing t of the current storage queue and the queue fullness status of the current storage queue are obtained; If the storage timing t is greater than the set calculation interval ΔT or the current storage queue is full, stop timing, obtain the frequency f of the current storage queue, calculate the average frequency spectrum density P0 of the current storage queue, and create a new storage queue as the current storage queue; Calculate the average frequency spectrum density Pj corresponding to all storage queues; According to the average frequency spectrum density P0 of the current calculation queue, the frequency f and the average frequency spectrum density Pi of all storage queues, the center frequency C of the current calculation queue is calculated; wherein, J is the number of storage queues; The center-of-gravity frequency of the current calculation queue is compared with the tool-breaking threshold set for the current process. If the center-of-gravity frequency of the current calculation queue is less than the tool-breaking threshold, a tool-breaking alarm is issued.

2. The machine tool broken tool monitoring method for the 3C industry according to claim 1, characterized in that: The vibration signal V(x, y, z) that meets the set conditions is stored in the created storage queue Qj according to the queue as the current storage queue Q0; including: Calculate the mean square value RMS of the corresponding vibration signal; If the mean square value RMS of the corresponding vibration signal is greater than the set energy threshold, it is considered to meet the set conditions, and the corresponding vibration signal is stored in the current storage queue according to the queue.

3. The machine tool broken tool monitoring method for the 3C industry according to claim 1, characterized in that: The vibration signal V(x,y,z) of the tool is collected according to the set sampling interval Δt, including: A high-frequency vibration sensor is used to collect the vibration signal of the tool in a sliding window manner, and the size of the sliding window is T.

4. The machine tool broken tool monitoring method for the 3C industry according to claim 3 is characterized in that: The full state of the current storage queue is the number of vibration signals in the current storage queue M=ΔT / Δt.

5. The machine tool broken tool monitoring method for 3C industry according to claim 3, characterized in that: If the storage time t is greater than the set calculation interval ΔT, it also includes: The number M of vibration signals in the current storage queue is obtained; if the number M of vibration signals in the current calculation queue is less than the set computable threshold ME, the current storage queue is used as the storage queue of the next sliding window.

6. The machine tool broken tool monitoring method for the 3C industry according to claim 1, characterized in that: The knife-breaking threshold is obtained by simulation experiments or statistical analysis.

7. A machine tool broken tool monitoring system for 3C industry, characterized in that: It includes a sampling module, a storage module, a processing module and a setting module. The sampling module is used to collect the vibration signal V(x, y, z) of the tool according to the set sampling interval Δt; the storage module stores the vibration signals that meet the set conditions in a queue; the processing module is used to execute a machine tool broken tool monitoring method for the 3C industry as described in any one of claims 1 to 6; the setting module is used to set the broken tool threshold and sampling parameters.

8. According to the machine tool tool breakage monitoring system for the 3C industry as described in claim 7, the tool breakage threshold and sampling parameters are manually entered or output by a trained neural network model.

Images