A machine tool broken tool monitoring method and system for 3C industry

Abstract

The application provides a machine tool broken tool monitoring method and system for a 3C industry, the monitoring method comprises the following steps: storing vibration signals meeting a set condition in a storage queue; calculating the center frequency of the storage queue meeting a calculation condition; and issuing a broken tool early warning if the center frequency is less than a broken tool threshold value. The application collects vibration signals of a tool and analyzes the frequency characteristics of the vibration signals, and is not simply dependent on the size of the vibration amount, and is more suitable for the characteristics of small tool size, weak electric power signals and small vibration signal amplitude of 3C products; the center frequency of the vibration signals is calculated in real time, and a broken tool abnormality is found in time, so that the response speed of abnormal processing is improved.

Description

TECHNICAL FIELD

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

[0002] With the development of modern manufacturing industry, the 3C (computer, communication and consumer electronics) industry has increasingly high requirements for production efficiency and product quality. As an important production equipment in the 3C industry, the machining precision and stability of numerical control machine tools directly affect the quality of products. However, in the long machining process, tool wear, breakage and other problems are inevitable. Once these problems occur, not only will the machining quality decrease, but also the equipment may be damaged, and even the operation efficiency of the entire production line may be affected.

[0003] The traditional tool state monitoring method mainly relies on manual inspection or simple sensor detection, mainly monitors the size of the vibration quantity, sets the threshold value of the vibration quantity, realizes the alarm of the threshold value, and monitors the working state of the tool through the threshold value. However, for the machining of 3C products (3C products are also called computer, communication and consumer electronic products), the tool characteristics of 3C process are small in size, less than 1mm in diameter, weak in electric power signal during machining, and small in vibration signal amplitude. Therefore, the traditional vibration quantity monitoring method is not suitable for the machining of 3C products. SUMMARY

[0004] To solve the above problems, the present application provides a machine tool broken tool monitoring method and system for 3C industry.

[0005] The main content of the present application includes:

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

[0007] According to the current machining process, 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, and j is the serial number of the storage queue;

[0008] The vibration signal V(x, y, z) meeting the set condition 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, the storage timing t of the current storage queue and the full queue state of the current storage queue are obtained according to the set calculation interval ΔT;

[0010] If the storage timer t is greater than the set calculation interval ΔT or the current storage queue is full, then stop the timer, obtain the frequency f of the current storage queue, calculate the average frequency spectral 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 spectral density Pj corresponding to all storage queues;

[0013] Based on the average frequency spectral density P0 of the current computation queue, the frequency f, and the average frequency spectral density Pi of all storage queues, calculate the centroid frequency C of the current computation queue; where, J represents the number of storage queues;

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

[0015] Preferably, vibration signals V(x,y,z) that meet the set conditions are stored in a pre-created storage queue Qj, which is then used 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.

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

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

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

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

[0022] Get the number M of vibration signals in the current storage queue; if the number M of vibration signals in the current calculation queue is less than the set calculable threshold ME, then use the current storage queue as the storage queue for the next sliding window.

[0023] Preferably, the blade breakage threshold is obtained from simulation experiments or statistical analysis.

[0024] This invention also proposes a machine tool breakage monitoring system for the 3C industry, including 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 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 breakage monitoring method for the 3C industry. The setting module is used to set the breakage threshold and sampling parameters.

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

[0026] The beneficial effects of this invention are as follows: The machine tool breakage monitoring method and system proposed in this invention for the 3C industry collects the vibration signal of the tool and analyzes its frequency characteristics. It does not rely solely on the magnitude of the vibration and is more suitable for the characteristics of small tool size, weak electrical power signal and small vibration signal amplitude of 3C products. By collecting and calculating the center frequency of the vibration signal in real time, the machine tool breakage abnormality can be detected in time, thus improving the response speed of abnormality handling. Attached Figure Description

[0027] Figure 1 This is a flowchart of the present invention. Detailed Implementation

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

[0029] Please combine Figure 1 This invention discloses a method and system for monitoring broken tools in machine tools used in the 3C industry. It addresses the challenges of using traditional broken tool monitoring methods due to the small size of tools, weak electrical power signals, and small vibration signal amplitudes in the 3C industry. Specifically, the machine tool broken tool monitoring system proposed in this invention includes a sampling module, a storage module, a processing module, and a setting module.

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

[0031] The storage module stores vibration signals that meet set conditions in a queue format. Specifically, the storage module contains multiple queues arranged according to the acquisition time, and each queue contains vibration signals that have been filtered by the processing module and meet the set conditions. In one embodiment, the processing module obtains the vibration signals acquired by the acquisition module at set sampling intervals, and calculates the mean square value (RMS) of the corresponding vibration signals. If the mean square (RMS) value of the corresponding vibration signal is greater than the set energy threshold, it is considered to meet the set conditions. The processing module then stores the corresponding vibration signal in the current storage queue. This is done to filter out vibration signals with higher energy for subsequent frequency analysis and to discard data with lower energy, thereby reducing the amount of data processing and ensuring the accuracy of subsequent center of gravity frequency calculation. The energy threshold can be manually input through the setting module. The energy threshold can be obtained through simulation methods or through extensive statistical analysis of data.

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

[0033] The processing module stores 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 the tool at a certain interval, and determines whether the tool is broken by comparing it with the frequency characteristics of the tool when the tool breaks.

[0034] Specifically, since different machining processes have specific frequency characteristics of the cutting tools, the processing module first collects the vibration signal V(x,y,z) of the cutting tool according to the current machining process and at a set sampling interval Δt, creates a storage queue Qj and starts timing, where j is the sequence number of the storage queue; that is, when the acquisition of the cutting tool vibration signal begins, a storage queue is created, and the storage queue has a set length; that is, timing starts from the head of a sliding window, and after acquiring a vibration signal at a 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. If it is greater, it is stored in the corresponding storage queue; if it does not meet the conditions, the vibration signal of the next sampling point is acquired.

[0035] When the current storage queue is full, in this embodiment, the full state of the current storage queue is defined as the number of vibration signals in the current storage queue being M = ΔT / Δt. That is, all sampling points within a sliding window meet the set conditions, and the vibration signals within that sliding window are all stored in the storage queue. The length of the storage queue is set to N, i.e., N = ΔT / Δt. At this point, it indicates that the current storage queue has completed its collection, and frequency analysis can be performed on the sampling period.

[0036] In addition, the processing module simultaneously checks the cumulative time stored in the current storage queue, denoted as storage time t, and determines whether the storage time is greater than the calculation interval ΔT. That is, before the start of the next calculation interval ΔT, the data storage of the current storage queue is completed. Within a sliding window, the number of vibration signals in the storage queue may be equal to or less than the number of sampling points ΔT / Δt within the sliding window. This indicates that a vibration signal in the sampling does not meet the set conditions. In other words, when the current storage queue is not full, the processing module will continue to store vibration signals from the next sampling period. When the next calculation interval arrives, if the storage time t is greater than one sampling period (i.e., greater than one sliding window), it also indicates that the storage queue has completed collection, and frequency analysis can then be performed on the storage queue.

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

[0038] Next, based on the average frequency spectral density P0 of the current computation queue, the frequency f, and the average frequency spectral density Pi of all storage queues, the centroid frequency C of the current computation queue is calculated; where, J represents the number of storage queues.

[0039] Finally, the center frequency of the current calculation queue is compared with the tool breakage threshold set for the current process. If the center frequency of the current calculation queue is less than the tool breakage threshold, a tool breakage 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, wherein the size of the sliding window is T, and T = ΔT.

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

[0042] Get the number M of vibration signals in the current storage queue; if the number M of vibration signals in the current calculation queue is less than the set calculable threshold ME, then use the current storage queue as the storage queue for the next sliding window.

[0043] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for monitoring broken machine tools in the 3C industry, characterized in that, Includes the following steps: According to the current machining process, the vibration signal V(x,y,z) of the tool is collected at 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; Vibration signals V(x,y,z) that meet the set conditions are stored in the created storage queue Qj according to the queue, which is used as the current storage queue Q0. The storage time of the current storage queue is recorded as the storage time t. The length of a single storage queue Q is N; Within the current process, according to the set calculation interval ΔT, obtain the storage time t of the current storage queue and the full status of the current storage queue; If the storage timer t is greater than the set calculation interval ΔT or the current storage queue is full, then stop the timer, obtain the frequency f of the current storage queue, calculate the average frequency spectral density P0 of the current storage queue, and create a new storage queue, which will be used as the current storage queue. Calculate the average frequency spectral density Pj corresponding to all storage queues; Based on the average frequency spectral density P0 of the current computation queue, the frequency f, and the average frequency spectral density Pi of all storage queues, calculate the centroid frequency C of the current computation queue; where, J represents the number of storage queues; The center frequency of the current calculation queue is compared with the tool breakage threshold set for the current process. If the center frequency of the current calculation queue is less than the tool breakage threshold, a tool breakage alarm is issued.

2. The method for monitoring broken machine tools in the 3C industry according to claim 1, characterized in that, Vibration signals V(x,y,z) that meet the set conditions are stored in the created storage queue Qj, which is then used 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.

3. The method for monitoring broken machine tools in 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, wherein the size of the sliding window is T.

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

5. A method for monitoring broken machine tools in the 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: Get the number M of vibration signals in the current storage queue; if the number M of vibration signals in the current calculation queue is less than the set calculable threshold ME, then use the current storage queue as the storage queue for the next sliding window.

6. A method for monitoring broken machine tools in the 3C industry according to claim 1, characterized in that, The blade breakage threshold is obtained through simulation experiments or statistical analysis.

7. A machine tool breakage monitoring system for the 3C industry, characterized in that, The method 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 cutting 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 machine tool breakage monitoring method for the 3C industry as described in any one of claims 1 to 6. The setting module is used to set the breakage threshold and sampling parameters.

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

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