Machine tool anti-collision protection methods, systems, electronic equipment, and computer program products

Abstract

This disclosure provides a machine tool collision avoidance protection method, system, electronic device, and computer program product. The method includes: acquiring a time-synchronized vibration signal of the machine tool spindle and a current signal of its drive motor; extracting time-domain features from the current signal and identifying the operating state of the machine tool spindle based on the time-domain features; in response to the operating state being a rapid movement state, acquiring a signal segment within a first time window from the current signal; performing fluctuation analysis on the signal segment and verifying the operating state based on the fluctuation analysis results; determining the instantaneous impact intensity of the vibration signal; and in response to successful verification and the instantaneous impact intensity exceeding an intensity threshold, triggering a collision protection mechanism. This disclosure deeply fuses two types of universal, low-cost sensor signals—current signals and vibration signals—through intelligent algorithms to achieve a protection effect greater than the sum of its parts (1+1>2), thereby providing low-cost, high-reliability, and multi-model-compatible intelligent collision avoidance protection for machine tools.

Description

Technical Field

[0001] This disclosure relates to the field of industrial manufacturing technology, and in particular to a machine tool anti-collision protection method, system, electronic device, and computer program product. Background Technology

[0002] During CNC machine tool machining, in machine tool debugging, tool setting, and manual operation modes, operators typically use the rapid traverse command (G0) to quickly position the spindle or worktable. At this stage, due to factors such as misoperation, programming errors, and insufficient tool setting accuracy, collisions between the spindle and the workpiece or fixture (commonly known as "tool collisions") are highly likely to occur. Such accidents not only cause tool damage and a permanent decrease in spindle accuracy, but in severe cases, they can also lead to equipment damage and personal injury accidents, significantly increasing production costs and safety risks.

[0003] The common methods and shortcomings of collision protection for CNC machine tools are as follows:

[0004] Single vibration threshold method: This method involves installing a vibration sensor on the machine tool body and setting a fixed vibration amplitude threshold to trigger an over-limit alarm. However, normal cutting, start-up and shutdown operations of the machine tool, as well as the operation of peripheral equipment, all generate strong vibrations, which can easily lead to false triggering and a high false alarm rate, making it difficult to meet the needs of practical engineering applications.

[0005] Load current monitoring method: This method uses the spindle motor current or load power to trigger an over-threshold alarm. However, this method suffers from a trade-off between sensitivity and specificity: if the threshold is set too high, it cannot detect minor collisions; if the threshold is set too low, it frequently triggers false alarms during normal acceleration / deceleration and cutting operations, failing to effectively distinguish between normal high-load machining and abnormal collision conditions.

[0006] High-end dedicated sensing method: This method uses high-precision force sensors, torque sensors, or acoustic emission sensors to directly detect collision force and impact signals. It has high detection accuracy, but it is expensive, complex to install, and requires modification of the spindle or machine tool body structure, making it difficult to popularize and promote in most equipment.

[0007] The CNC system internal signal method: Collision detection is achieved by reading internal status signals such as servo error and following error of the CNC (Computer Numerical Control) system. This solution has poor versatility, is highly dependent on specific CNC system brands and models, and most systems do not expose their underlying real-time signal interfaces, thus limiting its application scope.

[0008] In summary, existing collision protection methods generally suffer from problems such as high false alarm rate, insufficient sensitivity, high cost, poor versatility, and difficulty in modification, making it difficult to meet the actual needs of industrial sites for the safe operation of CNC machine tools. Summary of the Invention

[0009] The technical problem to be solved by this disclosure is to overcome the above-mentioned defects in the prior art and provide a machine tool anti-collision protection method, system, electronic device, and computer program product.

[0010] This disclosure solves the above-mentioned technical problems through the following technical solution:

[0011] Firstly, a machine tool anti-collision protection method is provided, including:

[0012] Acquire the vibration signal of the machine tool spindle and the current signal of its drive motor that are synchronized with the time.

[0013] Extract time-domain features from the current signal and identify the operating state of the machine tool spindle based on the time-domain features;

[0014] In response to the operating state being a rapid movement state, a signal segment within a first time window is obtained from the current signal;

[0015] Fluctuation analysis is performed on the signal segment, and the operating status is verified based on the fluctuation analysis results;

[0016] Determine the instantaneous impact intensity of the vibration signal;

[0017] In response to successful verification and the instantaneous impact intensity being greater than the intensity threshold, a collision protection mechanism is triggered.

[0018] Optionally, the time-domain features include instantaneous pulse width and absolute peak amplitude;

[0019] Identifying the operating state of the machine tool spindle based on the time-domain features includes:

[0020] In response to the instantaneous waveform width and the absolute amplitude peak value satisfying the fast movement determination condition, the operating state is determined to be a fast movement state; the fast movement determination condition includes the instantaneous waveform width falling within a preset waveform width range and the absolute amplitude peak value being greater than a peak value threshold.

[0021] Optionally, in response to the fact that the duration of the instantaneous waveform width and the peak absolute amplitude do not meet the fast movement determination conditions is greater than the duration threshold and / or the number of times is greater than the number of times, the fast movement state is determined to end.

[0022] Optionally, the drive motor is used to drive the machine tool spindle to move in multiple directions;

[0023] Extracting time-domain features from the current signal and identifying the operating state of the machine tool spindle based on the time-domain features includes:

[0024] Time-domain features are extracted from each current signal that drives the machine tool spindle to move in different directions;

[0025] If the time-domain characteristics of at least one current signal satisfy the fast movement determination condition, then the operating state is determined to include the fast movement state.

[0026] Optionally, the fluctuation analysis includes envelope monotonicity analysis and peak-to-peak stability analysis of the signal segment;

[0027] The operational status is verified based on the fluctuation analysis results, including:

[0028] If the monotonicity of the signal segment meets the preset requirements and the coefficient of variation of the peak-to-peak value is less than the coefficient threshold, then the verification is deemed successful.

[0029] Optionally, it also includes:

[0030] In response to the target duration being reached after successful verification, the absolute values ​​of the current signal samples at N points within the second time window are obtained; where N is a positive integer greater than or equal to 2.

[0031] Calculate the mean and standard deviation of the N current signal sampling points;

[0032] A dynamic control boundary for identifying rapid movement states is constructed based on the mean and standard deviation.

[0033] Optionally, determining the instantaneous impact intensity of the vibration signal includes:

[0034] In response to the fact that the amplitude of the latest sampling point of the vibration signal is greater than the amplitude of the adjacent sampling points, the difference between the amplitude of the latest sampling point and the most recent trough is taken as the instantaneous impact intensity.

[0035] In response to the fact that the amplitude of the latest sampling point of the vibration signal is less than the amplitude of the adjacent sampling points, the difference between the amplitude of the most recent peak and the amplitude of the latest sampling point is taken as the instantaneous impact intensity.

[0036] And / or, the protection mechanism includes: emergency braking and / or alarm prompts.

[0037] Secondly, a machine tool anti-collision protection system is provided, including:

[0038] The acquisition module is used to acquire the vibration signal of the machine tool spindle and the current signal of its drive motor that are synchronized with the time.

[0039] A current state identification module is used to extract time-domain features from the current signal and identify the operating state of the machine tool spindle based on the time-domain features;

[0040] The acquisition module is further configured to acquire a signal segment within a first time window from the current signal in response to the running state being a fast-moving state.

[0041] The current state identification module is also used to perform fluctuation analysis on the signal segment and verify the operating state based on the fluctuation analysis results;

[0042] The vibration and impact calculation module is used to determine the instantaneous impact intensity of the vibration signal;

[0043] A joint decision maker is used to trigger a collision protection mechanism in response to a successful verification and the instantaneous impact intensity being greater than an intensity threshold.

[0044] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and for running on the processor, wherein the processor executes the computer program to implement the machine tool anti-collision protection method described in any one of the first aspects.

[0045] Fourthly, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the machine tool anti-collision protection method described in any one of the first aspects.

[0046] Based on common knowledge in the field, the above-mentioned preferred conditions can be combined arbitrarily to obtain various preferred embodiments of this disclosure.

[0047] The positive and progressive effects of this disclosure are as follows: The embodiments of this disclosure propose a directional event capture and linkage mechanism based on operational status perception, which deeply integrates two types of general and low-cost sensor signals, namely current signal and vibration signal, through intelligent algorithms to achieve a protection effect of 1+1>2, thereby providing machine tools with low-cost, high-reliability, and multi-model-compatible intelligent anti-collision protection. Attached Figure Description

[0048] Figure 1 A flowchart illustrating a machine tool anti-collision protection method provided as an exemplary embodiment of this disclosure;

[0049] Figure 2 A flowchart illustrating state fusion during machine tool collision avoidance protection, provided as an exemplary embodiment of this disclosure;

[0050] Figure 3 This is a schematic diagram illustrating the effect of processing a current signal using a machine tool anti-collision protection method provided in an exemplary embodiment of this disclosure;

[0051] Figure 4a A raw waveform diagram of a vibration signal provided as an exemplary embodiment of this disclosure;

[0052] Figure 4b To use the most recent reverse extreme value increment method for Figure 4a The waveform diagram shown is the result of processing the vibration signal;

[0053] Figure 5A schematic diagram of a machine tool anti-collision protection system provided as an exemplary embodiment of this disclosure;

[0054] Figure 6 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of the present disclosure. Detailed Implementation

[0055] The present disclosure is further illustrated below by way of embodiments, but the present disclosure is not limited to the scope of the embodiments described herein.

[0056] The prefixes such as "first" and "second" used in this disclosure are merely for distinguishing different descriptive objects and do not limit the position, order, priority, quantity, or content of the described objects. The use of ordinal numbers and other prefixes used to distinguish descriptive objects in this disclosure does not constitute a limitation on the described objects. The description of the described objects is given in the claims or the context of the embodiments, and should not be construed as an unnecessary limitation. Furthermore, in the description of this embodiment, unless otherwise stated, "multiple" means two or more.

[0057] Figure 1 A flowchart of a machine tool anti-collision protection method provided for an exemplary embodiment of this disclosure, the method including the following steps:

[0058] Step 101: Obtain the vibration signal of the machine tool spindle and the current signal of its drive motor that are synchronized with the time.

[0059] In one embodiment, a current sensor is used to acquire the current signal of the drive motor of the machine tool spindle in real time. The current sensor may be, but is not limited to, a clamp-on current sensor, which is clamped to the power line of the drive motor of the spindle to acquire the current signal.

[0060] In one embodiment, a vibration acceleration sensor is used to collect vibration acceleration signals in real time from key parts of the machine tool spindle. The key parts can be set according to actual needs. The vibration acceleration sensor can be, but is not limited to, a triaxial vibration acceleration sensor, which is mounted on the side of the spindle box via a magnetic base to collect vibration acceleration signals.

[0061] In one embodiment, time synchronization of vibration and current signals is achieved by synchronously acquiring data using two types of sensors. For example, both types of sensors are connected to the same multi-channel data acquisition card, and the sampling frequency is set to 4kHz for both.

[0062] In one embodiment, time synchronization of vibration and current signals is achieved by aligning vibration and current signals acquired at known times.

[0063] Step 102: Extract time-domain features from the current signal and identify the operating status of the machine tool spindle based on the time-domain features.

[0064] The operating states of the machine tool spindle can be set according to actual conditions, including but not limited to at least one of the following: rapid traverse state, cutting state, idle state, prediction state, delay and fault tolerance state, and end-lock state. These operating states can be stored in a finite state machine, which can also store the decision conditions and transition conditions between each operating state.

[0065] Machine tool collision risks typically occur during non-cutting rapid traverse operations, specifically during the execution of rapid traverse commands (G0), such as when an operator triggers a G0 command during machine setup. In this condition, the machine tool only performs axis positioning actions and does not participate in cutting operations; it is a rapid traverse process in a non-cutting state.

[0066] In one embodiment, time-domain features are extracted from the current signal in real time based on a sliding window mechanism.

[0067] In this embodiment, the characteristics of current signals, such as good stability and the ability to clearly characterize the macroscopic motion state of the machine tool, are utilized to accurately identify the rapid movement period of the machine tool with the highest collision risk.

[0068] In this embodiment, by extracting the time-domain features from the current signal, the basic time-domain features are transformed into a stable, reliable, and robust identification result for the complex operating state of the machine tool. This effectively avoids misjudgment of the operating state caused by signal noise and operating condition fluctuations, improves the accuracy and anti-interference capability of operating state identification, and is suitable for real-time monitoring and intelligent determination of the operating state under various operating conditions.

[0069] Step 103: In response to the running state being fast movement state, obtain the signal segment within the first time window from the current signal.

[0070] The window length of the first time window can be set according to the actual situation. For example, the window length can be set to [175ms, 200ms]. The first time window ends at the moment when the machine tool spindle is detected to be in rapid movement or at the current moment, and begins at the moment corresponding to one window length backward from that moment.

[0071] Step 104: Perform fluctuation analysis on the signal segment and verify the operating status based on the fluctuation analysis results.

[0072] Verification passed, confirming the machine tool's final state is rapid traverse. Verification failed, indicating the presence of short-term transient interference.

[0073] The operating state determined based on time-domain features in step 102 is a preliminary judgment result. In this embodiment, when the operating state is determined to be a rapid movement state based on time-domain features, the final state is not directly confirmed. Instead, a prospective analysis stage is entered, where fluctuation analysis of the signal segment is performed to distinguish between the true rapid movement state and short-term transient interference. This avoids misjudgments of the state caused by factors such as motor start-stop, signal glitches, and transient interference, significantly improving the stability, reliability, and anti-interference capability of operating state identification, and providing an accurate and reliable time window for subsequent machine tool collision protection.

[0074] Step 105: Determine the instantaneous impact intensity of the vibration signal.

[0075] Instantaneous impact intensity is used to characterize the degree of instantaneous change in vibration signal at the current sampling point, reflecting the instantaneous impact magnitude of vibration signal.

[0076] Step 106: In response to successful verification and instantaneous impact intensity exceeding the intensity threshold, the collision protection mechanism is triggered.

[0077] The strength threshold is set according to the rigidity of the machine tool, for example, the strength threshold TH. impact =10.

[0078] An instantaneous impact intensity greater than the intensity threshold indicates that a severe instantaneous impact event has been detected.

[0079] In one embodiment, the protection mechanism includes: emergency braking and / or alarm prompts.

[0080] In this embodiment, collision risk is determined based on a dual-condition joint assessment. Specifically, a collision risk requiring emergency protection is only identified when both the machine tool is in a rapid movement state and a severe, instantaneous impact event is detected. If the machine tool is in a cutting state (not in a rapid movement state), the protection mechanism is not triggered even if a severe, instantaneous impact event (large vibration amplitude) is detected. Similarly, if the machine tool is in a rapid movement state but no severe, instantaneous impact event is detected (stable vibration signal), the protection mechanism is also not triggered. This fundamentally eliminates the potential for false alarms during normal operating conditions such as cutting and spindle acceleration / deceleration, significantly improving the reliability of the collision protection.

[0081] This embodiment proposes a directional event capture and linkage mechanism based on operational status perception. It deeply integrates two types of universal and low-cost sensor signals, namely current signals and vibration signals, through intelligent algorithms to achieve a protection effect of 1+1>2, thereby providing machine tools with low-cost, high-reliability, and multi-model-compatible intelligent anti-collision protection.

[0082] In one embodiment, a hierarchical judgment process is adopted, which first analyzes the current signal and then analyzes the vibration signal. If the preceding verification fails, the process is terminated directly without having to perform vibration signal analysis, thereby reducing computational overhead.

[0083] In one embodiment, steps 102-104 are executed synchronously with step 105, thereby making full use of system processing resources, shortening the overall identification time, improving the real-time performance of collision risk identification without increasing hardware overhead, ensuring the response speed of collision detection, and meeting the high real-time and high reliability monitoring requirements of industrial sites.

[0084] In one embodiment, the verification result in step 104 is represented by a high-confidence binary signal:

[0085] G0_Flag[t] = 1, indicating that the final state of the machine tool is "rapid traverse state";

[0086] G0_Flag[t]=0 indicates that the final state of the machine tool is not "rapid traverse state";

[0087] In this embodiment, the binary signal serves as the enabling basis for the entire linkage anti-collision protection. Only during the period when G0_Flag[t]=1, subsequent vibration and impact monitoring has the authority to trigger the protection mechanism, thereby eliminating the possibility of false alarms under normal working conditions such as cutting and acceleration / deceleration.

[0088] In one embodiment, the time-domain characteristics include instantaneous pulse width and peak absolute amplitude. The instantaneous pulse width is determined based on the number of sampling points between two adjacent zero-crossings in the current signal, or based on the time interval between two adjacent zero-crossings in the current signal.

[0089] In step 102, the step of identifying the operating state of the machine tool spindle includes: in response to the instantaneous waveform width and absolute amplitude peak value satisfying the rapid traverse determination condition, determining the operating state as a rapid traverse state.

[0090] The criteria for determining rapid movement include an instantaneous waveform width falling within a preset waveform width range and an absolute amplitude peak value exceeding a peak threshold. The preset waveform width range and peak threshold can be set according to actual conditions. For example, the preset waveform width range is [0, 125ms], and the peak threshold range is [10, 30].

[0091] In this embodiment, the operating state of the machine tool spindle is identified based on multimodal time-domain features. This can integrate the complementary characteristics of various time-domain features, ensuring high computational efficiency and strong real-time performance while significantly improving the accuracy and robustness of state differentiation. It can effectively distinguish between normal working conditions and abnormal impacts, and in principle avoid misjudgments caused by cutting, acceleration and deceleration, etc.

[0092] The following describes the process of extracting multimodal temporal features.

[0093] The discrete sequence I[n] of the sampled current signal is processed in real time, and three time-domain feature streams are generated:

[0094] (1) Zero-crossing event flow: Detects the microscopic dynamic reversal point of the signal, defined as:

[0095] ;

[0096] Where n represents the time of the discrete sequence of the current signal.

[0097] when A zero-crossing event is marked at each point to segment the waveform period. The operating speed of the spindle drive motor is positively correlated with the number of zero-crossing events.

[0098] (2) Instantaneous pulse width characteristic flow: Between two adjacent zero-crossing events, the number of sampling points in the current half-cycle is counted and denoted as W. k It reflects the instantaneous local frequency of circuit signal oscillation. A legitimate fast operating state requires W... k It falls within the preset bandwidth range (a physical constraint range determined empirically):

[0099] W min ≤W k ≤W max

[0100] Among them, W min With W max These are the upper and lower limits of the preset wavewidth range, determined by the dynamic characteristics of the machine tool motor-mechanical system.

[0101] (3) Local amplitude envelope current: Calculate the absolute amplitude peak value A of the current signal within the sliding time window L. m This serves as a representation of the energy level within the sliding time window:

[0102] ;

[0103] Where i represents the loop index (traversal variable) within the sliding time window, used to indicate which sampling point in the window is currently being checked; m represents the index of the current sampling point, which is fixed and represents the current time (the right endpoint of the sliding time window).

[0104] Assuming the current time m=100 and the window length L=50, the above formula expands to:

[0105] A 100 =max{∣I

[51] ∣, ∣I

[52] ∣, …, ∣I

[100] ∣};

[0106] Here, i takes values ​​of 51, 52, 53, …, 100, which are used to iterate through each sampling point within the sliding time window.

[0107] The sliding time window L can be set to a window length of 75ms, but is not limited to 75ms, with a step size of 1 sampling point.

[0108] In this embodiment, the current signal is converted from a time-domain waveform into a multi-dimensional feature stream, and an online, accurate, and robust identification of the machine tool's rapid movement state is achieved through a designed hybrid drive state machine. This embodiment avoids the complexity and real-time lag problems of traditional frequency domain analysis, directly extracting the essence of the working condition from the time-domain dynamic characteristics. The identification process is efficient and stable.

[0109] In one embodiment, fluctuation analysis includes envelope monotonicity analysis and peak-to-peak stability analysis of the signal segment. Step 104, which verifies the operating state based on the fluctuation analysis results, includes: if the monotonicity of the signal segment meets preset requirements and the coefficient of variation of the peak-to-peak value is less than a coefficient threshold, then the verification is deemed successful.

[0110] The preset requirements and coefficient thresholds can be set according to the actual situation.

[0111] The process of fluctuation analysis will be further explained below.

[0112] Take the signal segment S within the first time window pre Analysis:

[0113] Criterion 1: Envelope Monotonicity Analysis

[0114] S pre Divide the data into M sub-segments and calculate the maximum absolute amplitude sequence E1, E2, ..., E of each sub-segment. M M can be set according to the actual situation, for example, M=8.

[0115] Define the envelope rate of change R and the index of the location of the maximum amplitude P. max :

[0116] If (P) is satisfied max ≥T h )∧(R≥R th ), or (P max <T h )∧(max(E Th:M )>0.5•max(E i ))∧(R>R th If the current signal is unstable, it is determined that the state misjudgment may have been caused by factors such as motor start-stop, signal glitches, and instantaneous interference in step 102, meaning that the result of step 102 is unreliable.

[0117] Among them, T h Threshold Index ;R th =50%.

[0118] Criterion 2: Peak-to-peak stability analysis

[0119] Calculate S pre The peak-to-peak sequence {PP1,PP2,…} of the continuous waveform period within the inner peak.

[0120] If its coefficient of variation CV exceeds the threshold C th If the signal is unstable and oscillating, it may be due to factors such as motor start-stop, signal glitches, and instantaneous interference that cause misjudgment of the state in step 102, meaning that the result of step 102 is unreliable.

[0121] In this embodiment, the pre-trigger verification mechanism based on dual stability criteria allows the current signal to proceed to subsequent processing only after the result of step 102 has been verified by the dual stability criteria. This effectively eliminates the influence of instantaneous signal fluctuations, random interference, and non-stationary processes, further improving the accuracy and robustness of state differentiation and reducing the probability of false triggering of the collision avoidance protection mechanism.

[0122] In one embodiment, a fault-tolerant state continuous monitoring and delay mechanism is implemented. Specifically, the method further includes: determining the end of the fast movement state in response to the duration of the instantaneous pulse width and absolute amplitude peak value not meeting the fast movement determination conditions being greater than a duration threshold and / or the number of times being greater than a number threshold.

[0123] The duration threshold and the number of times threshold can be set according to the actual situation.

[0124] The following section further explains the implementation process of the fault-tolerant state continuous monitoring and delay mechanism.

[0125] After confirming that the machine tool has entered rapid traverse mode, it enters continuous monitoring mode. A "delay mechanism" is introduced at this stage to address unavoidable momentary distortions or loss of signal, effectively improving the stability and fault tolerance of status recognition.

[0126] Define tolerance counter C delay and duration threshold T delay .

[0127] During the duration of the state:

[0128] The counter is reset to zero whenever the instantaneous pulse width and the peak absolute amplitude meet the fast-movement judgment condition. delay ←0;

[0129] If the instantaneous pulse width and absolute amplitude peak value do not meet the fast-moving judgment conditions (e.g., the instantaneous pulse width does not fall within the preset pulse width range and / or the absolute amplitude peak value is less than or equal to the peak value threshold), then C is activated or accumulated. delay ←C delay +1;

[0130] If C delay ≤T delay The determination to maintain a rapid movement state tolerates brief anomalies.

[0131] If the abnormality persists, causing C delay >T delay If so, it is determined that the fast movement state has ended.

[0132] In this embodiment, a fault-tolerant continuous state monitoring and delayed confirmation mechanism is adopted, which can effectively resist unexpected interference such as signal noise and transient distortion, avoid misjudgment of state and false triggering of protection mechanism due to short-term abnormal signals, significantly improve the stability, reliability and robustness of the state recognition process, and ensure that the collision protection can still operate stably and accurately under complex working conditions.

[0133] In one embodiment, the drive motor is used to drive the machine tool spindle to move in multiple directions. The step of extracting time-domain features from the current signal and identifying the operating state of the machine tool spindle based on the time-domain features includes: extracting time-domain features from each current signal that drives the machine tool spindle to move in different directions; and determining that the operating state includes a rapid traverse state in response to the time-domain features of at least one current signal satisfying the rapid traverse determination condition.

[0134] See Figure 2 and Figure 3 In this embodiment, the states of the machine tool in three motion directions (e.g., X, Y, and Z axes) are simultaneously calculated, and the states in all three directions are ultimately fused to represent the operating state of the machine tool spindle. The signals from each motion direction are first analyzed independently, and then fused. See also... Figure 3 The figure shows the motion state of the spindle along each direction of motion. Red indicates rapid movement, blue indicates machining, and yellow indicates stationary state.

[0135] The fusion logic is as follows:

[0136] *||*|| Fast move = Fast move;

[0137] still&still&still=still;

[0138] Processing &! Quick Move &! Quick Move = Processing;

[0139] The above fusion logic indicates that: as long as any axis is identified as being in rapid traverse state, the machine tool spindle is in rapid traverse state; the machine tool spindle is in a stationary state only when all axes are stationary; and the machine tool spindle is in a machining state when at least one axis is in machining state and the other axes are in non-rapid traverse state.

[0140] In one embodiment, the priority of each state is defined as: fast movement > processing > stationary, to ensure clear and conflict-free state determination when switching between multiple working conditions, prioritize response to the higher-risk fast movement state, avoid identification confusion caused by overlapping working conditions, and further improve the reliability and real-time performance of collision protection.

[0141] In one embodiment, the method further includes: in response to the target duration being reached after successful verification, acquiring the absolute values ​​of N current signal sampling points within a second time window, calculating the mean and standard deviation of the N current signal sampling points, and constructing a dynamic control boundary for identifying the rapid movement state based on the mean and standard deviation. Here, N is a positive integer greater than or equal to 2.

[0142] In this embodiment, an adaptive termination boundary based on statistical process control is adopted, which can dynamically adjust the judgment threshold according to the actual statistical characteristics of the signal, and effectively judge the result point of the fast movement state.

[0143] The specific implementation process is described below.

[0144] After a period of rapid movement, the machine tool automatically enters an adaptive learning mode to establish a dynamic judgment threshold for the current specific motion process.

[0145] Process modeling: Construct a sequence of absolute signal values ​​from the N most recent current signal sampling points.

[0146] X = |I[t-N+1]|,…, I[t]|.

[0147] Parameter estimation: Calculate the sample mean μ and sample standard deviation σ of the sequence.

[0148] Control Boundary Generation: Constructing Asymmetric Dynamic Control Boundaries

[0149] UCL = μ + k u •σ,LCL=μ-k l •σ;

[0150] Where UCL is the upper control limit of the dynamic control boundary, LCL is the lower control limit of the dynamic control boundary, and k u and k l This is an adjustable coefficient. L is the window length of the sliding time window. k l ku You can set it yourself according to the actual situation, k l =0.5, k u =3.5.

[0151] Termination criterion: Real-time monitoring of the current signal I[t]. If I[t]≥UCL or |I[t]|≤LCL, the determination process is out of control, that is, the characteristics of the rapid movement state have undergone a fundamental change, and a state termination signal is immediately issued.

[0152] In this embodiment, statistical process control theory is applied to real-time signal segmentation, transforming the determination of the state end point from a fixed threshold to an adaptive intelligent decision that matches the statistical characteristics of the current signal, effectively improving the accuracy of state recognition.

[0153] In one embodiment, the instantaneous impact intensity is calculated based on the most recent reverse extreme value increment method, and step 105 specifically includes:

[0154] Since the amplitude of the latest sampling point of the vibration signal is greater than the amplitude of the adjacent sampling points, the difference between the amplitude of the latest sampling point and the nearest trough is taken as the instantaneous impact intensity.

[0155] Since the amplitude of the latest sampling point of the vibration signal is less than the amplitude of the adjacent sampling points, the difference between the amplitude of the most recent peak and the amplitude of the latest sampling point is taken as the instantaneous impact intensity.

[0156] The most recent trough is the local trough closest to the latest sampling point. The most recent peak is the local peak closest to the latest sampling point.

[0157] In this embodiment, the most recent trough and most recent peak are tracked and maintained in real time.

[0158] In this embodiment, see Figure 4a and Figure 4b The algorithm for calculating instantaneous impact intensity has high-pass filtering characteristics: for continuous vibration signals such as cutting vibration with high amplitude but slow change, the output value of instantaneous impact intensity is small; while for instantaneous impact signals such as collision with drastic amplitude changes, the output value of instantaneous impact intensity will be instantly amplified into a sharp pulse, thereby significantly improving the signal-to-noise ratio of the impact signal and facilitating effective identification.

[0159] In one embodiment, while implementing the protection mechanism, dual-channel raw data (vibration signal and current signal) and intermediate variables for a period of time before and after the accident are locked and stored for post-accident analysis and system optimization.

[0160] The following example, using the manual operation mode, will further explain the process of machine tool anti-collision protection.

[0161] a. In manual operation mode, the operator enters the command "G0 Z-100." to make the spindle move downwards quickly for tool setting.

[0162] b. Current Analysis: When the spindle drive motor starts and accelerates, the current surges. After verification using dual stability criteria, the instability of the current signal is confirmed, and it is filtered out. After the drive motor enters a constant speed rapid traverse, the current signal exhibits stable periodic fluctuations. After verification using dual stability criteria, it is confirmed that the spindle has entered a rapid traverse state, and G0_Flag[t] = 1 is output.

[0163] c. Vibration Monitoring: During the period G0_Flag[t] = 1, the instantaneous impact intensity of the vibration signal is continuously calculated. Since the spindle moves smoothly, the output value of the instantaneous impact intensity fluctuates slightly around zero.

[0164] d. Impact Occurrence and Judgment: The spindle accidentally contacts the workpiece, generating a momentary, severe vibration. The output value of the momentary impact intensity is a sharp pulse that is far higher than the intensity threshold.

[0165] e. Linked Trigger: Condition 1 (G0_Flag[t] = 1) and Condition 2 (instantaneous impact intensity greater than the intensity threshold) are simultaneously met. The joint decision-maker takes effect immediately and executes the protection mechanism.

[0166] f. Emergency stop execution: An emergency stop signal is issued within 2 milliseconds, the machine tool drive power is cut off, and the spindle is stopped before substantial damage occurs.

[0167] g. Post-event process data: Before the trigger, the current signal was stable and in a rapid movement state, and the vibration impact curve showed a significant single peak, which could completely reproduce the process of this collision accident.

[0168] Corresponding to the aforementioned embodiments of machine tool anti-collision protection methods, this disclosure also provides embodiments of machine tool anti-collision protection systems.

[0169] Figure 5 A schematic diagram of a machine tool anti-collision protection system provided for an exemplary embodiment of this disclosure, the system comprising:

[0170] The current state identification module 51 is used to acquire the current signal of the drive motor of the machine tool spindle, extract time-domain features from the current signal, and identify the operating state of the machine tool spindle based on the time-domain features.

[0171] The current state recognition module is also used to obtain a signal segment within a first time window from the current signal in response to the running state being a fast movement state.

[0172] The current state identification module is also used to perform fluctuation analysis on the signal segment and verify the operating state based on the fluctuation analysis results;

[0173] The vibration and impact calculation module 52 is used to acquire the vibration signal of the machine tool spindle and determine the instantaneous impact intensity of the vibration signal; the vibration signal is synchronized with the current signal in time.

[0174] The joint decision 53 is used to trigger the collision protection mechanism in response to the verification being passed and the instantaneous impact intensity being greater than the intensity threshold.

[0175] In one embodiment, all the above modules are integrated into a finite state machine driven by events (zero crossing, exceeding limits) and time (delay timing, locking timing). This state machine defines states such as "idle," "predictive," "G0 running," "delayed fault tolerance," and "lockout," as well as all the rigorous transition conditions between them. It is this highly coordinated, non-obvious state machine design that transforms simple time-domain characteristics into stable and reliable identification of complex operating states.

[0176] In one embodiment, the time-domain features include instantaneous pulse width and absolute peak amplitude;

[0177] When identifying the operating state of the machine tool spindle based on the time-domain features, the current state identification module is specifically used for:

[0178] In response to the instantaneous waveform width and the absolute amplitude peak value satisfying the fast movement determination condition, the operating state is determined to be a fast movement state; the fast movement determination condition includes the instantaneous waveform width falling within a preset waveform width range and the absolute amplitude peak value being greater than a peak value threshold.

[0179] In one embodiment, the current state identification module is further configured to: determine the end of the fast movement state in response to the fact that the duration of the instantaneous pulse width and the absolute amplitude peak value does not meet the fast movement determination condition is greater than the duration threshold and / or the number of times is greater than the number of times threshold.

[0180] In one embodiment, the drive motor is used to drive the machine tool spindle to move in multiple directions;

[0181] The current status identification module is specifically used for:

[0182] Time-domain features are extracted from each current signal that drives the machine tool spindle to move in different directions;

[0183] If the time-domain characteristics of at least one current signal satisfy the fast movement determination condition, then the operating state is determined to include the fast movement state.

[0184] In one embodiment, the fluctuation analysis includes envelope monotonicity analysis and peak-to-peak stability analysis of the signal segment;

[0185] When verifying the operating state based on the fluctuation analysis results, the current state identification module is specifically used for:

[0186] If the monotonicity of the signal segment meets the preset requirements and the coefficient of variation of the peak-to-peak value is less than the coefficient threshold, then the verification is deemed successful.

[0187] In one embodiment, the current state identification module is also used for:

[0188] In response to the target duration being reached after successful verification, the absolute values ​​of the current signal samples at N points within the second time window are obtained; where N is a positive integer greater than or equal to 2.

[0189] Calculate the mean and standard deviation of the N current signal sampling points;

[0190] A dynamic control boundary for identifying rapid movement states is constructed based on the mean and standard deviation.

[0191] In one embodiment, the vibration and shock calculation module is specifically used for:

[0192] In response to the fact that the amplitude of the latest sampling point of the vibration signal is greater than the amplitude of the adjacent sampling points, the difference between the amplitude of the latest sampling point and the most recent trough is taken as the instantaneous impact intensity.

[0193] In response to the fact that the amplitude of the latest sampling point of the vibration signal is less than the amplitude of the adjacent sampling points, the difference between the amplitude of the most recent peak and the amplitude of the latest sampling point is taken as the instantaneous impact intensity.

[0194] And / or, the protection mechanism includes: emergency braking and / or alarm prompts.

[0195] In one embodiment, the system further includes a control signal output and recording module. The control signal output and recording module is used for emergency stop execution and event recording.

[0196] For the system embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs.

[0197] Figure 6This is a schematic diagram of the structure of an electronic device according to an example embodiment of the present disclosure. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the machine tool anti-collision protection method described in any of the above embodiments. Figure 6 The electronic device 60 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0198] like Figure 6 As shown, the electronic device 60 can be manifested as a general-purpose computing device, such as a server device. The components of the electronic device 60 may include, but are not limited to: at least one processor 61, at least one memory 62, and a bus 63 connecting different system components (including memory 62 and processor 61).

[0199] Bus 63 includes a data bus, an address bus, and a control bus.

[0200] The memory 62 may include volatile memory, such as random access memory (RAM) 621 and / or cache memory 622, and may further include read-only memory (ROM) 623.

[0201] The memory 62 may also include a program tool 625 (or utility) having a set (at least one) program module 624, such program module 624 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0202] The processor 61 executes various functional applications and data processing by running computer programs stored in the memory 62, such as the machine tool anti-collision protection method provided in any of the above embodiments.

[0203] Electronic device 60 can also communicate with one or more external devices 64 (e.g., keyboard, pointing device, etc.). This communication can be performed through input / output (I / O) interface 65. Furthermore, electronic device 60 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public network, such as the Internet) via network adapter 66. As shown, network adapter 66 communicates with other modules of electronic device 60 via bus 63. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 60, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems.

[0204] It should be noted that although several units / modules or sub-units / modules of the electronic device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0205] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the machine tool anti-collision protection method provided in any of the above embodiments.

[0206] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0207] This disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the machine tool anti-collision protection method described in any of the above embodiments.

[0208] The program code for executing the computer program product of this disclosure can be written in any combination of one or more programming languages, and the program code can be executed entirely on a user device, partially on a user device, as a stand-alone software package, partially on a user device and partially on a remote device, or entirely on a remote device.

[0209] While specific embodiments of this disclosure have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of this disclosure is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of this disclosure, but all such changes and modifications fall within the scope of protection of this disclosure.

Claims

1. A machine tool anti-collision protection method, characterized in that, include: Acquire the vibration signal of the machine tool spindle and the current signal of its drive motor that are synchronized with the time. Extract time-domain features from the current signal and identify the operating state of the machine tool spindle based on the time-domain features; In response to the operating state being a rapid movement state, a signal segment within a first time window is obtained from the current signal; Fluctuation analysis is performed on the signal segment, and the operating status is verified based on the fluctuation analysis results; Determine the instantaneous impact intensity of the vibration signal; In response to successful verification and the instantaneous impact intensity being greater than the intensity threshold, a collision protection mechanism is triggered.

2. The machine tool anti-collision protection method according to claim 1, characterized in that, The time-domain characteristics include instantaneous pulse width and absolute peak amplitude; Identifying the operating state of the machine tool spindle based on the time-domain features includes: In response to the instantaneous waveform width and the absolute amplitude peak value satisfying the fast movement determination condition, the operating state is determined to be a fast movement state; The rapid movement determination conditions include the instantaneous wavelength falling within a preset wavelength range and the absolute amplitude peak value being greater than a peak value threshold.

3. The machine tool anti-collision protection method according to claim 2, characterized in that, If the duration of the instantaneous waveform width and the peak absolute amplitude do not meet the fast movement determination conditions is greater than the duration threshold and / or the number of occurrences is greater than the number of occurrences threshold, the fast movement state is determined to end.

4. The machine tool anti-collision protection method according to claim 1, characterized in that, The drive motor is used to drive the machine tool spindle to move in multiple directions; Extracting time-domain features from the current signal and identifying the operating state of the machine tool spindle based on the time-domain features includes: Time-domain features are extracted from each current signal that drives the machine tool spindle to move in different directions; If the time-domain characteristics of at least one current signal satisfy the fast movement determination condition, then the operating state is determined to include the fast movement state.

5. The machine tool anti-collision protection method according to claim 1, characterized in that, The fluctuation analysis includes envelope monotonicity analysis and peak-to-peak stability analysis of the signal segment. The operational status is verified based on the fluctuation analysis results, including: If the monotonicity of the signal segment meets the preset requirements and the coefficient of variation of the peak-to-peak value is less than the coefficient threshold, then the verification is deemed successful.

6. The machine tool anti-collision protection method according to any one of claims 1-5, characterized in that, Also includes: In response to the target duration being reached after successful verification, the absolute values ​​of the current signal samples at N points within the second time window are obtained; where N is a positive integer greater than or equal to 2. Calculate the mean and standard deviation of the N current signal sampling points; A dynamic control boundary for identifying rapid movement states is constructed based on the mean and standard deviation.

7. The machine tool anti-collision protection method according to any one of claims 1-5, characterized in that, Determining the instantaneous impact intensity of the vibration signal includes: In response to the fact that the amplitude of the latest sampling point of the vibration signal is greater than the amplitude of the adjacent sampling points, the difference between the amplitude of the latest sampling point and the most recent trough is taken as the instantaneous impact intensity. In response to the fact that the amplitude of the latest sampling point of the vibration signal is less than the amplitude of the adjacent sampling points, the difference between the amplitude of the most recent peak and the amplitude of the latest sampling point is taken as the instantaneous impact intensity. And / or, the protection mechanism includes: emergency braking and / or alarm prompts.

8. A machine tool anti-collision protection system, characterized in that, include: The current state recognition module is used to acquire the current signal of the drive motor of the machine tool spindle, extract time-domain features from the current signal, and identify the operating state of the machine tool spindle based on the time-domain features. The current state recognition module is also used to obtain a signal segment within a first time window from the current signal in response to the running state being a fast movement state. The current state identification module is also used to perform fluctuation analysis on the signal segment and verify the operating state based on the fluctuation analysis results; The vibration and impact calculation module is used to acquire the vibration signal of the machine tool spindle and determine the instantaneous impact intensity of the vibration signal; the vibration signal is synchronized with the current signal in time. A joint decision maker is used to trigger a collision protection mechanism in response to a successful verification and the instantaneous impact intensity being greater than an intensity threshold.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and for running on the processor, characterized in that, When the processor executes the computer program, it implements the machine tool anti-collision protection method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the machine tool anti-collision protection method as described in any one of claims 1-7.

Images