Tool monitoring system and method, data processing platform, monitoring terminal and medium

Abstract

This invention discloses a tool monitoring system and method, a data processing platform, a monitoring terminal, and a medium. The data processing platform of the tool monitoring system determines the operating current corresponding to each working cycle from the current data based on the rotational speed data collected by the monitoring terminal; it then performs curve fitting based on the operating current to obtain an initial fitting curve; finally, it determines a simulation fitting curve and an alarm threshold based on all the initial fitting curves; and the monitoring terminal acquires the simulation fitting curve and the alarm threshold, and monitors the real-time operating condition of the tool based on these parameters. This invention adaptively generates different simulation fitting curves and alarm thresholds for different tool milling scenarios, improving monitoring accuracy and shortening the model adjustment cycle.

Description

Technical Field

[0001] This invention relates to the field of tool monitoring technology, and in particular to a tool monitoring system and method, a data processing platform, a monitoring terminal, and a medium. Background Technology

[0002] Currently, when monitoring the working status of milling cutters on equipment, a monitoring terminal is typically installed next to the equipment. This terminal displays the cutter's status in real time for monitoring and alarm purposes. However, this approach has several drawbacks: the monitoring terminal only monitors based on the real-time display and cannot trace the cutter's historical working status. Furthermore, the operating parameters and cutting materials vary for each piece of equipment, leading to inaccurate monitoring results and false alarms. Summary of the Invention

[0003] This invention provides a tool monitoring system and method, a data processing platform, a monitoring terminal, and a medium to solve problems such as inaccurate monitoring results in the prior art.

[0004] A tool monitoring system includes a monitoring terminal and a data processing platform; the monitoring terminal is used to collect tool operating condition data within a target time period and report it to the data processing platform; the operating condition data includes rotational speed data and current data;

[0005] The data processing platform is used for:

[0006] The operating current corresponding to each working cycle is determined from the current data based on the rotation speed data;

[0007] Based on curve fitting of all the operating currents, multiple initial fitting curves corresponding one-to-one with each of the operating cycles are obtained;

[0008] Based on all the initial fitting curves, determine the simulation fitting curves and alarm thresholds for monitoring the real-time operating conditions of the tool.

[0009] The monitoring terminal is also used to: acquire the simulation fitting curve and alarm threshold, and monitor the real-time working condition of the tool based on the simulation fitting curve and alarm threshold.

[0010] A tool monitoring method, applied to a data processing platform, the tool monitoring method comprising:

[0011] Receives operating condition data within a target time period collected by the monitoring terminal; the operating condition data includes speed data and current data;

[0012] The operating current corresponding to each working cycle is determined from the current data based on the rotation speed data;

[0013] Based on curve fitting of all the operating currents, multiple initial fitting curves corresponding one-to-one with each of the operating cycles are obtained;

[0014] Based on all the initial fitting curves, a simulation fitting curve and an alarm threshold are determined for monitoring the real-time operating condition of the tool, so that the monitoring terminal can acquire the simulation fitting curve and the alarm threshold, and monitor the real-time operating condition of the tool based on the simulation fitting curve and the alarm threshold.

[0015] A tool monitoring method, applied to a monitoring terminal, includes:

[0016] The simulation fitting curve and alarm threshold are obtained, and the real-time operating condition of the tool is monitored based on the simulation fitting curve and alarm threshold. The simulation fitting curve and alarm threshold are determined as follows: After the data processing platform receives the operating condition data collected and reported by the monitoring terminal within the target time period, the working current corresponding to each working cycle is determined from the current data in the operating condition data based on the rotation speed data in the operating condition data; curve fitting is performed based on all the working currents to obtain multiple initial fitting curves that correspond one-to-one with each of the working cycles; the simulation fitting curve and alarm threshold used for monitoring the real-time operating condition of the tool are determined based on all the initial fitting curves.

[0017] A data processing platform for executing the tool monitoring method.

[0018] A monitoring terminal for executing the tool monitoring method.

[0019] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described tool monitoring method.

[0020] In the aforementioned tool monitoring system and method, data processing platform, monitoring terminal, and medium, the monitoring terminal collects tool operating condition data within a target time period and reports it to the data processing platform. The data processing platform determines the operating current corresponding to each working cycle from the current data based on the rotational speed data. It then performs curve fitting based on all the operating currents to obtain multiple initial fitting curves corresponding to each working cycle. Finally, it determines a simulation fitting curve and an alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitting curves. The monitoring terminal is further configured to: acquire the simulation fitting curve and the alarm threshold, and monitor the real-time operating condition of the tool based on the simulation fitting curve and the alarm threshold.

[0021] The tool monitoring system of this invention can collect tool operating parameters for any milling scenario and generate simulation fitting curves and alarm thresholds based on the collected speed and current data. It then uses these simulation fitting curves and alarm thresholds to accurately monitor the real-time operating condition of the tool. In other words, this invention can adaptively adjust and generate different simulation fitting curves and alarm thresholds for different milling scenarios, improving monitoring accuracy. It also shortens the model adjustment cycle after changing the milling scenario, making the machining cycle controllable. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a schematic diagram of a tool monitoring system in one embodiment of the present invention;

[0024] Figure 2 This is a diagram showing the correspondence between rotational speed data, current data, and time data in one embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram illustrating the correspondence between the simulation curve and the real-time current in one embodiment of the present invention;

[0026] Figure 4 This is a flowchart of a tool monitoring method in one embodiment of the present invention;

[0027] Figure 5 This is a flowchart of a tool monitoring method in another embodiment of the present invention;

[0028] Figure 6 This is a schematic diagram of a computer device according to an embodiment of the present invention.

[0029] The reference numerals in the accompanying drawings are as follows:

[0030] 1. Tool monitoring system; 11. Monitoring terminal; 12. Data processing platform. Detailed Implementation

[0031] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] In one embodiment, such as Figure 1 As shown, a tool monitoring system 1 is provided, including a monitoring terminal 11 and a data processing platform 12. The monitoring terminal 11 is used to collect tool operating condition data within a target time period and report it to the data processing platform 12. The operating condition data includes rotational speed data and current data. The target time period can be set according to requirements, but it should include multiple tool operating cycles and the time interval between adjacent different operating cycles (i.e., the time period corresponding to the tool being in standby mode). Specifically, the process of the monitoring terminal 11 collecting operating condition data is as follows: First, CNC equipment needs to be added to the acquisition library. Each type of CNC equipment in the acquisition library corresponds to a different tool milling scenario; that is, for each tool milling scenario, only one corresponding CNC equipment needs to be set in the acquisition library. Understandably, the first step is to configure the IP address (Internet Protocol) of the CNC devices in the data acquisition library to connect the CNC devices to the internal network of the tool monitoring system 1 (that is, the monitoring terminal 11 will connect to the CNC devices through this internal network). Specifically, the IP address, port, asset number information, etc. of the CNC devices are configured so that when it is necessary to collect working condition data, the CNC devices can be matched and connected according to the above configuration information. (If the matching and connection are successful, the acquisition end of the monitoring terminal 11 can start collecting working condition data. If the matching and connection fails, the reason for the failure will be written to the management log for easy querying and tracing of the reason for the failure.)

[0033] The working condition data refers to the working status parameters directly related to the actions (including tool actions) of the CNC equipment when it is working; the working condition data includes, but is not limited to, one or more of the following: speed data, current data, and time data. After the monitoring terminal 11 collects the working condition data, it will be standardized (e.g., set to a uniform format) and then reported to the data processing platform 12 in real time, where it will be saved. Understandably, the monitoring terminal 11 uses .NET data acquisition to collect the working condition data, and most devices use SDKs (Software Development Kits) that are more compatible with .NET. Therefore, using .NET data acquisition improves the stability and convenience of data acquisition.

[0034] Furthermore, the tool monitoring system 1 also includes a display device connected to the monitoring terminal 11 and the data processing platform 12 for displaying data. The display device can be the display screen of the central control terminal, and it is used to visualize relevant data from the CNC equipment and supports playback of historical status data of the CNC equipment.

[0035] In one embodiment, the data processing platform 12 includes a message engine, a forwarding module, and a database. The message engine receives the operating condition data reported by the monitoring terminal 11. The forwarding module processes the operating condition data received by the message engine in real time and forwards it to the database for storage. The database also stores the simulation fitting curve and the alarm threshold. Specifically, the monitoring terminal 11 collects operating condition data of the equipment in real time, such as speed data, current data, and time data. Each time data (each specific sampling time point) is associated with a speed data and a current data. Thus, after collecting the operating condition data corresponding to several working cycles of the tool (the working cycle includes the initial working stage, the stable working stage, and the final working stage), the monitoring terminal 11 reports the collected operating condition data to the message engine (e.g., a distributed message engine) of the data processing platform 12 in real time for storage. The forwarding module processes the operating condition data received by the message engine in real time and forwards it to the database. Specifically, the forwarding module... The system includes a data forwarding service module, a Kafka (an open-source stream processing platform developed by the Apache Software Foundation) module, and a Flink (a framework and distributed processing engine) module. The data forwarding service module receives operational data from the message engine in real time, unifies the data into JSON format, and then sends the JSON data to the Kafka module for caching. The Flink module consumes the operational data from Kafka in real time, performs normalization processing on the data, and then saves the normalized operational data to a database, which can be InfluxDB (a high-performance time-series, time, and metrics database).

[0036] Furthermore, the data processing platform 12 is used for:

[0037] The operating current corresponding to each work cycle is determined from the current data based on the rotation speed data. Specifically, the data processing platform 12 also includes an algorithm engine module. After receiving the training request sent by the monitoring terminal 11, the algorithm engine module retrieves the working condition data from the database for training. Specifically, firstly, all work cycles are separated from the current data based on the rotation speed data. While separating the work cycles, each work cycle can also be divided into three work stages based on the rotation speed data: the start work stage, the stable work stage, and the end work stage (understandably, the working condition data corresponds to multiple work cycles, and each work cycle includes the start work stage, the stable work stage, and the end work stage connected in sequence, while the time data other than the work cycle corresponds to the standby state of the tool), thereby determining the operating current corresponding to each work cycle.

[0038] Understandably, Figure 2 The diagram illustrates the correlation between current data, rotational speed data, and time data; Figure 2 As can be seen, during the initial operation phase L2 (time data corresponds to the first speed segment B) and the final operation phase L4 (time data corresponds to the second speed segment D), the spindle speed of the motor controlling the tool rotation undergoes a sudden change. Based on this speed change characteristic, the initial operation phase L2 and the final operation phase L4 of the operation cycle can be determined. Therefore, the operation cycle can be separated based on this speed change characteristic, and the working current corresponding to all operation cycles (one operation cycle includes the initial operation phase L2, the stable operation phase L3, and the final operation phase L4) can be separated from the current data. Current data other than the working current indicates that the tool is in standby mode (corresponding to...). Figure 2 The current in the two stages of L1 and L5 (that is, the current data corresponding to the time data outside the operation cycle).

[0039] Curve fitting is performed on all the operating currents to obtain multiple initial fitting curves corresponding to each of the operating cycles. That is, in this embodiment, the algorithm engine module of the data processing platform 12 only performs curve fitting on the operating currents corresponding to all operating cycles to form an initial fitting curve for each operating cycle. In one embodiment, it is necessary to generate an initial fitting curve based on a preset fitting model. When the monitoring terminal 11 is in training mode (the monitoring terminal 11 includes both training mode and monitoring mode), the monitoring terminal 11 will report the collected operating condition data to the data processing platform 12 and send a training request to the algorithm engine module. This instructs the algorithm engine module to train the preset fitting model based on the operating currents and their corresponding time data (that is, to determine the model parameters in the preset fitting model), and then fit the initial fitting curve corresponding to each of the operating cycles based on the trained preset fitting model. Specifically, after the monitoring terminal 11 starts the training mode, it will first clear other fitted models in the local cache, and then start collecting working condition data and reporting it to the data processing platform 12 in real time. After terminating the data collection, the monitoring terminal 11 will notify the algorithm engine module to train the working condition data that was just collected (that is, send a training request to the data processing platform) to obtain the preset fitted model. After the algorithm engine module finishes training, it will save the model parameters corresponding to the preset fitted model to the database.

[0040] Based on all the initial fitting curves, a simulation fitting curve and alarm threshold for monitoring the real-time operating condition of the tool are determined. Specifically, after obtaining multiple initial fitting curves that correspond one-to-one with each of the described operation cycles, the algorithm engine module samples the three operation stages of each initial fitting curve in equal numbers, and then calculates the average of the data points corresponding to each sampling point to generate the final simulation fitting curve.

[0041] While generating the simulation fitting curve, the algorithm engine module can also obtain the point difference values ​​of all sampling points corresponding to different operation stages (start operation stage, stable operation stage, and end operation stage) for each initial fitting curve. This point difference value refers to the difference between the point data corresponding to the same sampling point and the point mean. Furthermore, the maximum absolute value of the point difference value corresponding to each operation stage is used as the alarm threshold for that operation stage. Finally, the algorithm engine module saves the preset fitting model, simulation fitting curve, and alarm threshold to the database, allowing the monitoring terminal 11 and the display device to access the data stored in the database through the data service interface. For example, when the monitoring terminal 11 enters monitoring mode, it can obtain the simulation fitting curve and alarm threshold from the database to monitor the real-time working condition of the CNC equipment's tools, thereby determining whether the tools are experiencing abnormal conditions such as wear.

[0042] The monitoring terminal 11 is also used to: acquire the simulation fitting curve and alarm threshold, and monitor the real-time working condition of the tool according to the simulation fitting curve and alarm threshold.

[0043] In one specific embodiment, the step of acquiring the simulation fitting curve and alarm threshold, and monitoring the real-time operating condition of the tool based on the simulation fitting curve and alarm threshold, includes:

[0044] After receiving the tool monitoring command, the simulation fitting curve and the alarm threshold are retrieved from the data processing platform 12, and real-time rotational speed and real-time current are collected. Specifically, after the monitoring terminal 11 enters the detection mode, if it receives the tool monitoring command sent by the data processing platform 12 or the CNC equipment, the monitoring terminal 11 can send a call request to the data processing platform 12 (the call request is generated after the monitoring terminal 11 receives the tool monitoring command). The data processing platform 12 will then respond to the call request, allowing the monitoring terminal 11 to retrieve the simulation fitting curve and alarm threshold from the database. After successfully obtaining the simulation fitting curve and alarm threshold, the data acquisition function will be activated to collect the real-time rotational speed and real-time current of the spindle of the drive motor used by the CNC equipment to control the tool rotation, thereby monitoring the real-time working condition of the tool.

[0045] After determining that the tool has entered the working cycle based on the real-time rotation speed, the current difference corresponding to the real-time current is determined based on the simulation fitting curve. Specifically, during the process of collecting the real-time rotation speed and real-time current, it is possible to determine whether the tool has entered the working cycle based on the real-time rotation speed. After entering the working cycle, the current difference between the real-time current and the fitting current corresponding to the simulation fitting curve is determined.

[0046] Based on the current difference and the alarm threshold, a monitoring result is generated. That is, based on the current difference and the alarm threshold, it is possible to monitor in real time whether the tool is malfunctioning and obtain the monitoring result. In this embodiment, the monitoring terminal 11 can perform real-time monitoring and alarm functions on the tool based on the simulation fitting curve and the alarm threshold.

[0047] The tool monitoring system 1 of this invention can collect tool operating parameters for any tool milling scenario, and generate simulation fitting curves and alarm thresholds based on the collected speed and current data. It then uses these simulation fitting curves and alarm thresholds to accurately monitor the real-time operating condition of the tool. In other words, this invention can adaptively adjust and generate different simulation fitting curves and alarm thresholds for different tool milling scenarios (such as changes in milling materials and CNC equipment), improving monitoring accuracy and shortening the model adjustment cycle after changing the tool milling scenario, thus making the machining cycle controllable.

[0048] In one embodiment, determining the operating current corresponding to each operating cycle from the current data based on the rotational speed data includes:

[0049] Based on the speed data, a first speed segment meeting the preset speed surge condition, a second speed segment meeting the preset speed drop condition, and a stable speed segment connecting adjacent first and second speed segments are determined. Specifically, whether the preset speed surge condition is met can be determined by whether the difference between the speed data corresponding to adjacent acquisition time points (the speed data corresponding to the later acquisition time point minus the speed data corresponding to the previous acquisition time point) exceeds a preset maximum speed threshold. For example, if a period of data contains several acquisition time points, and the difference between the speed data corresponding to any two adjacent acquisition time points in that period of data exceeds the preset maximum speed threshold, then the condition is considered met. If a speed threshold is set, the rotational speed data corresponding to this time period can be considered to meet the preset conditions for a sudden increase in rotational speed. Similarly, the preset conditions for a sudden decrease in rotational speed can be determined by whether the difference between the rotational speed data corresponding to adjacent acquisition time points (the rotational speed data corresponding to the later acquisition time point minus the rotational speed data corresponding to the previous acquisition time point) is less than a preset minimum rotational speed threshold (the preset minimum rotational speed threshold is a negative value). For example, if a time period of data contains several acquisition time points, and the difference between the rotational speed data corresponding to any two adjacent acquisition time points in this time period is less than the preset minimum rotational speed threshold, then the rotational speed data corresponding to this time period of data can be considered to meet the preset conditions for a sudden decrease in rotational speed. The first rotational speed segment corresponds to the initial operation stage, the stable rotational speed segment corresponds to the stable operation stage, and the second rotational speed segment corresponds to the end of the operation stage.

[0050] Understandably, in this embodiment, the steady speed range refers to the speed range connected between the adjacent first speed range and the second speed range, with its front end connected to the first speed range and its rear end connected to the second speed range. The steady speed range does not include the standby speed range corresponding to when the tool is in standby state (the front end of the standby speed range is connected to the second speed range and its rear end is connected to the first speed range).

[0051] Understandably, as long as the CNC equipment is powered on, the spindle speed of the tool drive motor will always remain at a certain preset fixed value. Figure 2 The mid-speed data will always remain around 5000 rpm; such as Figure 2The curve P1 shows the correspondence between the mid-speed data and the time data. In the standby speed segment A, the speed data is around 5000 rpm (the tool has not yet started milling, and the speed data is stable at around 5000 rpm); in the first speed segment B corresponding to the initial operation stage, the speed data drops from 5000 rpm to around 4300 rpm (the tool starts milling, the resistance increases, and the speed drops to around 4300 rpm; at this time, the working current needs to be gradually increased to raise the speed data back to 5000 rpm); in the stable speed segment C corresponding to the stable operation stage, the speed data recovers to around 5000 rpm (after increasing the working current to raise the speed data to 5000 rpm, the working current is kept basically unchanged, and milling can continue); afterwards, in the... In the second speed range D corresponding to the end of the operation, the speed data increases to about 5500 rpm (after the milling operation ends, because the working current is greater than the idle speed range A, but there is no working resistance at this time, the speed data will be greater than the 5000 rpm corresponding to the idle speed range A, and gradually increase to 5500 rpm. At this time, it is necessary to gradually reduce the working current to match the working current corresponding to the idle speed range A, so that the speed data drops back to 5000 rpm); in the subsequent idle speed range E, the speed data drops from 5500 rpm to 5000 rpm (after reducing the working current to reduce the speed data to 5000 rpm, the tool does not perform milling operations, so it is sufficient to keep the working current basically unchanged to stabilize the speed data at about 5000 rpm); thus, in Figure 2 In the process, by analyzing the changes in rotational speed data, a complete operating cycle is determined to be from the starting point of the first rotational speed segment B to the ending point of the second rotational speed segment D (i.e., ... Figure 2 The time periods corresponding to the first speed range B, the stable speed range C, and the second speed range D are also the time periods corresponding to the initial operation stage L2, the stable operation stage L3, and the final operation stage L3.

[0052] The current data corresponding to each set of rotational speed change data is determined as the working current corresponding to one work cycle; wherein each set of rotational speed change data includes a first rotational speed segment, a stable rotational speed segment, and a second rotational speed segment connected in sequence. Understandably, after determining the first rotational speed segment, the stable rotational speed segment, and the second rotational speed segment, the work cycle can be separated according to the different rotational speed segments corresponding to different work stages (the first rotational speed segment corresponds to the initial work stage, the stable rotational speed segment corresponds to the stable work stage, and the second rotational speed segment corresponds to the end work stage), thereby separating the working current corresponding to different work stages in all work cycles from the current data; and the current data other than the working current are all currents when the tool is in standby mode (i.e., current data corresponding to time data outside the work cycle). Further, the data processing platform 12 includes an algorithm engine module; in this embodiment, the above steps are all executed by the engine module.

[0053] In one embodiment, the operating cycle includes a starting operating phase corresponding to the first speed range, a stable operating phase corresponding to the stable speed range, and an ending operating phase corresponding to the second speed range; the step of performing curve fitting based on all the operating currents to obtain multiple initial fitting curves corresponding one-to-one with each of the operating cycles includes:

[0054] The time data corresponding to the operating current is obtained from the operating condition data. All time data corresponding to each of the work cycles are then aligned with their start times to obtain aligned cycle time information. Specifically, as time changes, the actual cycle data corresponding to each work cycle in the collected operating condition data is not the same. To facilitate obtaining a unique simulation fitting curve based on multiple initial fitting curves, in this embodiment, it is necessary to first align the start times of all time data corresponding to each work cycle. That is, the start time point of each work cycle (i.e., the start time point of the initial work phase) is set to time t0 (t0 can be time 0 or other specific times). Afterwards, each cycle time information is the duration corresponding to that work cycle, but the time period starting at time t0.

[0055] Based on the operating current and cycle time information, curve fitting is performed to generate multiple initial fitting curves corresponding one-to-one with the multiple work cycles. Each initial fitting curve corresponding to a work cycle includes a first start time period corresponding to the initial work phase, a first intermediate time period corresponding to the stable work phase, and a first end time period corresponding to the final work phase. That is, as... Figure 2As shown, during curve fitting, each initial fitting curve P3 uses its corresponding cycle time information as the abscissa (in the abscissa, the initial fitting curve P3 takes time t0 as the starting point of the first starting time period). Then, based on the preset fitting model and cycle time information, the current value corresponding to the ordinate is determined, and finally, the initial fitting curve corresponding to each working cycle is fitted and generated. Further, the data processing platform 12 includes an algorithm engine module; in this embodiment, all the above steps are executed by the engine module.

[0056] In one embodiment, the step of performing curve fitting based on the operating current and the cycle time information to generate multiple initial fitting curves corresponding one-to-one with the multiple operating cycles includes:

[0057] The cycle time information corresponding to each of the aforementioned work cycles is input into a preset fitting model for curve fitting, generating an initial fitting curve corresponding to that work cycle; the preset fitting model is trained based on the cycle time information and its corresponding operating current (specifically, the current data corresponding to the work cycle is the operating current). Figure 2 Curve P2 in the diagram represents the relationship between the operating current and time data. When the initial fitting curve obtained after training the preset fitting model essentially coincides with P2, and the fluctuation range falls within the preset fluctuation range, the preset fitting model can be considered successfully trained. However, if the fluctuation range between the initial fitting curve obtained after training and P2 exceeds the preset fluctuation range, the preset fitting model can be considered not successfully trained, and further adjustments to the model parameters (a1, a2, a...) are still needed. 3、 After adjusting model parameters such as b1, b2, c1, c2, and c3, training continues with alignment. The preset fitting model is used for:

[0058] During the first initial time interval (t0<t≤t1) of the initial fitted curve, the current value of the initial fitted curve during the first initial time interval is calculated using an exponential function.

[0059] During the first intermediate time period (t1 < t ≤ t2) of the initial fitted curve, the current value of the initial fitted curve during the first intermediate time period is calculated using a logarithmic function;

[0060] During the first end time period (t2<t≤t3) of the initial fitting curve, the current value of the first start time period of the initial fitting curve is calculated using a quadratic function.

[0061] Specifically, the preset fitting model includes:

[0062]

[0063] in:

[0064] t represents the cycle time information corresponding to the work cycle; wherein, after performing start time alignment processing on all the time data corresponding to each work cycle, the start time point of the cycle time information corresponding to each work cycle (that is, the start time point of the start work stage) is set to time t0 (t0 can be time 0 or other specific time), and the cycle time information is the duration corresponding to the work cycle (that is, t3-t0).

[0065] S(t) is the current value on the initial fitting curve corresponding to the cycle time information corresponding to the operation cycle;

[0066] It is a quasi-exponential function used to calculate the current value during the first starting time period of the initial fitted curve;

[0067] b1log(t)+b2 is the logarithmic function used to calculate the current value during the first intermediate time period of the initial fitted curve;

[0068] c1t 2 +c2t+c3 is a quadratic function used to calculate the current value of the first end time period corresponding to the initial fitting curve;

[0069] a1, a2, a 3、 b1, b2, c1, c2, and c3 are all preset constants;

[0070] t0 is the starting time point of the first starting time period of the initial fitting curve;

[0071] t1 is the end time point of the first starting time period of the initial fitted curve;

[0072] t2 is the end time of the first intermediate time period of the initial fitted curve;

[0073] t3 is the end time point of the first end time period of the initial fitted curve.

[0074] In one embodiment, after generating multiple initial fitting curves corresponding one-to-one with each of the said work cycles, the algorithm engine module is further configured to:

[0075] For each initial fitting curve, the first start time period, the first middle time period, and the first end time period are sampled in equal numbers to determine a preset number of sampling points corresponding to each initial fitting curve. After obtaining multiple initial fitting curves that correspond one-to-one with each of the work cycles, the algorithm engine module will sample in equal numbers for each of the three work stages of each initial fitting curve. That is, a number of sampling points are sampled for each of the three work stages: the start work stage, the stable work stage, and the end work stage. For example, a first number of first sampling points are sampled for all start work stages, a second number of second sampling points are sampled for all stable work stages, and a third number of third sampling points are sampled for all end work stages (the first number, the second number, and the third number can be equal or unequal).

[0076] The average value of the data points corresponding to the same sampling point on all the initial fitted curves is processed to obtain the average value of the data points corresponding to each sampling point. For each sampling point, the average value of the data points includes the period time information corresponding to the horizontal axis and the current value corresponding to the vertical axis. Therefore, the average value of the data points corresponding to each sampling point means obtaining the time average value of all period time information corresponding to the same sampling point and the current average value of all current values ​​corresponding to that sampling point. That is, the average value of the data points includes the above-mentioned current average value and time average value.

[0077] A simulation fitting curve is generated based on the average values ​​of all the points. The simulation fitting curve includes a second starting time period corresponding to the initial operation phase, a second intermediate time period corresponding to the stable operation phase, and a second ending time period corresponding to the final operation phase. That is, the final simulation fitting curve is generated based on the average time and average current value corresponding to each sampling point (the average current value corresponding to the sampling point is the fitting current on the simulation fitting curve corresponding to that sampling point).

[0078] In one embodiment, determining the alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitted curves includes:

[0079] The algorithm engine module acquires all point differences corresponding to each sampling point, where the point difference refers to the difference between the point data and the point mean corresponding to the same sampling point. That is, while generating the simulation fitting curve, the algorithm engine module can also acquire the point differences of all sampling points corresponding to different operation stages (start operation stage, stable operation stage, and end operation stage) for each initial fitting curve. The point difference refers to the difference between the point data and the point mean corresponding to the same sampling point. Further, the point difference can be the difference between the working current in the point data and the current mean in the point mean corresponding to the same sampling point.

[0080] The maximum absolute value of the point differences corresponding to all sampling points in the same work phase is determined, and this maximum value is recorded as the alarm threshold corresponding to that work phase. The work phase includes the start work phase, the stable work phase, and the end work phase of the work cycle. That is, the maximum absolute value of the point differences corresponding to each work phase can be used as the alarm threshold for that work phase. Finally, the algorithm engine module saves the preset fitting model, the simulation fitting curve, and the alarm threshold to the database. When the monitoring terminal 11 enters the monitoring mode, the monitoring terminal 11 can call the data service module of the data processing platform 12 to obtain the simulation fitting curve and the alarm threshold from the database, and then monitor the real-time working condition of the CNC equipment's tool to determine whether the tool has abnormal conditions such as wear. Furthermore, in this embodiment, all the above steps are executed by the engine module.

[0081] In one embodiment, after determining the entry of the tool into the working cycle based on the real-time rotation speed, determining the current difference corresponding to the real-time current based on the simulation fitting curve includes:

[0082] Determine whether the real-time rotational speed meets the preset speed surge requirement. Specifically, it can be determined whether the preset speed surge condition is met by whether the difference between the real-time rotational speeds corresponding to adjacent acquisition time points (the real-time rotational speed corresponding to the later acquisition time point minus the real-time rotational speed corresponding to the previous acquisition time point) exceeds a preset maximum rotational speed threshold. For example, if there are several acquisition time points in a period of time before the current time point, and the difference between the real-time rotational speeds corresponding to any two adjacent acquisition time points in this period of time exceeds the preset maximum rotational speed threshold, then the real-time rotational speed corresponding to this period of time can be considered to meet the preset speed surge condition.

[0083] When the preset speed increase requirement is met, the tool is determined to enter the work cycle, and the start time of entering the work cycle is recorded. Specifically, if the real-time speed meets the preset speed increase requirement, it indicates that the tool has begun entering the work cycle and starting milling operations. In this case, the first stage is the start of the work cycle, and the start time of entering the work cycle (i.e., the start time of the start of the work cycle) needs to be recorded first. When the real-time speed no longer meets the preset speed increase condition, the start of the work cycle is confirmed to have ended, and the end time of this start of the work cycle (i.e., the start time of the stable work cycle) can be recorded.

[0084] Before determining that the cutting tool has not ended the operation cycle, the fitting current corresponding to the current time point is determined according to the simulation fitting curve and the starting time point, and the absolute value of the difference between the real-time current and the fitting current is recorded as the current difference value at the current time point. In this embodiment, the end of the work cycle of the tool can be determined by judging whether the real-time rotational speed meets the preset speed drop condition. Specifically, the difference between the real-time rotational speeds corresponding to adjacent acquisition time points (the difference between the real-time rotational speeds corresponding to the later acquisition time point and the real-time rotational speeds corresponding to the previous acquisition time point) can be used to determine whether the preset speed drop condition is met. For example, if there are several acquisition time points in a period of time before the current time point, and the difference between the real-time rotational speeds corresponding to any two adjacent acquisition time points in this period of time is less than the preset minimum speed threshold, then the real-time rotational speed corresponding to this period of time can be considered to meet the preset speed drop condition. At this time, it is determined that the tool has entered the end stage of the work cycle, and the start time of the end stage (that is, the end time of the stable work stage) is recorded. When the real-time rotational speed no longer meets the preset speed drop condition, the end of the work cycle is confirmed (before this, it is considered that the current work cycle has not ended), and the end time of the work cycle (that is, the end time of the end stage) can be recorded. Specifically, when the current time point is within the operation cycle, the current difference w(t) = |i(t) - i real (t)|, where: i real Let be the real-time current at the current time point; i(t) is the fitted current on the simulation curve corresponding to the current time point. Furthermore, when the current time point is not within the operating cycle, the current difference w(t) = 0.

[0085] The above embodiments clarify how to determine the current difference value corresponding to the current point in the work cycle. Alternatively, the start and end times of each work stage can be determined before the tool finishes the work cycle, so as to facilitate real-time monitoring and alarming of the tool based on the alarm thresholds corresponding to each work stage.

[0086] In one embodiment, generating the monitoring result based on the current difference and the alarm threshold includes:

[0087] Before determining that the cutting tool has not ended the work cycle, the current work stage within the work cycle is obtained based on the real-time rotational speed. The current work stage is one of the start work stage, stable work stage, and end work stage of the work cycle. That is, referring to the previous embodiment, the end of the work cycle can be confirmed based on whether the real-time rotational speed meets the preset speed drop condition, which will not be repeated here. Furthermore, as can be seen from the above embodiment, in determining the current difference value corresponding to each current time point in the work cycle, the start and end time points of each work stage can also be determined based on the real-time rotational speed, thereby determining the current work stage within the work cycle (before the cutting tool has ended the work cycle, the current work stage is one of the three work stages of the work cycle).

[0088] Obtain the alarm threshold corresponding to the current operation stage, and determine whether the current difference at the current time point is greater than the alarm threshold. Specifically, each operation stage corresponds to an alarm threshold. Therefore, after determining the current operation stage corresponding to the current time point, the alarm threshold corresponding to the current operation stage can also be known. In this way, it can be determined whether the current difference corresponding to the current time point is greater than the alarm threshold corresponding to the current operation stage, and thus obtain the monitoring result.

[0089] When the current difference is greater than the alarm threshold, the monitoring result is confirmed as a tool malfunction and an alarm message is generated; specifically, if the alarm threshold is 2A, and the current difference corresponding to the current time point is greater than the alarm threshold corresponding to the current operation stage, then, as follows... Figure 3 As shown, during the monitoring of the real-time working condition of the tool by the monitoring terminal 11, the simulation curve is S; the curve of the real-time current changing with time is L. Figure 3 When the current difference w(t) corresponding to 27 seconds on the horizontal axis is greater than the alarm threshold of 2A, the monitoring terminal 11 confirms that the monitoring result is a tool abnormality and generates an alarm message. The alarm message can be an audible alarm, a visual alarm, or a text message alarm sent to a preset recipient. That is, when the monitoring result is a tool abnormality, an alarm will be triggered based on the alarm message, thereby enabling the tool monitoring system 1 to effectively monitor the real-time operating condition of the tool. The aforementioned tool abnormality can be an abnormal condition such as tool wear. Understandably, after confirming that the monitoring result is a tool abnormality and generating an alarm message, the alarm message can be uploaded to the database of the data processing platform 12 for storage, so as to facilitate the review of historical operating condition data. After confirming that the monitoring result is a tool abnormality and generating an alarm message, real-time rotation speed and real-time current can continue to be collected to monitor the real-time operating condition of the tool to generate new monitoring results, or the current monitoring can be terminated directly.

[0090] When the current difference is less than or equal to the alarm threshold, the monitoring result is confirmed as the tool being normal. That is, when the current difference corresponding to the current time point is less than or equal to the alarm threshold corresponding to the current operation stage, it indicates that the tool is currently operating normally without any abnormalities. At this time, real-time rotation speed and real-time current can continue to be collected to monitor the real-time operating condition of the tool.

[0091] This invention also provides a tool monitoring method, which is applied to the data processing platform 12 of the tool monitoring system 1. Further specific limitations on the tool monitoring method can be found in the above-described limitations of the tool monitoring system 1. Figure 4 As shown, the tool monitoring method includes:

[0092] S10, receive operating condition data within a target time period collected by monitoring terminal 11; the operating condition data includes speed data and current data;

[0093] S20, determine the operating current corresponding to each working cycle from the current data based on the rotation speed data;

[0094] S30, curve fitting is performed based on all the operating currents to obtain multiple initial fitting curves that correspond one-to-one with each of the operating cycles;

[0095] S40, determine a simulation fitting curve and an alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitting curves, so that the monitoring terminal can acquire the simulation fitting curve and the alarm threshold, and monitor the real-time operating condition of the tool based on the simulation fitting curve and the alarm threshold.

[0096] The tool monitoring system 1 of this invention can collect tool operating parameters for any tool milling scenario, and generate simulation fitting curves and alarm thresholds based on the collected speed and current data. It then uses these simulation fitting curves and alarm thresholds to accurately monitor the real-time operating condition of the tool. In other words, this invention can adaptively adjust and generate different simulation fitting curves and alarm thresholds for different tool milling scenarios (such as changes in milling materials and CNC equipment), improving monitoring accuracy and shortening the model adjustment cycle after changing the tool milling scenario, thus making the machining cycle controllable.

[0097] In one embodiment, step S20, namely determining the operating current corresponding to each operating cycle from the current data based on the rotational speed data, includes:

[0098] Based on the speed data, a first speed range that meets the preset speed increase condition, a second speed range that meets the preset speed decrease condition, and a stable speed range connecting the adjacent first speed range and second speed range are determined.

[0099] The current data corresponding to each set of speed change data is determined as the working current corresponding to one working cycle; wherein each set of speed change data includes a first speed segment, a stable speed segment and a second speed segment connected in sequence.

[0100] In one embodiment, the work cycle includes a start-up work phase corresponding to the first speed range, a steady-state work phase corresponding to the steady-state speed range, and a finish-up work phase corresponding to the second speed range.

[0101] Further, step S30, namely, performing curve fitting based on all the operating currents to obtain multiple initial fitting curves corresponding one-to-one with each of the operating cycles, includes:

[0102] Obtain the time data corresponding to the working current from the working condition data, and perform start time alignment processing on all the time data corresponding to each working cycle to obtain the aligned cycle time information;

[0103] Based on the operating current and the cycle time information, curve fitting is performed to generate multiple initial fitting curves that correspond one-to-one with the multiple operation cycles. Each initial fitting curve corresponding to the operation cycle includes a first start time period corresponding to the start operation stage, a first intermediate time period corresponding to the stable operation stage, and a first end time period corresponding to the end operation stage.

[0104] Further, the step of performing curve fitting based on the operating current and the cycle time information to generate multiple initial fitting curves corresponding one-to-one with the multiple operating cycles includes:

[0105] The cycle time information corresponding to each of the aforementioned work cycles is input into a preset fitting model for curve fitting, generating an initial fitting curve corresponding to that work cycle; the preset fitting model is trained based on the cycle time information and its corresponding operating current, and the preset fitting model is used for:

[0106] During the first initial time period of the initial fitted curve, the current value of the first initial time period of the initial fitted curve is calculated using an exponential function.

[0107] During the first intermediate time period of the initial fitted curve, the current value of the initial fitted curve during the first intermediate time period is calculated using a logarithmic function;

[0108] During the first end time period of the initial fitting curve, the current value of the first start time period of the initial fitting curve is calculated using a quadratic function.

[0109] Specifically, the preset fitting model includes:

[0110]

[0111] in:

[0112] t represents the cycle time information corresponding to the work cycle;

[0113] S(t) is the current value on the initial fitting curve corresponding to the cycle time information corresponding to the operation cycle;

[0114] It is a quasi-exponential function used to calculate the current value during the first starting time period of the initial fitted curve;

[0115] b1log(t)+b2 is the logarithmic function used to calculate the current value during the first intermediate time period of the initial fitted curve;

[0116] c1t 2 +c2t+c3 is a quadratic function used to calculate the current value of the first end time period corresponding to the initial fitting curve;

[0117] a1, a2, a 3、 b1, b2, c1, c2, and c3 are all preset constants;

[0118] t0 is the starting time point of the first starting time period of the initial fitting curve;

[0119] t1 is the end time point of the first starting time period of the initial fitted curve;

[0120] t2 is the end time of the first intermediate time period of the initial fitted curve;

[0121] t3 is the end time point of the first end time period of the initial fitted curve.

[0122] Further, in step S40, determining the simulation fitting curve for monitoring the real-time working condition of the tool based on all the initial fitting curves includes:

[0123] For each initial fitting curve, the first start time period, the first middle time period, and the first end time period are sampled in equal numbers to determine a preset number of sampling points corresponding to each initial fitting curve.

[0124] The mean value of the data points corresponding to the same sampling point on all the initial fitting curves is processed to obtain the mean value of the data points corresponding to each sampling point.

[0125] A simulation fitting curve is generated based on the mean values ​​of all the points. The simulation fitting curve includes a second starting time period corresponding to the starting operation phase, a second intermediate time period corresponding to the stable operation phase, and a second ending time period corresponding to the ending operation phase.

[0126] Further, in step S40, determining the alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitted curves includes:

[0127] Obtain all point differences corresponding to each of the sampling points, where the point difference refers to the difference between the point data and the point mean value corresponding to the same sampling point.

[0128] The maximum value among the absolute values ​​of the point differences corresponding to all the sampling points in the same work phase is determined, and the maximum value is recorded as the alarm threshold corresponding to the work phase; the work phase includes the start work phase, the stable work phase, and the end work phase of the work cycle.

[0129] Furthermore, after determining the simulation fitting curve and alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitting curves, the method further includes:

[0130] The system receives a call request sent by the monitoring terminal, which is generated after the monitoring terminal receives the tool monitoring instruction.

[0131] In response to the call request, after the monitoring terminal calls the simulation fitting curve and the alarm threshold, it collects real-time rotation speed and real-time current. After determining that the tool has entered the working cycle based on the real-time rotation speed, it determines the current difference corresponding to the real-time current based on the simulation fitting curve, and then generates monitoring results based on the current difference and the alarm threshold.

[0132] This invention also provides a tool monitoring method, which is applied to the monitoring terminal 11 of the tool monitoring system 1. Further specific limitations of the tool monitoring method can be found in the above-described limitations of the tool monitoring system 1. The tool monitoring method includes:

[0133] The simulation fitting curve and alarm threshold are obtained, and the real-time operating condition of the tool is monitored based on the simulation fitting curve and alarm threshold. The simulation fitting curve and alarm threshold are determined as follows: After the data processing platform receives the operating condition data collected and reported by the monitoring terminal within the target time period, the working current corresponding to each working cycle is determined from the current data in the operating condition data based on the rotation speed data in the operating condition data; curve fitting is performed based on all the working currents to obtain multiple initial fitting curves that correspond one-to-one with each of the working cycles; the simulation fitting curve and alarm threshold used for monitoring the real-time operating condition of the tool are determined based on all the initial fitting curves.

[0134] The tool monitoring system 1 of this invention can collect tool operating parameters for any tool milling scenario, and generate simulation fitting curves and alarm thresholds based on the collected speed and current data. It then uses these simulation fitting curves and alarm thresholds to accurately monitor the real-time operating condition of the tool. In other words, this invention can adaptively adjust and generate different simulation fitting curves and alarm thresholds for different tool milling scenarios (such as changes in milling materials and CNC equipment), improving monitoring accuracy and shortening the model adjustment cycle after changing the tool milling scenario, thus making the machining cycle controllable.

[0135] In one embodiment, such as Figure 5 As shown, the step of acquiring the simulation fitting curve and alarm threshold, and monitoring the real-time operating condition of the tool based on the simulation fitting curve and alarm threshold, includes:

[0136] S100, after receiving the tool monitoring command, retrieves the simulation fitting curve and the alarm threshold from the data processing platform, and collects real-time rotational speed and real-time current;

[0137] S200, after determining that the tool has entered the working cycle based on the real-time rotation speed, the current difference corresponding to the real-time current is determined based on the simulation fitting curve;

[0138] S300, generate monitoring results based on the current difference and the alarm threshold.

[0139] In one embodiment, step S200, which is the step of determining the current difference corresponding to the real-time current based on the simulation fitting curve after determining that the tool has entered the working cycle according to the real-time rotation speed, includes:

[0140] Determine whether the real-time rotational speed meets the preset speed surge requirement;

[0141] When the preset speed increase requirement is met, the tool is determined to enter the working cycle, and the start time of entering the working cycle is recorded;

[0142] Before determining that the cutting tool has not ended the operation cycle, the fitting current corresponding to the current time point is determined according to the simulation fitting curve and the starting time point, and the absolute value of the difference between the real-time current and the fitting current is recorded as the current difference value at the current time point.

[0143] In one embodiment, step S300, namely generating a monitoring result based on the current difference and the alarm threshold, includes:

[0144] Before determining that the cutting tool has not ended the work cycle, the current work stage in the work cycle is obtained based on the real-time rotation speed; the current work stage is one of the start work stage, stable work stage, and end work stage of the work cycle;

[0145] Obtain the alarm threshold corresponding to the current operation stage, and determine whether the current difference at the current time point is greater than the alarm threshold;

[0146] When the current difference is greater than the alarm threshold, the monitoring result is confirmed as a tool abnormality and an alarm message is generated;

[0147] When the current difference is less than or equal to the alarm threshold, the monitoring result is confirmed to be that the tool is normal.

[0148] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0149] The present invention also provides a data processing platform 12 for executing the above-described tool monitoring method.

[0150] The present invention also provides a monitoring terminal 11 for performing the above-described tool monitoring method.

[0151] For further specific limitations regarding the data processing platform 12 and the monitoring terminal 11, please refer to the limitations of the tool monitoring system 1 above, which will not be repeated here. Each module in the data processing platform 12 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module. Understandably, both the data processing platform 12 and the monitoring terminal 11 can be considered as one or more computer devices, such as... Figure 6As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and the database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data used in the tool monitoring method described in the above embodiments. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements the tool monitoring method described above.

[0152] In one embodiment, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described tool monitoring method.

[0153] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0154] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0155] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A tool monitoring system, characterized in that, It includes a monitoring terminal and a data processing platform; the monitoring terminal is used to collect the working condition data of the cutting tool within a target time period and report it to the data processing platform; the working condition data includes rotational speed data and current data; The data processing platform is used for: The operating current corresponding to each working cycle is determined from the current data based on the rotation speed data; the operating current corresponding to each working cycle includes a set of current data corresponding to a set of rotation speed change data, and the set of rotation speed change data includes a first rotation speed segment that meets the preset rotation speed increase condition, a second rotation speed segment that meets the preset rotation speed decrease condition, and a stable rotation speed segment connected between the adjacent first rotation speed segment and the second rotation speed segment. Curve fitting is performed based on all the operating currents to obtain multiple initial fitting curves that correspond one-to-one with each of the operating cycles; the operating cycle includes a starting operating stage corresponding to the first speed range, a stable operating stage corresponding to the stable speed range, and a ending operating stage corresponding to the second speed range; each initial fitting curve corresponding to the operating cycle includes a first starting time period corresponding to the starting operating stage, a first intermediate time period corresponding to the stable operating stage, and a first ending time period corresponding to the ending operating stage; Based on all the initial fitting curves, a simulation fitting curve and an alarm threshold are determined for monitoring the real-time operating condition of the tool. The simulation fitting curve includes a second starting time period corresponding to the initial operation phase, a second intermediate time period corresponding to the stable operation phase, and a second ending time period corresponding to the final operation phase. Each operation phase corresponds to an alarm threshold, and the alarm threshold corresponding to an operation phase is the maximum value among the absolute values ​​of the point differences corresponding to all sampling points in the operation phase. The point difference refers to the difference between the point data corresponding to the same sampling point and the point mean. The operation phase includes the initial operation phase, the stable operation phase, and the final operation phase of the operation cycle. The monitoring terminal is also used to: acquire the simulation fitting curve and alarm threshold, and monitor the real-time working condition of the tool based on the simulation fitting curve and alarm threshold.

2. The tool monitoring system as described in claim 1, characterized in that, The step of determining the operating current corresponding to each operating cycle from the current data based on the rotation speed data includes: Based on the speed data, a first speed range that meets the preset speed increase condition, a second speed range that meets the preset speed decrease condition, and a stable speed range connecting the adjacent first speed range and second speed range are determined. The current data corresponding to each set of speed change data is determined as the working current corresponding to one working cycle; wherein each set of speed change data includes a first speed segment, a stable speed segment and a second speed segment connected in sequence.

3. The tool monitoring system as described in claim 2, characterized in that, The step of performing curve fitting based on all the operating currents to obtain multiple initial fitting curves corresponding one-to-one with each of the operating cycles includes: Obtain the time data corresponding to the working current from the working condition data, and perform start time alignment processing on all the time data corresponding to each working cycle to obtain the aligned cycle time information; Based on the operating current and the cycle time information, curve fitting is performed to generate multiple initial fitting curves that correspond one-to-one with the multiple operating cycles.

4. The tool monitoring system as described in claim 3, characterized in that, The step of performing curve fitting based on the operating current and the cycle time information to generate multiple initial fitting curves corresponding one-to-one with the multiple operating cycles includes: The cycle time information corresponding to each of the aforementioned work cycles is input into a preset fitting model for curve fitting, generating an initial fitting curve corresponding to that work cycle; the preset fitting model is trained based on the cycle time information and its corresponding operating current, and the preset fitting model is used for: During the first initial time period of the initial fitted curve, the current value of the first initial time period of the initial fitted curve is calculated using an exponential function. During the first intermediate time period of the initial fitted curve, the current value of the initial fitted curve during the first intermediate time period is calculated using a logarithmic function; During the first end time period of the initial fitting curve, the current value of the first start time period of the initial fitting curve is calculated using a quadratic function.

5. The tool monitoring system as described in claim 3, characterized in that, The step of determining the simulation fitting curve for monitoring the real-time operating condition of the tool based on all the initial fitting curves includes: For each initial fitting curve, the first start time period, the first middle time period, and the first end time period are sampled in equal numbers to determine a preset number of sampling points corresponding to each initial fitting curve. The mean value of the data points corresponding to the same sampling point on all the initial fitted curves is processed to obtain the mean value of the data points corresponding to each sampling point. A simulation fitting curve is generated based on the mean of all the points mentioned.

6. The tool monitoring system as described in claim 5, characterized in that, The step of determining the alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitted curves includes: Obtain all point differences corresponding to each of the sampling points; Determine the maximum value among the absolute values ​​of the point differences corresponding to all the sampling points in the same work phase, and record the maximum value as the alarm threshold corresponding to that work phase.

7. The tool monitoring system as described in claim 1, characterized in that, The step of acquiring the simulation fitting curve and alarm threshold, and monitoring the real-time operating condition of the tool based on the simulation fitting curve and alarm threshold, includes: After receiving the tool monitoring command, the simulation fitting curve and the alarm threshold are retrieved from the data processing platform, and real-time rotational speed and real-time current are collected. After determining the entry of the tool into the working cycle based on the real-time rotation speed, the current difference corresponding to the real-time current is determined based on the simulation fitting curve; The monitoring results are generated based on the current difference and the alarm threshold.

8. The tool monitoring system as described in claim 7, characterized in that, After determining the entry of the tool into the working cycle based on the real-time rotation speed, determining the current difference corresponding to the real-time current based on the simulation fitting curve includes: Determine whether the real-time rotational speed meets the preset speed surge requirement; When the preset speed increase requirement is met, the tool is determined to enter the working cycle, and the start time of entering the working cycle is recorded; Before determining that the cutting tool has not ended the operation cycle, the fitting current corresponding to the current time point is determined according to the simulation fitting curve and the starting time point, and the absolute value of the difference between the real-time current and the fitting current is recorded as the current difference value at the current time point.

9. The tool monitoring system as described in claim 7, characterized in that, The step of generating monitoring results based on the current difference and the alarm threshold includes: Before determining that the cutting tool has not ended the work cycle, the current work stage in the work cycle is obtained based on the real-time rotation speed; the current work stage is one of the start work stage, stable work stage, and end work stage of the work cycle; Obtain the alarm threshold corresponding to the current operation stage, and determine whether the current difference at the current time point is greater than the alarm threshold; When the current difference is greater than the alarm threshold, the monitoring result is confirmed as a tool abnormality and an alarm message is generated; When the current difference is less than or equal to the alarm threshold, the monitoring result is confirmed to be that the tool is normal.

10. The tool monitoring system as described in claim 1, characterized in that, The data processing platform includes a message engine, a forwarding module, and a database; the message engine is used to receive the operating condition data reported by the monitoring terminal; the forwarding module is used to process the operating condition data received by the message engine in real time and forward it to the database for storage; the database is also used to store the simulation fitting curve and the alarm threshold.

11. The tool monitoring system as described in claim 1, characterized in that, The tool monitoring system also includes a display device that connects the monitoring terminal and the data processing platform and is used to display data.

12. A tool monitoring method, characterized in that, The tool monitoring method, applied to a data processing platform, includes: Receives operating condition data within a target time period collected by the monitoring terminal; the operating condition data includes speed data and current data; The operating current corresponding to each working cycle is determined from the current data based on the rotation speed data; the operating current corresponding to each working cycle includes a set of current data corresponding to a set of rotation speed change data, and the set of rotation speed change data includes a first rotation speed segment that meets the preset rotation speed increase condition, a second rotation speed segment that meets the preset rotation speed decrease condition, and a stable rotation speed segment connected between the adjacent first rotation speed segment and the second rotation speed segment. Curve fitting is performed based on all the operating currents to obtain multiple initial fitting curves that correspond one-to-one with each of the operating cycles; the operating cycle includes a starting operating stage corresponding to the first speed range, a stable operating stage corresponding to the stable speed range, and a ending operating stage corresponding to the second speed range; each initial fitting curve corresponding to the operating cycle includes a first starting time period corresponding to the starting operating stage, a first intermediate time period corresponding to the stable operating stage, and a first ending time period corresponding to the ending operating stage; Based on all the initial fitting curves, a simulation fitting curve and an alarm threshold are determined for monitoring the real-time operating condition of the tool, so that the monitoring terminal can acquire the simulation fitting curve and the alarm threshold, and monitor the real-time operating condition of the tool according to the simulation fitting curve and the alarm threshold; the simulation fitting curve includes a second starting time period corresponding to the starting operation stage, a second intermediate time period corresponding to the stable operation stage, and a second ending time period corresponding to the ending operation stage; each operation stage corresponds to an alarm threshold, and the alarm threshold corresponding to an operation stage is the maximum value among the absolute values ​​of the point differences corresponding to all sampling points in the operation stage; the point difference refers to the difference between the point data corresponding to the same sampling point and the point mean; the operation stage includes the starting operation stage, the stable operation stage, and the ending operation stage of the operation cycle.

13. The tool monitoring method as described in claim 12, characterized in that, The step of determining the operating current corresponding to each operating cycle from the current data based on the rotation speed data includes: Based on the speed data, a first speed range that meets the preset speed increase condition, a second speed range that meets the preset speed decrease condition, and a stable speed range connecting the adjacent first speed range and second speed range are determined. The current data corresponding to each set of speed change data is determined as the working current corresponding to one working cycle; wherein each set of speed change data includes a first speed segment, a stable speed segment and a second speed segment connected in sequence.

14. The tool monitoring method as described in claim 13, characterized in that, The step of performing curve fitting based on all the operating currents to obtain multiple initial fitting curves corresponding one-to-one with each of the operating cycles includes: Obtain the time data corresponding to the working current from the working condition data, and perform start time alignment processing on all the time data corresponding to each working cycle to obtain the aligned cycle time information; Based on the operating current and the cycle time information, curve fitting is performed to generate multiple initial fitting curves that correspond one-to-one with the multiple operating cycles.

15. The tool monitoring method as described in claim 14, characterized in that, The step of performing curve fitting based on the operating current and the cycle time information to generate multiple initial fitting curves corresponding one-to-one with the multiple operating cycles includes: The cycle time information corresponding to each of the aforementioned work cycles is input into a preset fitting model for curve fitting, generating an initial fitting curve corresponding to that work cycle; the preset fitting model is trained based on the cycle time information and its corresponding operating current, and the preset fitting model is used for: During the first initial time period of the initial fitted curve, the current value of the first initial time period of the initial fitted curve is calculated using an exponential function. During the first intermediate time period of the initial fitted curve, the current value of the initial fitted curve during the first intermediate time period is calculated using a logarithmic function; During the first end time period of the initial fitting curve, the current value of the first start time period of the initial fitting curve is calculated using a quadratic function.

16. The tool monitoring method as described in claim 14, characterized in that, The step of determining the simulation fitting curve for monitoring the real-time operating condition of the tool based on all the initial fitting curves includes: For each initial fitting curve, the first start time period, the first middle time period, and the first end time period are sampled in equal numbers to determine a preset number of sampling points corresponding to each initial fitting curve. The mean value of the data points corresponding to the same sampling point on all the initial fitted curves is processed to obtain the mean value of the data points corresponding to each sampling point. A simulation fitting curve is generated based on the mean of all the points mentioned.

17. The tool monitoring method as described in claim 16, characterized in that, The step of determining the alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitted curves includes: Obtain all point differences corresponding to each of the sampling points; Determine the maximum value among the absolute values ​​of the point differences corresponding to all the sampling points in the same work phase, and record the maximum value as the alarm threshold corresponding to that work phase.

18. The tool monitoring method as described in claim 16, characterized in that, After determining the simulation fitting curve and alarm threshold for monitoring the real-time operating condition of the tool based on all the initial fitting curves, the method further includes: The system receives a call request sent by the monitoring terminal, which is generated after the monitoring terminal receives the tool monitoring instruction. In response to the call request, after the monitoring terminal calls the simulation fitting curve and the alarm threshold, it collects real-time rotation speed and real-time current. After determining that the tool has entered the working cycle based on the real-time rotation speed, it determines the current difference corresponding to the real-time current based on the simulation fitting curve, and then generates monitoring results based on the current difference and the alarm threshold.

19. A tool monitoring method, characterized in that, Applications to monitoring terminals include: The simulation fitting curve and alarm threshold are obtained, and the real-time operating condition of the tool is monitored based on the simulation fitting curve and alarm threshold; the simulation fitting curve and alarm threshold are determined as follows: After receiving the operating condition data collected and reported by the monitoring terminal within the target time period, the data processing platform determines the operating current corresponding to each working cycle from the current data in the operating condition data based on the speed data in the operating condition data. The operating current corresponding to each working cycle includes a set of current data corresponding to a set of speed change data. The set of speed change data includes a first speed segment that meets the preset speed increase condition, a second speed segment that meets the preset speed decrease condition, and a stable speed segment connected between the adjacent first speed segment and the second speed segment. Curve fitting is performed based on all the operating currents to obtain multiple initial fitting curves corresponding one-to-one with each of the operating cycles. The operating cycle includes a starting operating stage corresponding to the first speed range, a stable operating stage corresponding to the stable speed range, and a ending operating stage corresponding to the second speed range. Each initial fitting curve corresponding to the operating cycle includes a first starting time period corresponding to the starting operating stage, a first intermediate time period corresponding to the stable operating stage, and a first ending time period corresponding to the ending operating stage. The simulation fitting curve includes a second starting time period corresponding to the starting operating stage, a second intermediate time period corresponding to the stable operating stage, and a second ending time period corresponding to the ending operating stage. Based on all the initial fitting curves, a simulation fitting curve and an alarm threshold are determined for monitoring the real-time operating condition of the tool. Each operation stage corresponds to an alarm threshold, and the alarm threshold corresponding to an operation stage is the maximum value among the absolute values ​​of the point differences corresponding to all sampling points in the operation stage. The point difference refers to the difference between the point data corresponding to the same sampling point and the point mean. The operation stage includes the start operation stage, the stable operation stage, and the end operation stage of the operation cycle.

20. The tool monitoring method as described in claim 19, characterized in that, The step of acquiring the simulation fitting curve and alarm threshold, and monitoring the real-time operating condition of the tool based on the simulation fitting curve and alarm threshold, includes: After receiving the tool monitoring command, the simulation fitting curve and the alarm threshold are retrieved from the data processing platform, and real-time rotational speed and real-time current are collected. After determining the entry of the tool into the working cycle based on the real-time rotation speed, the current difference corresponding to the real-time current is determined based on the simulation fitting curve; The monitoring results are generated based on the current difference and the alarm threshold.

21. The tool monitoring method as described in claim 20, characterized in that, After determining the entry of the tool into the working cycle based on the real-time rotation speed, determining the current difference corresponding to the real-time current based on the simulation fitting curve includes: Determine whether the real-time rotational speed meets the preset speed surge requirement; When the preset speed increase requirement is met, the tool is determined to enter the working cycle, and the start time of entering the working cycle is recorded; Before determining that the cutting tool has not ended the operation cycle, the fitting current corresponding to the current time point is determined according to the simulation fitting curve and the starting time point, and the absolute value of the difference between the real-time current and the fitting current is recorded as the current difference value at the current time point.

22. The tool monitoring method as described in claim 20, characterized in that, The step of generating monitoring results based on the current difference and the alarm threshold includes: Before determining that the cutting tool has not ended the work cycle, the current work stage in the work cycle is obtained based on the real-time rotation speed; the current work stage is one of the start work stage, stable work stage, and end work stage of the work cycle; Obtain the alarm threshold corresponding to the current operation stage, and determine whether the current difference at the current time point is greater than the alarm threshold; When the current difference is greater than the alarm threshold, the monitoring result is confirmed as a tool abnormality and an alarm message is generated; When the current difference is less than or equal to the alarm threshold, the monitoring result is confirmed to be that the tool is normal.

23. A data processing platform, characterized in that, Used to perform the tool monitoring method as described in any one of claims 12 to 18.

24. A monitoring terminal, characterized in that, Used to perform the tool monitoring method as described in any one of claims 19 to 22.

25. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the tool monitoring method as described in any one of claims 12 to 22.

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