Method and system for measuring working condition of aluminum chips in wheel hub pad, storage medium and electronic device

Abstract

A method, system, storage medium, and electronic device for measuring aluminum shavings accumulation on wheel hub pads are disclosed. This system is designed for detecting aluminum shavings accumulation in the chuck of a machining center during wheel hub machining. The system includes an edge computer, a current sensor, and a machining center control unit. The edge computer is located at the edge of the machining center, and the current sensor is located at the spindle motor, monitoring the three-phase power supply of the spindle. The machining center control unit modifies the internal ladder diagram of the machining center to enable external alarms. The edge computer can collect the spindle motor current of the machining center via the current sensor and, combined with the machining center's parameters, promptly issue an alarm when aluminum shavings are detected under the wheel hub, ensuring quality.

Description

Technical Field

[0001] This invention relates to the field of machining equipment technology, specifically to a method and system for measuring the working condition of aluminum chips in wheel hub gaskets, a storage medium, and an electronic device. Background Technology

[0002] Currently, existing machining centers produce aluminum shavings when machining aluminum wheels, which fall onto the chuck. The wheel is then placed on the machining center chuck for machining. After machining, the chuck is flushed with water to remove the aluminum shavings. Although it is hoped that the aluminum shavings can be flushed away by starting the water pump, sometimes not all of the aluminum shavings are flushed away, and some remain on the chuck.

[0003] When a wheel hub is placed on the machining center with aluminum shavings underneath, it causes uneven placement, resulting in a shavings-covered wheel hub condition. This leads to dimensions exceeding tolerances and causing quality defects. For the wheel hub structure, this particularly affects the bolt hole thickness, bolt hole chamfer, valve hole position, and the dimensional abnormalities of the valve hole grooves, thus impacting assembly and significantly affecting the product. Currently, without specialized equipment, existing machining centers cannot detect whether the rinsing is thorough, posing a serious quality risk. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide a system for measuring the condition of aluminum chips in wheel hub pads. By separately detecting the three-phase power supply, the accuracy of the detection is greatly improved, enabling accurate detection of the presence or occurrence of aluminum chip conditions in the machining center, ensuring the quality of wheel hub products, and thus protecting the safety of vehicle users.

[0005] According to one aspect of the present invention, a system for measuring the condition of aluminum chips under a wheel hub pad is provided for detecting whether aluminum chips are present under a wheel hub placed on a machining center. The system includes: an edge computer, a machining center control unit, and a current sensor. The edge computer is located at the edge of the machining center and interacts with the machining center control unit to read the current parameters of the machining center. The edge computer has a display screen. The machining center control unit is a machining center ladder diagram PMC control unit, capable of modifying the ladder diagram to accept information from the edge computer. The current sensor includes current detection and data transmission functions, respectively monitoring the three-phase current of the machining center's spindle motor and transmitting it to the edge computer. The system includes: a real-time variable establishment and three-phase current value detection module: when the first wheel hub is being processed, real-time variables required for aluminum chip error modeling are established, including tool number, compensation value, spindle current value, and program number, and the three-phase current value of the spindle current is measured in real-time using the current sensor; a sample value calculation module: calculating sample current values ​​of the real-time spindle motor current based on the three-phase current values; and a sample current value segmentation and real-time variable set modeling module: according to the settings on the display screen... The tool number and program number are used to segment the sample current values. Segmentation begins when the real-time tool number and program number are set. This segmentation point serves as the initial training population. The initialized population is trained using a standard error method support vector regression (SVR) program. The fitness of the trained model is evaluated using an SVR model. The optimal training model is selected when the R-squared score on the test set is less than 1. A standard genetic algorithm is used to establish a real-time variable set model for classification. The upper and lower limit correction module continuously corrects the upper and lower limits of the error range for aluminum chip pads using the real-time variable set model and training samples. The current value is compared with the current model. Optimization Module: When the next wheel hub is processed, the real-time variable set model and the actual machining spindle current value are compared and calculated. When the actual machining spindle current value does not exceed the upper and lower limits of the error range, the current model is further optimized using a genetic algorithm. Alarm Module: When the actual machining spindle current value exceeds the upper and lower limits of the error range, an alarm is issued, triggering the machining center shutdown module. Machining Center Shutdown Module: An abnormal alarm message is sent from the edge computer to the machining center control unit. By modifying the parameters in the ladder diagram, I / O signals are triggered to adjust the machining center's operating status and control the shutdown.

[0006] According to another aspect of the present invention, a method for measuring the aluminum chip condition of a wheel hub pad is provided, comprising: Step 1: When the first wheel hub is being processed, establishing real-time variables required for aluminum chip error modeling, including tool number, compensation value, spindle current value, and program number, and measuring the spindle current value in real time to obtain the detected three-phase current values ​​a1, a2, and a3, which represent the U, V, and W three-phase current values ​​respectively; Step 2: arranging the three-phase currents according to:

[0007] ,

[0008] Step 3: Calculate the sample current value Y of the real-time spindle current; Step 4: Divide the sample current value Y according to the tool number and program number set on the display screen. When the real-time tool number and real-time program number are the set values, the division begins. If either changes, the division ends. This division point serves as the initial training population. The initialized population is trained using a standard error method support vector regression (SVR) program. The fitness of the training model is evaluated using an SVR model. If the R-squared score on the test set is less than 1, it is the optimal training model. A standard genetic algorithm is used to establish a classification real-time variable set model; Step 5: Use this real-time variable set model and training samples to continuously correct the upper and lower limits of the error range for aluminum chip padding; Step 6: When the next wheel hub is processed, compare the real-time variable set model obtained in Step 3 with the actual spindle motor current value. When the actual spindle motor current value does not exceed the upper and lower limits mentioned in Step 4, use a genetic algorithm to further optimize the model, which becomes the current model.

[0009] ,

[0010] in This refers to the Y coordinate of the current model, where model represents the current model, second represents the number of milliseconds, and n represents the actual number of wheel hubs processed. After updating the current model, proceed to step six. When the upper and lower limits mentioned in step four are exceeded, an alarm is issued, and proceed to step seven.

[0011] Step 6: If the compensation value or program number does not change, repeat step 5; if the compensation value or program number changes, repeat step 3. Step 7: By modifying the parameters in the ladder diagram, trigger the IO signal to adjust the operating status of the machining center and control its shutdown.

[0012] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein a plurality of instructions are stored therein; the plurality of instructions are configured to be loaded by a processor and to execute the steps of the above-described method.

[0013] According to another aspect of the present invention, an electronic device is provided, comprising: a processor for executing a plurality of instructions; and a memory for storing the plurality of instructions; wherein the plurality of instructions are stored in the memory and loaded by the processor to execute the steps of the above method.

[0014] According to the present invention, the system parameters can be controlled using an edge computer, and the parameters can be adjusted at any time on the touch screen. The parameters can also be traced, making operation convenient. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the system for measuring the working condition of aluminum chips in wheel hub pads according to an embodiment of the present invention;

[0017] Figure 2 This is a schematic diagram of the system's operation;

[0018] Figure 3 It is the real-time variable set model of the system. Detailed Implementation

[0019] Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. The exemplary embodiments described below and illustrated in the drawings are intended to teach the principles of the invention, enabling those skilled in the art to implement and use the invention in various environments and for various applications. Therefore, the scope of protection of the present invention is defined by the appended claims, and the exemplary embodiments are not intended, and should not be considered, a limiting description of the scope of protection of the present invention. Furthermore, for ease of description, the same elements in the drawings are indicated by the same or similar reference numerals, and the dimensions of the various parts shown are not necessarily drawn to actual scale. Regarding orientational descriptions, such as the longitudinal direction corresponding to the length of the main body, and the orientations or positional relationships indicated by up, down, left, right, top, bottom, etc., are all based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. The following description of the various embodiments emphasizes the differences between the various embodiments, and their similarities or commonalities can be referred to mutually. For the sake of brevity, they will not be described in detail. The technical features of the different embodiments can be freely combined to form more embodiments according to design needs. The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. The reference to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments. The technical solutions in the embodiments of this application 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 this application. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0020] Example 1:

[0021] This embodiment 1 provides a system for measuring the working condition of aluminum chips in wheel hub gaskets, such as... Figure 1The structural diagram shown includes an edge computer, a machining center control unit, a machining center (not shown), and a current sensor.

[0022] The edge computer is located at the edge of the machining center and interacts with the machining center control unit using the Focas protocol. It reads the current parameters of the machining center and promptly triggers an alarm when a problem is detected. The edge computer has a built-in display screen that allows direct observation of the real-time spindle motor current value. It can input the specific tool number to be monitored and can also start and stop software operation on the screen, recording data in the edge computer for traceability. Thus, the edge computer can be used to control the system parameters, which can be adjusted at any time on the touchscreen, and traceability can be performed, making operation convenient.

[0023] The machining center is the hardware for specific monitoring. It has a chuck and can provide program numbers, tool numbers, etc., to the edge computer. For example, the machining center can automatically transmit machining parameters to the edge computer at a fixed frequency of 500ms; the edge computer can read the spindle motor current value of the machining center at a frequency of 1ms.

[0024] The machining center control unit is a machining center ladder diagram PMC control unit. By modifying the ladder diagram, it can be converted into a form that can receive information from the edge computer, thereby generating an alarm.

[0025] The current sensor includes current detection and data transmission functions, monitoring the three-phase current of the spindle motor with an accuracy of 0.001A power change at a frequency of 1000Hz, and transmitting data via the Modbus protocol. By separately detecting the three-phase current and transmitting the current values ​​to the edge computer via the Modbus protocol, the accuracy and speed of detection are greatly improved.

[0026] Because the drill bit moves vertically up and down, when the wheel hub is uneven due to aluminum chips, the cutting current will show an anomaly compared to a normally machined wheel. Therefore, by using algorithms to analyze this, when the machining current becomes abnormal, it's possible to accurately detect whether or not aluminum chips are present in the machining center, thus ensuring wheel hub product quality and protecting the safety of vehicle users.

[0027] Example 2

[0028] like Figure 2 As shown, the tool number, current upper and lower limits, and IP address of the machining center are first written and set through the edge computer's display screen, such as a touch screen, and previous alarms and change records can be queried.

[0029] The edge computer measures the three-phase current of the spindle motor of the machining center by a current sensor, reads the real-time machining parameters of the machining center, performs big data calculations, and sends an abnormal alarm message to the machining center control unit when an abnormal alarm is detected, thereby controlling the machining center to alarm and stop.

[0030] <Exemplary Method>

[0031] According to the present invention, a method for measuring the aluminum chip condition of wheel hub pads based on a real-time variable set model is provided. Figure 3 The model of the real-time variable set after segmentation is shown. This method mainly calculates the current of the machining center motor. The calculation steps are as follows:

[0032] Step 1: When the first hub is being machined, establish the real-time variables required for aluminum chip error modeling, including tool number, compensation value, spindle current value, program number, and the real-time measured spindle current value is the three-phase current value detected by the high-precision sensor (a1, a2, a3, representing the U, V, and W three-phase current values ​​respectively).

[0033] Step 2: Adjust the three-phase currents (a1, a2, a3) according to:

[0034] ,

[0035] The sample current value Y of the real-time spindle current value is calculated;

[0036] Step 3: Segment the sample current value Y according to the tool number and program number set on the display screen. Segmentation begins when the real-time tool number and program number are the set values. If either changes, the segmentation ends. This segmented end serves as the initial training population. The initialized population is trained using a Support Vector Regression (SVR) program based on the standard error method. The fitness of the trained model is evaluated using the SVR model. The optimal training model is one with an R-squared score less than 1 on the test set. A standard genetic algorithm is used to establish a real-time variable set model for classification. The X value of this real-time variable set model (corresponding to...) Figure 3 The x-axis represents the millisecond (ms) value at which the current value Y is divided (corresponding to...). Figure 3 The vertical axis represents the principal shaft current value of the segmented portion;

[0037] Step 4: Continuously adjust the upper and lower limits of the error range of aluminum chip pads using the real-time variable set model and training samples;

[0038] Step 5: When the next wheel hub is processed, the real-time variable set model obtained in Step 3 is compared with the actual spindle motor current value. If it does not exceed the upper and lower limits mentioned in Step 4, the model is further optimized using a genetic algorithm, which becomes the current model.

[0039] ,

[0040] in This refers to the Y-coordinate of the current model, where model represents the current model, second represents the number of milliseconds, and n represents the actual number of wheel hubs processed.

[0041] After updating the current model, proceed to step six;

[0042] When the upper and lower limits described in step four are exceeded, it indicates that the degree of cutting by the drill bit is abnormal, an alarm is issued, and the process proceeds to step seven.

[0043] Step Six: If the compensation value or program number does not change, repeat Step Five; if the compensation value or program number changes, repeat Step Three.

[0044] Step 7: By modifying the parameters in the ladder diagram, I / O signals are triggered to adjust the operating status of the machining center and control its shutdown.

[0045] As described above, according to the present invention, the location that needs to be monitored can be determined by analyzing the machining path and the hub structure. Using the corresponding tool number and the current value of its spindle motor sensor, the machine can learn the machining situation of each round and use a genetic algorithm to immediately alarm and stop the machine when a clear abnormality is found in the machining, and remind on-site personnel to check whether there are aluminum chips under the hub.

[0046] <Exemplary System>

[0047] According to the present invention, a system for measuring the working condition of aluminum chips in wheel hub pads is provided, comprising:

[0048] Real-time variable establishment and three-phase current value detection module: When the first hub is processed, the real-time variables required for aluminum chip error modeling are established, including tool number, compensation value, spindle current value, program number, and the three-phase current value of the spindle current is measured in real time.

[0049] Sample value calculation module: Calculates sample current values ​​of the real-time spindle motor current based on three-phase current values;

[0050] Sample current value segmentation and real-time variable set modeling module: The sample current value is segmented according to the tool number and program number set on the display screen. When the real-time tool number and real-time program number are the set values, the segmentation begins. This segmentation end serves as the initial training population. The initialized population is trained using the standard error method support vector regression machine program. The fitness of the trained model is evaluated using the SVR model. If the R-squared score on the test set is less than 1, it is the optimal training model. The standard genetic algorithm is used to establish a classification real-time variable set model.

[0051] Upper and lower limit correction module: continuously corrects the upper and lower limits of the error range of aluminum chip pads using a real-time variable set model and training samples;

[0052] Current value comparison and current model optimization module: When the next wheel hub is processed, the real-time variable set model and the actual processing spindle current value are compared and calculated. When the error range is within the upper and lower limits, the genetic algorithm is used to further optimize the current model.

[0053] Alarm module: When the actual machining spindle current value exceeds the upper or lower limit of the error range, an alarm is issued, triggering the machining center shutdown module;

[0054] Machining center shutdown module: The edge computer sends an abnormal alarm message to the machining center control unit, and by modifying the parameters in the ladder diagram, triggers IO signals to adjust the operating status of the machining center and control the shutdown.

[0055] Compared with existing technologies, the method and system of this invention have the following characteristics: 1. It utilizes Internet of Things (IoT) technology to connect the machining center and external sensors for analysis and calculation, improving accuracy; 2. Compared with previous vehicle inspection methods, it requires less external hardware and eliminates the need to modify the machining center, resulting in lower costs; 3. It has high accuracy, capable of detection at a frequency of 1ms, ensuring extremely high coverage and preventing the omission of aluminum shavings from the chuck pads. This benefits industry promotion by: 1. Ensuring quality and avoiding assembly problems caused by improper flushing leading to aluminum shavings from the chuck pads; 2. Utilizing big data analysis, by analyzing current data from multiple wheel types and drill bits, calculating current values, and continuously fitting models, making the detection of aluminum shavings from wheel hub pads more accurate, improving precision, and fully leveraging the deep integration of the Internet and industrial manufacturing to achieve intelligent manufacturing; 3. Further optimizing the wheel hub processing technology, enabling technological iteration and updates in the wheel hub industry.

[0056] In addition to the methods and systems described above, embodiments of this disclosure may also be an electronic device comprising: a processor for executing a plurality of instructions; and a memory for storing the plurality of instructions; wherein the plurality of instructions are stored in the memory and loaded by the processor to execute the methods described above.

[0057] Furthermore, embodiments of this disclosure may also be computer-readable storage media having computer program instructions stored thereon, which, when executed by a processor, cause the processor to perform the steps in the "Exemplary Method" section.

[0058] In the description of this application, "a plurality of" means two or more, unless otherwise expressly specified. Unless otherwise expressly specified and limited, the terms "installed," "connected," "linked," "fixed," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; a mechanical connection or an electrical connection; a direct connection or an indirect connection through an intermediate medium; or the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances. Although the invention has been described with reference to various specific embodiments, it should be understood that modifications can be made within the spirit and scope of the described inventive concept. Therefore, it is intended that the invention be limited to the described embodiments but will have the full scope defined by the language of the appended claims.

Claims

1. A system for measuring the condition of aluminum chips under a wheel hub pad, used to detect whether aluminum chips are present under a wheel hub placed on a machining center, characterized in that, include: Edge computer, machining center control unit, and current sensor, among which, The edge computer is located at the edge of the machining center and interacts with the machining center control unit to read the current parameters of the machining center. The edge computer has a display screen. The machining center control unit is a ladder diagram PMC control unit for machining centers, which can modify the ladder diagram to convert it into a form that can receive information from edge computers; The current sensor includes current detection and data transmission functions, monitoring the three-phase current of the spindle motor in the machining center and transmitting it to the edge computer. The system includes: Real-time variable establishment and three-phase current value detection module: When the first hub is processed, the real-time variables required for aluminum chip error modeling are established, including tool number, compensation value, spindle current value, and program number. The three-phase current value of the spindle current is measured in real time using a current sensor to obtain the detected three-phase current values ​​a1, a2, and a3, which represent the U, V, and W three-phase current values, respectively. Sample value calculation module: Based on three-phase current values ​​according to: ， Calculate the sample current value Y of the real-time spindle motor current; Sample current value segmentation and real-time variable set modeling module: The sample current value Y is segmented according to the tool number and program number set on the display screen. When the real-time tool number and real-time program number are the set values, the segmentation begins. This segmentation end serves as the initial training population. The initialized population is trained using the standard error method support vector regression machine program. The fitness of the trained model is evaluated using the SVR model. If the R-squared score on the test set is less than 1, it is the optimal training model. The standard genetic algorithm is used to establish a classification real-time variable set model. Upper and lower limit correction module: continuously corrects the upper and lower limits of the error range of aluminum chip pads using a real-time variable set model and training samples; Current value comparison and current model optimization module: When the next wheel hub is processed, the real-time variable set model and the actual machining spindle current value are compared and calculated. When the actual machining spindle current value does not exceed the upper or lower limit of the error range, the current model is further optimized using a genetic algorithm, which is the current model. ， in This refers to the Y-coordinate of the current model, where model represents the current model, second represents the number of milliseconds, and n represents the actual number of wheel hubs processed. Alarm module: When the actual machining spindle current value exceeds the upper or lower limit of the error range, an alarm is issued, triggering the machining center shutdown module; Machining center shutdown module: The edge computer sends an abnormal alarm message to the machining center control unit, which then modifies the parameters in the ladder diagram to trigger I / O signals, thereby adjusting the machining center's operating status and controlling its shutdown. The machining center automatically transmits machining parameters to the edge computer at a fixed frequency of 500ms; the edge computer reads the spindle motor current value of the machining center at a frequency of 1ms. The current sensor monitors the three-phase current of the spindle motor with an accuracy of 0.001A power change and a frequency of 1000Hz.

2. The system according to claim 1, characterized in that, The edge computer interacts with the machining center control unit using the Focas protocol, while the current sensor sends data to the edge computer via the Modbus protocol.

3. The system according to claim 1, characterized in that, The display screen has a touch function and is used to write and set the tool number, current upper and lower limits, and IP address of the machining center.

4. A method for measuring the working condition of aluminum chips in wheel hub gaskets, characterized in that, To implement the functions of the system according to any one of claims 1 to 3, including: Step 1: When the first hub is being processed, establish the real-time variables required for aluminum chip error modeling, including tool number, compensation value, spindle current value, and program number. Measure the spindle current value in real time to obtain the detected three-phase current values ​​a1, a2, and a3, which represent the U, V, and W three-phase current values, respectively. Step 2: Adjust the three-phase currents according to: ， The sample current value Y of the real-time spindle current value is calculated; Step 3: Segment the sample current value Y according to the tool number and program number set on the display screen. When the real-time tool number and real-time program number are the set values, the segmentation begins. If either changes, the segmentation ends. This segmentation point serves as the initial training population. The initialized population is trained using the standard error method support vector regression machine program. The fitness of the trained model is evaluated using the SVR model. If the R-squared score on the test set is less than 1, it is the optimal training model. The standard genetic algorithm is used to establish a real-time variable set model for classification. Step 4: Continuously adjust the upper and lower limits of the error range of aluminum chip pads using the real-time variable set model and training samples; Step 5: When processing the next wheel hub, compare the real-time variable set model obtained in Step 3 with the actual machining spindle motor current value. When the actual machining spindle motor current value does not exceed the upper and lower limits mentioned in Step 4, use a genetic algorithm to further optimize the model, which becomes the current model. ， in This refers to the Y-coordinate of the current model, where model represents the current model, second represents milliseconds, and n represents the actual number of wheel hubs processed. After updating the current model, proceed to step six. When the upper and lower limits described in step four are exceeded, an alarm is issued and the process proceeds to step seven. Step Six: If the compensation value or program number does not change, repeat Step Five; if the compensation value or program number changes, repeat Step Three. Step 7: By modifying the parameters in the ladder diagram, trigger the IO signal to adjust the operating status of the machining center and control its shutdown.

5. A computer-readable storage medium storing a plurality of instructions; the plurality of instructions being loaded by a processor and executing the steps of the method of claim 4.

6. An electronic device, characterized in that, The electronic device includes: a processor for executing multiple instructions; and a memory for storing multiple instructions; wherein the multiple instructions are stored in the memory and loaded by the processor to execute the steps of the method as described in claim 4.

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