Intelligent control method and device for die casting deburring process

Abstract

The invention discloses an intelligent control method and device for a die casting deburring process. The intelligent control method comprises the steps that a grinding head advancing track is generated according to a trimming contour of a die casting; the method comprises the following steps: extracting burr characteristics by analyzing a die casting image, and matching proper deburring audio data according to the burr characteristics; the abrasion degree of the grinding head is detected, the advancing track of the grinding head is corrected, and meanwhile corresponding grinding head control data are generated; and in the deburring process, audio feature data are collected in real time and compared with preset audio data, and if the similarity does not reach the standard, the grinding head track and the control data are adjusted. By accurately analyzing the abrasion of the grinding head and automatically correcting the track and control parameters of the grinding head, the high-quality and high-efficiency deburring effect is ensured in combination with real-time audio monitoring, manual intervention is reduced, the service life of equipment is prolonged, and the product consistency is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent manufacturing technology, and in particular to an intelligent control method and device for a die-casting deburring process. Background Art

[0002] With the development of industrial manufacturing, the quality requirements of die castings are getting higher and higher, and the presence of burrs seriously affects the appearance and performance of products. Traditional deburring processes often rely on manual operations, which are not only inefficient but also prone to errors. Without effective wear monitoring and adjustment strategies, grinding head wear may lead to reduced deburring effects and even damage the workpiece surface. Control parameters such as rotation speed and travel speed are usually fixed and cannot be dynamically adjusted according to actual conditions, which limits the flexibility and adaptability of deburring. Summary of the invention

[0003] In order to solve at least one of the technical problems mentioned above, the present invention provides a method and device for intelligent control of deburring process of die castings.

[0004] In a first aspect, the present invention provides a method for intelligently controlling a deburring process of a die casting, the method comprising:

[0005] Obtain the trimming profile of the die casting and generate the grinding head travel trajectory according to the trimming profile;

[0006] Acquire a die-casting image, extract burr features on the grinding head travel trajectory according to the die-casting image, obtain a burr feature sequence, and match multiple burr audio data from a preset deburring audio database based on the burr feature sequence;

[0007] Detecting the wear degree of the grinding head, correcting the grinding head travel trajectory according to the wear degree, and generating grinding head control data according to the wear degree; the wear degree of the grinding head includes the wear working radius and the wear missing angle;

[0008] Deburring the die casting according to the grinding head control data, and collecting audio feature data corresponding to different burr features in real time during the deburring process;

[0009] The audio similarity between the current audio feature data and the corresponding burr audio data is analyzed. When the audio similarity does not meet the preset conditions, the current deburring process is stopped and the grinding head travel trajectory and grinding head control data are corrected again.

[0010] The method of detecting the wear degree of the grinding head and correcting the moving track of the grinding head according to the wear degree includes:

[0011] Obtain the distance from the highest point on the grinding head to the central axis, obtain the wear working radius, and obtain the wear loss angle of the worn part of the grinding head;

[0012] The grinding head travel trajectory is corrected according to the wear working radius.

[0013] Preferably, the grinding head control data includes the grinding head rotation speed and the grinding head travel speed;

[0014] The step of generating grinding head control data according to the degree of wear includes:

[0015] The wear working radius and the wear loss angle are input into the preset wear influence algorithm to obtain the wear influence. The wear influence algorithm is expressed as:

[0016]

[0017] Where, T eff is the wear influence, R max is the wear working radius, R0 is the initial grinding head working radius, and θ is the wear loss angle;

[0018] The initial grinding head speed is divided by the wear influence to obtain the corrected grinding head speed. If the corrected grinding head speed is greater than the preset maximum speed, the maximum speed is used as the new grinding head speed, and the grinding head travel speed is updated according to the preset travel speed correction algorithm. The travel speed correction algorithm is expressed as:

[0019]

[0020] Where V r is the initial grinding head speed, V f is the initial grinding head travel speed, V f , is the corrected travel speed, is the maximum speed, T eff The impact of wear.

[0021] Preferably, the method further comprises: when the wear impact is less than a preset threshold, prompting to replace the grinding head.

[0022] Preferably, the method further comprises:

[0023] According to the size feature in the burr feature, the burrs are divided into burr levels, and different burr audio data are matched from the database based on different burr levels.

[0024] In a second aspect, the present invention further provides an intelligent control device for deburring a die casting, the device comprising:

[0025] A travel trajectory generation module is used to obtain the trimming profile of the die casting and generate a grinding head travel trajectory according to the trimming profile;

[0026] A burr audio acquisition module is used to acquire a die-casting image, extract burr features on the grinding head travel track according to the die-casting image, obtain a burr feature sequence, and match multiple burr audio data from a preset deburring audio database based on the burr feature sequence;

[0027] A grinding head control data generation module is used to detect the wear degree of the grinding head, correct the grinding head travel trajectory according to the wear degree, and generate grinding head control data according to the wear degree; the wear degree of the grinding head includes the wear working radius and the wear missing angle;

[0028] A deburring processing module is used to perform deburring on the die casting according to the grinding head control data, and collect audio feature data corresponding to different burr features in real time during the deburring process;

[0029] The burr audio comparison module is used to analyze the audio similarity between the current audio feature data and the corresponding burr audio data. When the audio similarity does not meet the preset conditions, the current deburring process is stopped and the grinding head travel trajectory and grinding head control data are corrected again.

[0030] Preferably, the grinding head control data generating module includes:

[0031] The grinding head wear degree acquisition unit is used to obtain the distance from the highest point on the grinding head to the central axis, obtain the wear working radius, and obtain the wear loss angle of the worn part of the grinding head;

[0032] The travel trajectory correction unit is used to correct the travel trajectory of the grinding head according to the wear working radius.

[0033] Preferably, the grinding head control data generating module further includes:

[0034] The wear influence calculation unit is used to input the wear working radius and the wear loss angle into a preset wear influence algorithm to obtain the wear influence. The wear influence algorithm is expressed as:

[0035]

[0036] Where, T eff is the wear influence, R max is the wear working radius, R0 is the initial grinding head working radius, and θ is the wear loss angle;

[0037] The grinding head control data calculation unit is used to divide the initial grinding head speed by the wear influence to obtain the corrected grinding head speed. If the corrected grinding head speed is greater than the preset maximum speed, the maximum speed is used as the new grinding head speed, and the grinding head travel speed is updated according to the preset travel speed correction algorithm. The travel speed correction algorithm is expressed as:

[0038]

[0039] Where V r is the initial grinding head speed, V f is the initial grinding head travel speed, V f , is the corrected travel speed, is the maximum speed, T eff The impact of wear.

[0040] Preferably, the grinding head control data generating module further includes:

[0041] The grinding head replacement reminder unit is used to remind the user to replace the grinding head when the wear impact is less than a preset threshold.

[0042] Preferably, the device further comprises:

[0043] The burr level classification module is used to classify the burrs according to the size characteristics in the burr characteristics, and match different burr audio data from the database based on different burr levels.

[0044] In a third aspect, the present invention further provides an electronic device comprising a processor and a memory, wherein the memory is used to store computer program code, and the computer program code comprises computer instructions. When the processor executes the computer instructions, the electronic device executes the method as described in the first aspect above and any possible implementation thereof.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1) The present invention accurately analyzes the degree of wear of the grinding head and automatically corrects the grinding head travel trajectory and grinding head control data according to the analysis results, thereby ensuring that a consistent and high-quality deburring effect can be maintained even when the grinding head is worn. Furthermore, by real-time monitoring of the audio data during the deburring process and comparing it with the preset deburring audio data, the effectiveness of the deburring process can be ensured. Once it is found that the audio similarity does not meet the preset conditions, it indicates that the deburring effect is not good. At this time, the device will automatically stop the current deburring process and correct the grinding head travel trajectory and control data again. This closed-loop control strategy not only improves the accuracy and efficiency of deburring, but also reduces dependence on manual monitoring, effectively extends the service life of the equipment, and ensures the consistency of product quality, thereby significantly improving the intelligence level of the entire deburring process.

[0047] 2) The present invention inputs the wear working radius and the wear missing angle into a preset wear influence algorithm to calculate the wear influence, which is used to measure the ratio of the actual working efficiency of the grinding head to the working efficiency in the unworn state. Afterwards, the initial grinding head speed is divided by the wear influence to obtain the corrected grinding head speed. This step helps to maintain a relatively stable working efficiency of the grinding head under wear conditions. Furthermore, based on the corrected grinding head speed and the preset maximum speed, it is determined whether the travel speed of the grinding head needs to be adjusted to ensure that the grinding head always maintains the best working state during the entire deburring process. By real-time monitoring and adjusting the grinding head control parameters, it is ensured that each deburring operation meets the preset standards, thereby ensuring the consistency of product quality.

[0048] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below.

[0050] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used to illustrate the technical solutions of the present disclosure together with the specification.

[0051] Figure 1 A schematic diagram of a process flow of an intelligent control method for a die casting deburring process provided by an embodiment of the present invention;

[0052] Figure 2 A schematic diagram of the principle of the grinding head travel trajectory correction provided by an embodiment of the present invention;

[0053] Figure 3 A schematic diagram of the structure of an intelligent control device for deburring a die casting provided by an embodiment of the present invention;

[0054] Figure 4 The embodiment of the present invention provides Figure 3 A schematic diagram of the structure of the submodules of the middle grinding head control data generation module;

[0055] Figure 5 A schematic structural diagram of an intelligent control device for deburring a die casting provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0058] Traditional deburring processes often rely on manual operations, which are not only inefficient but also prone to errors.

[0059] See also Figure 1 , Figure 1 The following is a flow chart of an intelligent control method for a die casting deburring process provided by an embodiment of the present invention. Figure 1 As shown, the method includes:

[0060] S100, obtaining a trimming profile of the die casting, and generating a grinding head travel trajectory according to the trimming profile;

[0061] In this embodiment, the contour information of the die casting is obtained through three-dimensional scanning or computer-aided design (CAD) model, and the optimal grinding head travel trajectory is calculated using a path planning algorithm. The die casting is scanned using a high-precision three-dimensional laser scanner to obtain three-dimensional point cloud data of the die casting surface, and the point cloud data is imported into the CAD software to build a three-dimensional model of the die casting. The path planning algorithm is used to calculate the optimal travel trajectory of the grinding head based on the three-dimensional model of the die casting. The calculated trajectory is converted into a robot executable instruction through reverse engineering software to ensure that the grinding head can accurately move along the position where the burrs need to be removed.

[0062] S200, acquiring a die-casting image, extracting burr features on a grinding head travel trajectory according to the die-casting image, obtaining a burr feature sequence, and matching a plurality of burr audio data from a preset deburring audio database based on the burr feature sequence;

[0063] Use industrial cameras to shoot die castings from multiple angles to obtain clear surface images, and use image processing algorithms, such as edge detection and morphological operations, to identify burr features on the surface of die castings. These algorithms can determine the key attributes of burrs, such as location, size, and shape, and form a burr feature sequence. Build a model based on deep learning or other machine learning technologies to match the audio data closest to the current burr feature from a preset deburring audio database. The model can be trained to learn the correspondence between different burr features and audio features, thereby achieving fast and accurate matching.

[0064] S300, detecting the wear degree of the grinding head, correcting the grinding head travel trajectory according to the wear degree, and generating grinding head control data according to the wear degree; the wear degree of the grinding head includes the wear working radius and the wear missing angle;

[0065] Use laser or visual inspection to regularly check the working area of ​​the grinding head, capture the slight changes on the grinding head surface, and calculate the working radius and wear loss angle of the grinding head after wear through image processing algorithms. Calculate the difference between the initial working radius of the grinding head and the working radius after wear to obtain the wear amount, and refer to Figure 2 , the grinding head travel trajectory is offset toward the die casting direction by the wear amount value to obtain the corrected grinding head travel trajectory.

[0066] The grinding head rotation speed and the grinding head travel speed are optimized and corrected according to the working radius and the wear loss angle (i.e. the degree of wear of the grinding head) after the grinding head is worn.

[0067] S400, performing deburring processing on the die casting according to the grinding head control data, and collecting audio feature data corresponding to different burr features in real time during the deburring process;

[0068] S500, analyzing the audio similarity between the current audio feature data and the corresponding burr audio data. When the audio similarity does not meet the preset conditions, the current deburring process is stopped and the grinding head travel trajectory and the grinding head control data are corrected again.

[0069] In this embodiment, a signal processing algorithm (such as fast Fourier transform FFT, wavelet transform, etc.) is used to analyze the spectral characteristics of the audio signal. It should be noted that fast Fourier transform and wavelet transform identify specific audio features, such as frequency, amplitude, etc.

[0070] Normalize the current audio feature data and the corresponding glitch audio data to make the sampling rates of the two audio files consistent. Use a noise reduction algorithm (such as spectral subtraction or Wiener filter) to remove background noise in the audio to improve the accuracy of subsequent processing. Convert the audio signal to a frequency domain representation to extract frequency and phase information. Use STFT to convert the time domain signal to a frequency-time representation to facilitate subsequent feature extraction. Extract MFCCs from the STFT results as audio features. It should be noted that MFCCs is one of the most commonly used features in speech recognition and reflects the characteristics of human auditory perception. Calculate the spectral contrast feature to reflect the energy distribution of different frequency components in the audio signal.

[0071] The extracted features are combined into a feature vector, which contains important characteristics of the audio, and a distance metric method of cosine similarity is selected to compare two feature vectors. In a possible embodiment, other distance metrics including but not limited to Euclidean distance and Mahalanobis distance can also be selected as distance metrics.

[0072] According to the selected distance measurement method, the similarity score between the feature vectors of the current audio feature data and the corresponding glitch audio data is calculated, and a threshold (obtained from empirical data) is set according to the actual situation to determine whether the similarity score is high enough. If the similarity score is higher than the threshold, the two audios are considered similar; otherwise, they are considered dissimilar.

[0073] In a possible embodiment, the MFCCs features of the current audio feature data and the corresponding burr audio data are extracted and represented as v A and v B , use cosine similarity to measure their similarity. Set the preset threshold to 0.85, that is, if the similarity is greater than 0.85, the two audios are considered similar; otherwise, they are considered dissimilar.

[0074] In this embodiment, by accurately analyzing the degree of wear of the grinding head and automatically correcting the grinding head travel trajectory and grinding head control data according to the analysis results, it is ensured that a consistent and high-quality deburring effect can be maintained even when the grinding head is worn. Furthermore, by real-time monitoring of the audio data during the deburring process and comparing it with the preset deburring audio data, the effectiveness of the deburring process can be ensured. Once it is found that the audio similarity does not meet the preset conditions, it indicates that the deburring effect is not good. At this time, the device will automatically stop the current deburring process and correct the grinding head travel trajectory and control data again. This closed-loop control strategy not only improves the accuracy and efficiency of deburring, but also reduces dependence on manual monitoring, effectively extends the service life of the equipment, and ensures the consistency of product quality, thereby significantly improving the intelligence level and economic benefits of the entire deburring process.

[0075] The method of detecting the wear degree of the grinding head and correcting the moving track of the grinding head according to the wear degree includes:

[0076] Obtain the distance from the highest point on the grinding head to the central axis, obtain the wear working radius, and obtain the wear loss angle of the worn part of the grinding head;

[0077] The grinding head travel trajectory is corrected according to the wear working radius.

[0078] Preferably, the grinding head control data includes the grinding head rotation speed and the grinding head travel speed;

[0079] The step of generating grinding head control data according to the degree of wear includes:

[0080] The wear working radius and the wear loss angle are input into the preset wear influence algorithm to obtain the wear influence. The wear influence algorithm is expressed as:

[0081]

[0082] Where, T eff is the wear influence, R max is the wear working radius, R0 is the initial grinding head working radius, and θ is the wear loss angle;

[0083] The initial grinding head speed is divided by the wear influence to obtain the corrected grinding head speed. If the corrected grinding head speed is greater than the preset maximum speed, the maximum speed is used as the new grinding head speed, and the grinding head travel speed is updated according to the preset travel speed correction algorithm. The travel speed correction algorithm is expressed as:

[0084]

[0085] Where V r is the initial grinding head speed, V f is the initial grinding head travel speed, V f , is the corrected travel speed, is the maximum speed, T eff The impact of wear.

[0086] In this embodiment, Used to calculate the wear influence T eff The wear impact reflects the degree of wear of the grinding head. It is a number between 0 and 1, which represents the ratio of the actual working efficiency of the grinding head to the working efficiency in the unworn state. Used to calculate the corrected grinding head travel speed V f ,The function of the travel speed correction algorithm is to adjust the travel speed of the grinding head according to the wear degree of the grinding head, so that the grinding head can still maintain a certain working efficiency in the worn state.

[0087] In this embodiment, the wear working radius and the wear missing angle are input into the preset wear influence algorithm to calculate the wear influence, which is used to measure the ratio of the actual working efficiency of the grinding head to the working efficiency in the unworn state. Afterwards, the initial grinding head speed is divided by the wear influence to obtain the corrected grinding head speed. This step helps to keep the grinding head at a relatively stable working efficiency under wear conditions. Furthermore, based on the corrected grinding head speed and the preset maximum speed, it is determined whether the travel speed of the grinding head needs to be adjusted to ensure that the grinding head always maintains the best working state during the entire deburring process. By real-time monitoring and adjusting the grinding head control parameters, it is ensured that each deburring operation meets the preset standards, thereby ensuring the consistency of product quality.

[0088] Preferably, the method further comprises:

[0089] According to the size feature in the burr feature, the burrs are divided into burr levels, and different burr audio data are matched from the database based on different burr levels.

[0090] In this embodiment, a series of burr size thresholds are set to classify burrs into multiple levels, such as small, medium, and large, and the burrs are classified into corresponding burr levels by measuring their sizes. Audio data of burrs of different levels during the removal process are collected and stored in a database. According to the burr level, the burr audio data of the corresponding level is searched in the database for subsequent comparison and analysis.

[0091] In a possible embodiment, three burr levels are set, namely small burrs (diameter less than 0.5 mm), medium burrs (diameter between 0.5 mm and 1.5 mm) and large burrs (diameter greater than 1.5 mm). Each level of burrs has its corresponding audio data. The audio data of the three levels of burrs during the removal process are collected and stored in a database. When a burr is detected, its level is determined according to the size of the burr, and then the burr audio data of the corresponding level is searched in the database for comparison.

[0092] In this embodiment, by burr classification, the amount of audio data to be processed in the database is reduced, and the amount of recognition calculation is reduced.

[0093] Preferably, the method further comprises: when the wear impact is less than a preset threshold, prompting to replace the grinding head.

[0094] In this embodiment, a preset threshold is set, which represents the critical point of the degree of wear of the grinding head. The wear impact of the grinding head is monitored. If it is lower than the preset threshold, the reminder mechanism is triggered. When the wear impact is lower than the preset threshold, a prompt signal is issued to remind the operator to replace the grinding head.

[0095] In one possible embodiment, the wear impact threshold is set to 0.6, which means that when the wear impact of the grinding head is lower than 0.6, it indicates that the grinding head is severely worn and needs to be replaced. During the deburring process, the wear impact of the grinding head is continuously monitored and the result of each deburring operation is recorded. When the wear impact is lower than the preset threshold for multiple consecutive times, the device issues an alarm to remind the operator to replace the grinding head.

[0096] In this embodiment, by setting the wear impact threshold and reminding to replace the grinding head, the automatic management and intelligentization of the die casting deburring process are achieved, thereby improving the production efficiency and product quality stability.

[0097] In summary, the method provided in this embodiment can at least achieve the following effects:

[0098] 1) The present invention accurately analyzes the degree of wear of the grinding head and automatically corrects the grinding head travel trajectory and grinding head control data according to the analysis results, thereby ensuring that a consistent and high-quality deburring effect can be maintained even when the grinding head is worn. Furthermore, by real-time monitoring of the audio data during the deburring process and comparing it with the preset deburring audio data, the effectiveness of the deburring process can be ensured. Once it is found that the audio similarity does not meet the preset conditions, it indicates that the deburring effect is not good. At this time, the device will automatically stop the current deburring process and correct the grinding head travel trajectory and control data again. This closed-loop control strategy not only improves the accuracy and efficiency of deburring, but also reduces dependence on manual monitoring, effectively extends the service life of the equipment, and ensures the consistency of product quality, thereby significantly improving the intelligence level of the entire deburring process.

[0099] 2) The present invention inputs the wear working radius and the wear missing angle into a preset wear influence algorithm to calculate the wear influence, which is used to measure the ratio of the actual working efficiency of the grinding head to the working efficiency in the unworn state. Afterwards, the initial grinding head speed is divided by the wear influence to obtain the corrected grinding head speed. This step helps to maintain a relatively stable working efficiency of the grinding head under wear conditions. Furthermore, based on the corrected grinding head speed and the preset maximum speed, it is determined whether the travel speed of the grinding head needs to be adjusted to ensure that the grinding head always maintains the best working state during the entire deburring process. By real-time monitoring and adjusting the grinding head control parameters, it is ensured that each deburring operation meets the preset standards, thereby ensuring the consistency of product quality.

[0100] See also Figure 3 In one embodiment, a die casting deburring process intelligent control device is also provided, the device comprising:

[0101] A travel trajectory generating module 100 is used to obtain a trimming profile of a die casting and generate a grinding head travel trajectory according to the trimming profile;

[0102] The burr audio acquisition module 200 is used to acquire a die-casting image, extract burr features on the grinding head travel track according to the die-casting image, obtain a burr feature sequence, and match multiple burr audio data from a preset deburring audio database based on the burr feature sequence;

[0103] The grinding head control data generating module 300 is used to detect the wear degree of the grinding head, correct the grinding head moving track according to the wear degree, and generate the grinding head control data according to the wear degree; the wear degree of the grinding head includes the wear working radius and the wear missing angle;

[0104] The deburring processing module 400 is used to perform deburring processing on the die casting according to the grinding head control data, and collect audio feature data corresponding to different burr features in real time during the deburring processing;

[0105] The burr audio comparison module 500 is used to analyze the audio similarity between the current audio feature data and the corresponding burr audio data. When the audio similarity does not meet the preset conditions, the current deburring process is stopped and the grinding head travel trajectory and grinding head control data are corrected again.

[0106] See also Figure 4 In one embodiment, the grinding head control data generating module 300 includes:

[0107] The grinding head wear degree acquisition unit 310 is used to acquire the distance from the highest point on the grinding head to the central axis, obtain the wear working radius, and acquire the wear loss angle of the worn part of the grinding head;

[0108] A travel trajectory correction unit 320, used to correct the travel trajectory of the grinding head according to the wear working radius;

[0109] Continue to see Figure 4 In another embodiment, the grinding head control data generating module 300 further includes:

[0110] The wear influence calculation unit 330 is used to input the wear working radius and the wear loss angle into a preset wear influence algorithm to obtain the wear influence. The wear influence algorithm is expressed as:

[0111]

[0112] Where, T eff is the wear influence, Rmax is the wear working radius, R0 is the initial grinding head working radius, and θ is the wear loss angle;

[0113] The grinding head control data calculation unit 340 is used to divide the initial grinding head speed by the wear influence degree to obtain the corrected grinding head speed. If the corrected grinding head speed is greater than the preset maximum speed, the maximum speed is used as the new grinding head speed, and the grinding head travel speed is updated according to the preset travel speed correction algorithm. The travel speed correction algorithm is expressed as:

[0114]

[0115] Where V r is the initial grinding head speed, V f is the initial grinding head travel speed, V f , is the corrected travel speed, is the maximum speed, T eff The impact of wear.

[0116] Continue to see Figure 4 In one embodiment, the grinding head control data generation module 300 further includes a grinding head replacement reminder unit 350 for reminding to replace the grinding head when the wear impact is less than a preset threshold.

[0117] See also Figure 5 In one embodiment, the device further includes a burr level classification module 600, which is used to classify the burrs according to the size features in the burr features, and match different burr audio data from the database based on different burr levels.

[0118] It can be understood that the functions or modules included in the device provided in this embodiment can be used to execute the method described in the above method embodiment. Its specific implementation can refer to the description of the above method embodiment. For the sake of brevity, it will not be repeated here.

[0119] The present invention also provides an electronic device, including a processor and a memory, wherein the memory is used to store computer program code, and the computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes a method as described in any possible implementation manner.

[0120] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, apparatuses and units can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. Those skilled in the art can also clearly understand that the descriptions of the various embodiments of the present invention have different focuses. For the convenience and brevity of description, the same or similar parts may not be repeated in different embodiments. Therefore, for parts not described or not described in detail in a certain embodiment, refer to the records of other embodiments.

Claims

1. An intelligent control method for deburring a die casting, characterized in that: The method comprises: Obtain the trimming profile of the die casting and generate the grinding head travel trajectory according to the trimming profile; Acquire a die-casting image, extract burr features on the grinding head travel trajectory according to the die-casting image, obtain a burr feature sequence, and match multiple burr audio data from a preset deburring audio database based on the burr feature sequence; Detecting the wear degree of the grinding head, correcting the grinding head travel trajectory according to the wear degree, and generating grinding head control data according to the wear degree; the wear degree of the grinding head includes the wear working radius and the wear missing angle; Deburring the die casting according to the grinding head control data, and collecting audio feature data corresponding to different burr features in real time during the deburring process; The audio similarity between the current audio feature data and the corresponding burr audio data is analyzed. When the audio similarity does not meet the preset conditions, the current deburring process is stopped and the grinding head travel trajectory and grinding head control data are corrected again.

2. The intelligent control method for deburring die castings according to claim 1, characterized in that: The method of detecting the wear degree of the grinding head and correcting the moving track of the grinding head according to the wear degree includes: Obtain the distance from the highest point on the grinding head to the central axis, obtain the wear working radius, and obtain the wear loss angle of the worn part of the grinding head; The grinding head travel trajectory is corrected according to the wear working radius.

3. The intelligent control method for die casting deburring process according to claim 1, characterized in that: The grinding head control data includes the grinding head rotation speed and the grinding head travel speed; The step of generating grinding head control data according to the degree of wear includes: The wear working radius and the wear loss angle are input into the preset wear influence algorithm to obtain the wear influence. The wear influence algorithm is expressed as: Where, T eff is the wear influence, R max is the wear working radius, R0 is the initial grinding head working radius, and θ is the wear loss angle; The initial grinding head speed is divided by the wear influence to obtain the corrected grinding head speed. If the corrected grinding head speed is greater than the preset maximum speed, the maximum speed is used as the new grinding head speed, and the grinding head travel speed is updated according to the preset travel speed correction algorithm. The travel speed correction algorithm is expressed as: Where V r is the initial grinding head speed, V f is the initial grinding head travel speed, V f , is the corrected travel speed, is the maximum speed, T eff The impact of wear.

4. The intelligent control method for die casting deburring process according to claim 3 is characterized in that: The method further includes: when the wear impact is less than a preset threshold, prompting to replace the grinding head.

5. The intelligent control method for deburring die castings according to claim 1, characterized in that: The method further comprises: According to the size feature in the burr feature, the burrs are divided into burr levels, and different burr audio data are matched from the database based on different burr levels.

6. An intelligent control device for deburring die castings, characterized in that: The device comprises: A travel trajectory generation module is used to obtain the trimming profile of the die casting and generate a grinding head travel trajectory according to the trimming profile; A burr audio acquisition module is used to acquire a die-casting image, extract burr features on the grinding head travel track according to the die-casting image, obtain a burr feature sequence, and match multiple burr audio data from a preset deburring audio database based on the burr feature sequence; A grinding head control data generation module is used to detect the wear degree of the grinding head, correct the grinding head travel trajectory according to the wear degree, and generate grinding head control data according to the wear degree; the wear degree of the grinding head includes the wear working radius and the wear missing angle; A deburring processing module is used to perform deburring on the die casting according to the grinding head control data, and collect audio feature data corresponding to different burr features in real time during the deburring process; The burr audio comparison module is used to analyze the audio similarity between the current audio feature data and the corresponding burr audio data. When the audio similarity does not meet the preset conditions, the current deburring process is stopped and the grinding head travel trajectory and grinding head control data are corrected again.

7. The intelligent control device for deburring die castings according to claim 6, characterized in that: The grinding head control data generation module includes: The grinding head wear degree acquisition unit is used to obtain the distance from the highest point on the grinding head to the central axis, obtain the wear working radius, and obtain the wear loss angle of the worn part of the grinding head; The travel trajectory correction unit is used to correct the travel trajectory of the grinding head according to the wear working radius.

8. The intelligent control device for deburring die castings according to claim 6, characterized in that: The grinding head control data generating module also includes: The wear influence calculation unit is used to input the wear working radius and the wear loss angle into a preset wear influence algorithm to obtain the wear influence. The wear influence algorithm is expressed as: Where, T eff is the wear influence, R max is the wear working radius, R0 is the initial grinding head working radius, and θ is the wear loss angle; The grinding head control data calculation unit is used to divide the initial grinding head speed by the wear influence to obtain the corrected grinding head speed. If the corrected grinding head speed is greater than the preset maximum speed, the maximum speed is used as the new grinding head speed, and the grinding head travel speed is updated according to the preset travel speed correction algorithm. The travel speed correction algorithm is expressed as: Where V r is the initial grinding head speed, V f is the initial grinding head travel speed, V f , is the corrected travel speed, is the maximum speed, T eff The impact of wear.

9. The intelligent control device for deburring die castings according to claim 8, characterized in that: The grinding head control data generating module also includes: The grinding head replacement reminder unit is used to remind the user to replace the grinding head when the wear impact is less than a preset threshold.

10. The intelligent control device for die casting deburring process according to claim 6, characterized in that: The device also includes: The burr level classification module is used to classify the burrs according to the size characteristics in the burr characteristics, and match different burr audio data from the database based on different burr levels.

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