A data intelligent processing method and device for laser cutting

Abstract

The embodiment of the specification discloses a data intelligent processing method and equipment for laser cutting, which is applied to the technical field of laser metal cutting and is used for solving the problem that the existing data processing easily leads to system lag. The method comprises the following steps: obtaining to-be-analyzed data based on a signal input unit and / or a network port processing unit; wherein the to-be-analyzed data corresponding to the signal input unit is obtained based on a system interaction unit and a preset sensor, and the to-be-analyzed data corresponding to the network port processing unit is obtained based on a network port integration module; processing the to-be-analyzed data and setting data corresponding to the to-be-analyzed data through a data processing module to obtain processing result data; and transmitting the processing result data to a preset system board card through a data output module, so that the system board card analyzes the processing result data, and the system board card displays the processing result data on an interface.

Description

TECHNICAL FIELD

[0001] The present specification relates to the technical field of laser metal cutting, and in particular to a data intelligent processing method and device for laser cutting. BACKGROUND

[0002] With the rapid development of modern manufacturing industry, laser cutting technology has been widely used in metal processing, automobile manufacturing, aerospace and other fields due to its high precision and high efficiency, and laser processing method has been more and more widely used in metal processing market. With the continuous development of technology, the current laser processing power gradually rises, and the requirement for the number of laser functions is also increasing. The increase of functions can meet the use demand of customers for laser cutting machine, so the demand for the function of laser cutting machine is gradually increasing. At this time, how to monitor the data of each function has become an important link to ensure the normal operation of the laser cutting machine.

[0003] However, some functions of the current traditional laser cutting operation do not need to be processed by the system, such as exceeding a certain threshold to alarm, performing some simple operations to display the interface, etc. Usually, these functions are converted by inputting RS485, RS232 or TTL data signals or analog voltage or analog current data signals into the system, and then a thread is opened in the system to convert the protocol data signal and process the data. However, since one function often corresponds to one thread, this method will lead to a higher CPU rate and memory occupancy rate of the software when facing more functions and more threads, which will easily cause system use to be lagged, and the cost of the whole machine is also increased accordingly. SUMMARY

[0004] In order to solve the above technical problems, one or more embodiments of the present specification provide a data intelligent processing method and device for laser cutting.

[0005] One or more embodiments of the present specification adopt the following technical solutions:

[0006] One or more embodiments of the present specification provide a data intelligent processing method for laser cutting, applied to an intelligent processing control device, the intelligent processing control device includes a system interaction unit, a signal input module, a data processing module, a data output module, and a network port processing unit connected with the data output module, and a network port integration module connected with the network port processing unit. The method comprises:

[0007] Obtaining the to-be-analyzed data based on the signal input unit and / or the network port processing unit; wherein the to-be-analyzed data corresponding to the signal input unit is obtained based on the system interaction unit and a preset sensor, and the to-be-analyzed data corresponding to the network port processing unit is obtained based on the network port integration module;

[0008] Processing the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data by the data processing module to obtain processing result data;

[0009] Transmitting the processing result data to a preset system board card through the data output module, so as to parse the processing result data by the system board card, and to display the processing result data on the interface of the system board card.

[0010] Optionally, in one or more embodiments of the present specification, the to-be-analyzed data is obtained based on the signal input unit and / or the network port processing unit, specifically including:

[0011] Obtaining the initial setting parameters of the system board card through the system interaction unit, and inputting the initial setting parameters into the signal input unit;

[0012] Integrating the initial setting parameters based on the signal input unit, determining the parameter range of each function of the current laser cutting machine, and taking the parameter range as the first to-be-analyzed data;

[0013] Obtaining the collection data of the current laser cutting machine based on a preset sensor, and integrating the collection data based on the signal input unit to obtain the second to-be-analyzed data; wherein the second to-be-analyzed data includes water quality data of a water cooler, pressure data of a differential pressure filter, temperature data on a laser head, temperature data in an electric control cabinet, and current data of each branch in the electric control cabinet.

[0014] And / or,

[0015] Uniformly integrating the network segments of the camera and the laser of the current laser cutting machine based on the network port integration module, so as to read the real-time data of the camera and the laser located in the same network segment;

[0016] Inputting the real-time data corresponding to each IP address into the network port processing unit, and saving the real-time data based on a preset time interval by the network port processing unit to obtain the to-be-analyzed data.

[0017] Optionally, in one or more embodiments of the present specification, the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data are processed by the data processing module to obtain processing result data, specifically including:

[0018] If the to-be-analyzed data is obtained based on the signal input unit, the data processing module receives the second to-be-analyzed data based on a Boolean signal;

[0019] determining a current laser cutting machine function corresponding to the second to-be-analyzed data, to determine the first to-be-analyzed data corresponding to the second to-be-analyzed data as setting data corresponding to the to-be-analyzed data;

[0020] According to the alarm strategy corresponding to each current laser cutting machine function, the setting data corresponding to the second to-be-analyzed data is compared with the setting data corresponding to the to-be-analyzed data in turn to obtain processing result data.

[0021] Optionally, in one or more embodiments of the present specification, the data processing module processes the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data to obtain processing result data, specifically including:

[0022] If the to-be-analyzed data is obtained based on the network port processing unit, the data processing module performs binaryzation processing on the to-be-analyzed data to obtain processed to-be-analyzed data;

[0023] The data processing module performs filtering processing on the processed to-be-analyzed data to obtain filtered to-be-analyzed data, and performs low-confidence processing on the filtered to-be-analyzed data according to the setting data preset by the system board card to obtain the processing result data;

[0024] Preferably, before the data processing module performs binaryzation processing on the to-be-analyzed data to obtain processed to-be-analyzed data, the method further includes:

[0025] Obtain real-time data collected by the network port integration unit to perform grayscale processing on the real-time data based on the network port processing unit to obtain grayscale image data corresponding to the real-time data;

[0026] Filter the grayscale image data based on a preset Gaussian filter, and divide the filtered grayscale image data into regions based on a preset size;

[0027] Detect the filtered grayscale image data of each region according to a preset human feature image file to determine the to-be-analyzed data containing human features.

[0028] Optionally, after the data processing module processes the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data to obtain processing result data, the method further includes:

[0029] The alarm status values ​​corresponding to each function of the current laser cutting machine are determined based on the system board.

[0030] If the data processing module determines that the processing result data does not correspond to the preset alarm status value of the data to be analyzed, then the data to be analyzed is iteratively detected.

[0031] If the data processing module determines that the processing result data corresponds to the preset alarm status value of the data to be analyzed, then the processing result data is transmitted to the preset system board through the data output module.

[0032] Optionally, in one or more embodiments of this specification, the preset sensor and the signal processing unit are connected for communication based on a preset communication protocol; wherein, the preset communication protocol includes: RS485 transmission protocol, RS232 transmission protocol, and TTL transmission protocol.

[0033] Optionally, in one or more embodiments of this specification, the processing result data is transmitted to a pre-installed system board via the data output module, specifically including:

[0034] The data output module preprocesses the processed result data to obtain the result data to be transmitted; wherein, the preprocessing includes: data cleaning, data formatting, and data calibration.

[0035] The communication protocol between the data output module and the preset system board is determined by the data output module, so as to logically summarize the data to be transmitted according to the communication protocol and obtain the corresponding data packet to be transmitted; wherein, the communication protocol is the RS485 communication protocol;

[0036] The data output module encapsulates the data packet to be transmitted into a format recognizable by the preset system board, and transmits the encapsulated data packet to the preset system board based on the preset communication protocol.

[0037] Optionally, in one or more embodiments of this specification, the data intelligent processing control device further includes an industrial control computer and a display; wherein the industrial control computer is connected to the display and the system interaction unit respectively;

[0038] Preferably, before acquiring the data to be analyzed based on the signal input unit and / or the network port processing unit, the method further includes: transmitting the data to be analyzed acquired by the system interaction unit to the signal input module based on the industrial control computer.

[0039] Optionally, in one or more embodiments of the present specification, the processing result data is transmitted to a preset system board card through the data output module, specifically comprising:

[0040] If the data processing unit determines that the processing result data does not correspond to the preset alarm state value of the to-be-analyzed data, the processing result data is transmitted to the industrial computer through the data output module, so that the industrial computer controls the display to display the processing result data based on the industrial computer;

[0041] If the data processing unit determines that the processing result data corresponds to the preset alarm state value of the to-be-analyzed data, the display is controlled to display first prompt information based on the industrial computer, and the data output module is controlled to transmit the processing result data to a preset system board card; wherein the first prompt information is used to prompt the functional abnormality of the current laser cutting machine corresponding to the to-be-analyzed data.

[0042] One or more embodiments of the present specification provide a data intelligent processing device for laser cutting, applied to an intelligent processing control device, the intelligent processing control device comprising a system interaction unit, a signal input module, a data processing module, a data output module, a network port processing unit connected with the data output module, and a network port integration module connected with the network port processing unit, the device comprising:

[0043] at least one processor; and,

[0044] a memory in communication connection with the at least one processor; wherein,

[0045] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute any of the above-mentioned data intelligent processing methods for laser cutting.

[0046] The above-mentioned at least one technical solution adopted by the embodiments of the present specification can achieve the following beneficial effects:

[0047] Through the acquisition of the to-be-analyzed data by the signal input unit and the network port processing unit, the data intelligent processing process of the laser cutting can be used for the function data processing of the conventional cutting operation of the laser cutting machine, and is also applicable to complex application scenarios that need real-time monitoring and early warning. In addition, through the intelligent processing control device, the to-be-analyzed data corresponding to different functions from the signal input unit and the network port processing unit are integrated, so that the subsequent data can be uniformly transmitted to the system board card, and the system board card only needs to perform simple data analysis to obtain the processing result data processed by the data processing module. Through the unified data processing process, the number of threads is reduced, and the problem of high CPU rate and memory occupancy rate and system lag caused by the more threads opened with the more functions is avoided. In addition, through the integration of the port and the unified data processing process, the system architecture is simplified, and unnecessary hardware and software components are reduced. This not only reduces the complexity and maintenance cost of the system, but also improves the overall performance of the system. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present specification or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present specification, and those skilled in the art can also obtain other drawings according to these drawings without creative labor. In the drawings:

[0049] Figure 1 A data intelligent processing method flow diagram for laser cutting provided by an embodiment of the present specification;

[0050] Figure 2 A structure diagram of an intelligent processing control device provided by an embodiment of the present specification;

[0051] Figure 3 A data intelligent processing method logic diagram for laser cutting in an application scenario provided by an embodiment of the present specification;

[0052] Figure 4 A data intelligent processing method logic diagram for laser cutting in another application scenario provided by an embodiment of the present specification

[0053] Figure 5 A network port processing unit logic diagram in an application scenario provided by an embodiment of the present specification;

[0054] Figure 6 A structure diagram of a data intelligent processing device for laser cutting provided by an embodiment of the present specification. DETAILED DESCRIPTION

[0055] The embodiment of the present specification provides a data intelligent processing method and device for laser cutting.

[0056] In order for those skilled in the art to better understand the technical solutions in the present specification, the technical solutions in the present specification will be described clearly and completely in the present specification, and obviously, the described embodiments are only part of the embodiments of the present specification, not all. Based on the embodiments of the present specification, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present specification.

[0057] As shown in the present specification, the embodiment provides a data intelligent processing method flow diagram for laser cutting. As shown in the present specification, Figure 1 As shown in the present specification, the embodiment provides a data intelligent processing method flow diagram for laser cutting. As shown in the present specification, Figure 1 As shown in the present specification, the embodiment provides a data intelligent processing method flow diagram for laser cutting. As shown in the present specification, Figure 2 As shown in the present specification, the embodiment provides a data intelligent processing method flow diagram for laser cutting. As shown in the present specification,

[0058] S101: obtaining the data to be analyzed based on the signal input unit and / or the network port processing unit; wherein the data to be analyzed corresponding to the signal input unit is obtained based on the system interaction unit and the preset sensor, and the data to be analyzed corresponding to the network port processing unit is obtained based on the network port integration module.

[0059] In order to solve the problem that in the prior art, one thread corresponds to one function, the more functions, the more threads are opened, and then the CPU rate and memory occupancy rate of the software are too high, in the embodiment of the present specification, the functions are unified for data processing and transmission to the system, and in order to achieve this purpose, the data to be analyzed is obtained based on the signal input unit and / or the network port processing unit in the embodiment of the present specification. Based on Figure 2 As shown in the present specification, the embodiment provides a data intelligent processing method flow diagram for laser cutting. As shown in the present specification,

[0060] Specifically, in one or more embodiments of the present specification, the signal input unit and / or the network port processing unit are used to obtain the data to be analyzed, which specifically includes the following processes:

[0061] First, the initial setting parameters of the system board card are obtained through the system interaction unit, and the initial setting parameters are input to the signal input unit. At the same time, the initial setting parameters are integrated based on the signal input unit to determine the parameter range of each function of the laser cutting machine, and the parameter range is taken as the first data to be analyzed. It can be understood that the initial setting parameters are the parameter data of each function set by the user on the interface obtained by the system interaction unit. Integrating the initial setting parameters can be understood as integrating the processed data into the parameter range of each function according to the working principle and cutting requirements of the laser cutting machine. At the same time, the acquisition data of the current laser cutting machine is obtained based on the preset sensor, so that the acquisition data is integrated based on the signal input unit to obtain the second data to be analyzed. The second data to be analyzed includes water quality data of the water cooler, pressure data of the differential pressure filter, temperature data on the laser head, temperature data in the electric control cabinet, current data of each branch in the electric control cabinet, etc. It should be noted that the preset sensor and the signal processing unit are connected in communication based on the preset communication protocol, so the second data to be analyzed can be transmitted to the signal processing unit based on the preset sensor. It can be understood that the preset communication protocol includes RS485 transmission protocol, RS232 transmission protocol, and TTL transmission protocol.

[0062] As shown in the Figure 2 In addition to being obtained based on the signal processing unit, the data to be analyzed can also be obtained by reading the real-time data of the camera and the laser in the same network segment through the network integration module after the network segment of the camera and the laser of the current laser cutting machine is unified based on the network integration module. Then input the real-time data corresponding to each IP address to the network processing unit to save the real-time data based on the preset time interval according to the network processing unit, and obtain the data to be analyzed. For example, in a certain application scenario, the network integration module processes the camera in the same network segment, and the network processing unit reads the video stream of the camera. After one second, a picture is saved.

[0063] In the embodiments of the present specification, the initial setting parameters and real-time data are obtained and integrated by the signal input unit and the network port processing unit respectively, realizing centralized management and efficient processing of data. This avoids scattered storage and processing of data, improving the efficiency and accuracy of data processing. The initial setting parameters can be obtained through the system interaction unit and allow users to set on the interface. This setting method is intuitive and convenient, allowing users to flexibly adjust parameters according to actual cutting needs, improving the flexibility and adaptability of cutting. The current laser cutting machine acquisition data is obtained through the pre-set sensor and integrated into the second to-be-analyzed data, which helps to realize the comparison of the function threshold value based on the first to-be-analyzed data and the second to-be-analyzed data, so that the alarm result can be directly transmitted to the system board card, thereby improving the production efficiency. In addition, the network segment of the camera and the laser of the current laser cutting machine is unified through the network integration module, simplifying the network configuration and making data reading more convenient. At the same time, the network port processing unit saves the real-time data based on the pre-set time interval, which not only guarantees the integrity of the data, but also reduces the occupation of the storage space. The acquisition of two kinds of to-be-analyzed data makes the intelligent processing of laser cutting data not only applicable to the function data processing of the regular cutting operation of the laser cutting machine, but also suitable for complex application scenarios that require real-time monitoring and early warning. For example, in terms of camera monitoring, by regularly saving pictures, visual recording of the cutting process can be realized to prevent personnel from entering the laser cutting work scene from being harmed.

[0064] S102: processing the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data through the data processing module to obtain processing result data.

[0065] After obtaining the to-be-analyzed data based on the above steps, in order to make the system only need to do a simple data analysis and display to the interface, in the embodiments of the present specification, the functions of exceeding a certain threshold value to alarm, doing some simple operations for interface display, etc. are realized by processing the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data through the data processing module, thereby obtaining processing result data.

[0066] Specifically, in one or more embodiments of the present specification, the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data are processed through the data processing module to obtain processing result data, specifically including the following processes:

[0067] Based on the above step S101, the data intelligent processing method can be used for processing the function data of the conventional cutting operation of the laser cutting machine, and is also suitable for complex application scenarios that need real-time monitoring and early warning. Therefore, for the case where the to-be-analyzed data is obtained based on the signal input unit, the data processing module in the embodiment of the present specification receives the second to-be-analyzed data based on the Boolean signal, that is, receives the preset sensor. Then, by determining the current laser cutting machine function corresponding to the second to-be-analyzed data, the first to-be-analyzed data corresponding to the second to-be-analyzed data is determined as the setting data corresponding to the to-be-analyzed data. That is, the system interaction unit is used to obtain the parameters of each function set by the user on the interface, and based on the above, the first to-be-analyzed data is the setting data, by determining the first to-be-analyzed data corresponding to the second to-be-analyzed data as the setting data corresponding to the to-be-analyzed data, it is helpful to determine whether the to-be-analyzed data collected by the preset sensor needs to be alarmed. Therefore, after determining the first to-be-analyzed data corresponding to the second to-be-analyzed data as the setting data corresponding to the to-be-analyzed data, the processing result data can be obtained by comparing the setting data corresponding to the to-be-analyzed data according to the alarm strategy corresponding to each current laser cutting machine function, as shown in Figure 3 、 Figure 4 .

[0068] In addition, it should be noted that since the to-be-analyzed data transmitted by the sensor to the data intelligent processing control device through RS485, RS232, and TTL is an analog quantity, the data processing unit actually calculates the actual value corresponding to each sensor by the corresponding proportion of the sensor analog quantity and the digital quantity. However, since the sensor value may be inaccurate due to interference problems, in a feasible embodiment, the first five values, the last five values, and the intermediate values of the to-be-analyzed data are judged, and then a deviation threshold is given. If the difference of the intermediate values exceeds the threshold, the current value will be filtered out.

[0069] In this process, the to-be-analyzed data and the corresponding setting data are processed by the data processing module, and the processing result data can be quickly obtained. The to-be-analyzed data and the setting data can be compared according to the alarm strategy corresponding to each current laser cutting machine function, so as to determine whether an alarm is needed. This intelligent alarm strategy helps to reduce false alarms and missed alarms, and improves the accuracy of the alarm. By using the data processing module to unify the functions for data processing and transmission to the system, the system board card only needs to perform a simple data analysis and display to the interface, which greatly simplifies the system structure, solves the problem of high CPU rate and memory occupancy rate of the system, and speeds up the system response speed.

[0070] It should be noted that: for the alarm strategy corresponding to each current laser cutting machine function, the second to be analyzed data corresponding to the to be analyzed data is compared in turn with the to be analyzed data corresponding to the set data, and the line of sight process of obtaining the processing result data is obtained. In one example, after the current value exceeds the function threshold value set by the user on the interface, the data processing unit does not send an alarm signal to the system board card through the data output module, but averages the first K data of the to be analyzed data based on the alarm strategy corresponding to the current laser cutting machine function, and then compares it with the function threshold value, that is, the first to be analyzed data. If the value does not exceed the function threshold value corresponding to the first to be analyzed data at this time, the first data is discarded and one data behind is added, and the data comparison is continued in this way; if the value exceeds the function threshold value at this time, the data processing unit sends it to the system board card through the data output module, and the system board card analyzes whether the current function needs to be alarmed through a specific technical protocol. Wherein, K is the interval number of the system board card data set by the user. In another example, assuming that the function 1 alarm logic is: the detection range is 0-3000; the number of values is changed every half minute, then if it exceeds the function threshold value, the alarm strategy is to detect K times, if K times are above the function threshold value, alarm, if there is a time in between that is not above the threshold, then the alarm times are recorded again. The alarm strategy of function 2 is: directly detect the value and the function threshold value, and alarm if it exceeds the alarm value.

[0071] Specifically, in another embodiment of the present specification, the to be analyzed data and the set data corresponding to the to be analyzed data are processed by the data processing module to obtain the processing result data, which specifically includes the following processes:

[0072] If the to be analyzed data is obtained based on the network port processing unit, the data processing module will perform binaryzation processing on the to be analyzed data to obtain the processed to be analyzed data. Then, the data processing module performs filtering processing on the processed to be analyzed data to obtain filtered to be analyzed data, and performs low-confidence processing on the filtered to be analyzed data according to the preset set data of the system board card to obtain the processing result data.

[0073] Preferably, if the to be analyzed data is obtained based on the network port processing unit, the data processing module performs binaryzation processing on the to be analyzed data to obtain the processed to be analyzed data, and the method further includes the following processes: first, the real-time data collected by the network port integration unit is obtained to perform grayscale processing on the real-time data based on the network port processing unit to obtain grayscale image data corresponding to the real-time data. Then, the grayscale image data is filtered based on the preset Gaussian filter, and the filtered grayscale image data is regionally divided based on the preset size. The filtered grayscale image data of each region is detected based on the preset human feature image file to determine the to be analyzed data containing human features.

[0074] That is, in order to analyze whether there is a person in the data obtained by the network port processing unit, so as to output alarm to the system board card through the output module, so that the system board card can control the laser cutting machine to stop, prevent personnel from being harmed. In one embodiment, the camera on the laser cutting machine is divided into front camera and rear camera, and the two cameras are in a unified network segment but have different IP addresses. Taking the camera inside the laser cutting machine as an example, the IP address and port number of the camera required by the network port integration module to read the camera are 192.168.1.108 and 37777 respectively, and if the settings are incorrect, it will affect the use of the function. After setting the IP address and port number of the camera, the network port processing unit reads the auxiliary code stream of the camera, the main code stream is used for the system board card to read the camera data, the resolution of the auxiliary code stream is set to 704*576(D1), the encoding mode is set to H.264H, the frame rate (FPS) is set to 25, the code stream control is set to fixed code stream, the code stream is set to 512, and the frame interval is set to 50, which can be calibrated after the setting is completed.

[0075] Before using the network port integration module, as Figure 5The shown also includes the following process: first, the visual detection device needs to be installed on the large enclosure, and the camera on the upper edge of the large enclosure needs to be fixed. Then, after installing the visual detection device on the large enclosure, the visual device installation is carried out according to the debugging data prompt issued by the data intelligent processing control device. Because the installation of the visual device is not correct, the data intelligent processing control method must be adjusted according to the debugging data. After installation and debugging, pre-treatment is carried out. When taking a picture, the software will automatically take a picture to the D drive, and the folder attribute is hidden. Specifically, the folders under the folder are automatically established. First, the Alarmarchinewushanchu folder saves the photos after the alarm. The current alarm photo and the previous ten photos before the alarm and the next ten photos after the alarm are saved. The contents in this folder are deleted one month, only the files more than one month are deleted, and the files less than one month are saved. The photos in the Savepicture folder are saved. The current alarm photo is selected, and the selected part causes the alarm. The contents in this folder are deleted one hour. The Savepicturewushan folder saves every second photo, and this folder is deleted one day. Then, open the software on the laser equipment machine tool to take a picture, and perform histogram equalization on the picture, then train the picture, and generate a specific xml file. This step will take pictures of the human body parts of the laser equipment respectively, and then generate a specific XML file. Convert the original picture to a grayscale picture. This step is to avoid errors caused by color as much as possible. Based on the Gaussian filter, the grayscale picture is filtered to remove some factors that are prone to false alarms. Then, divide the captured picture into regions, use the trained XML file to detect the human body features in the picture and analyze the human body feature positions.

[0076] In another embodiment, after setting the camera parameters, the system board card opens the software, the software communicates with the data intelligent processing control device, and then adjusts the position of the camera according to the area given by the data intelligent processing control device, and performs position calibration. Then the network port processing unit analyzes the picture by using the library processed in advance. Before analysis, first, the picture is binarized, then the picture is binarized, the information in the picture is read after the binarization is completed, and then the possible human area is filtered.

[0077] Before obtaining the data to be analyzed, the embodiment of the present specification first collects real-time data through the network port integration unit and performs grayscale processing and region division, which helps to narrow the processing range and make the subsequent human feature detection more efficient and accurate. Using a pre-set human feature image file for detection can ensure that only data containing human features is processed, thereby avoiding unnecessary calculations and resource waste. The low-confidence processing of the filtered data to be analyzed according to the preset data of the system board card makes the system board card adjustable and optimized according to different application scenarios and needs, improving the flexibility and adaptability of the system. Through a series of processing steps, including binarization, filtering, region division, and human feature detection, the accuracy and reliability of data processing can be significantly improved, and the system board card can be alarmed in the presence of personnel, so that the system board card can control the laser cutting machine to stop and prevent personnel from being harmed.

[0078] Further, in one or more embodiments of the present specification, after the data processing module processes the data to be analyzed and the setting data corresponding to the data to be analyzed to obtain the processing result data, the method further includes the following process:

[0079] First, based on the system board card, determine the alarm state value corresponding to each function of the laser cutting machine. If the data processing module determines that the processing result data does not correspond to the preset alarm state value of the data to be analyzed, iterate the detection of the data to be analyzed. If the data processing module determines that the processing result data corresponds to the preset alarm state value of the data to be analyzed, the processing result data is transmitted to the preset system board card through the data output module. That is, during the operation of the laser cutting machine, a large amount of data will be generated, such as cutting speed, power output, temperature, etc. These data are collected in real time and compared and analyzed with the preset setting data by the data processing module. Assuming that the cutting speed of the laser cutting machine exceeds the preset maximum value at this time, the data processing module will calculate this anomaly and generate processing result data. The system board card will determine the alarm state value corresponding to each function according to the current state of the laser cutting machine. Since the cutting speed is abnormal in this example, the system board card will identify an alarm state value related to the cutting speed. At this time, the data processing module compares the processing result data with the preset alarm state value. If the processing result data matches the preset alarm state value, it means that an alarm is needed.

[0080] In the process, the data processing module processes the to-be-analyzed data and the corresponding setting data to obtain processing data results, and then determines the alarm state value of each function of the current laser cutting machine based on the system board card, and compares it with the processing result data, so as to accurately judge whether the alarm needs to be triggered. This method avoids false alarms or missed alarms caused by data errors or misjudgments, and the judgment is advanced to the data processing module, which also relieves the content pressure of the system board card. Once the processing result data corresponds to the preset alarm state value of the to-be-analyzed data, the data will be immediately transmitted to the preset system board card through the data output module. This kind of instant response mechanism can quickly trigger the alarm, so that the operator can take timely measures to prevent potential equipment damage or production accidents.

[0081] S103: transmitting the processing result data to the preset system board card through the data output module, so as to parse the processing result data through the system board card, so that the system board card displays the processing result data.

[0082] Based on the processing of the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data by the data processing module in step S102, in order to achieve the purpose of timely alarm response and data display, the processing result data is transmitted to the preset system board card through the data output module in the embodiment of the present specification, so as to parse the processing result data through the system board card, and then the system board card displays the processing result data. In this process, once the processing result data is transmitted to the system board card through the data output module, the system board card only needs to parse it to obtain the abnormality or alarm state indicated by the processing result data, which helps to quickly trigger the alarm mechanism, thereby realizing the timely response to potential problems. And in this process, the system board card to which the processing result data is transmitted is based on the data processing module which unifies each function for data processing, avoiding the traditional scheme in which one function often corresponds to one thread, resulting in more functions and more threads. Therefore, the CPU rate and memory occupancy rate of the software will be too high in the later stage, which will cause the system to be lagging and the use cost of the whole machine will also increase accordingly, thereby improving the response rate of the system board card.

[0083] Specifically, in one or more embodiments of the present specification, the processing result data is transmitted to the preset system board card through the data output module, specifically including the following process:

[0084] Firstly, the data output module is used to pre-process the processing result data to obtain the to-be-transmitted result data. It is understood that the pre-processing includes data cleaning, data formatting and data calibration. Then, the communication protocol between the data output module and the preset system board card is determined by the data output module, and the to-be-transmitted result data is logically summarized according to the communication protocol to obtain the corresponding to-be-transmitted result data packet. It should be noted that the communication protocol is RS485 communication protocol, and the specific parameters are 9600 baud rate, no check, 8-bit data bit and 1-bit stop bit. Then, the to-be-transmitted result data packet is packaged into a recognizable format of the preset system board card according to the data output module, and the packaged to-be-transmitted result data packet is transmitted to the preset system board card based on the preset communication protocol. That is, the video stream of the network port is transmitted through the network cable, the data transmitted by the laser parameter and the sensor is integrated and transmitted to the system board card through RS485, and the system board card analyzes the data by reverse compiling according to the rules of the RS485 protocol, and transmits the corresponding function data to the corresponding display screen for display.

[0085] For the logical summary of the to-be-transmitted result data according to the communication protocol, for example, Table 1 below shows an example of the format of the data intelligent processing control device corresponding to two functions transmitted to the system board card by the data output module. The meanings of the positions in Table 1 below are as follows:

[0086] The first bit of the transmitted data is fixed as 0x81, indicating that this instruction is a response command;

[0087] The second bit is whether to enable the correct response inquiry command, 0x01 for normal response and other for exception;

[0088] The third bit is the state of function 1;

[0089] The fourth and fifth bits are the response value of function 1, and the calculation method is 256*Byte1+Byte2;

[0090] The sixth bit is the state of function 2;

[0091] The seventh and eighth bits are the response value of function 2, and the calculation method is 256*Byte1+Byte2;

[0092] The ninth bit is the state bit of whether function 1 is connected successfully, 0x01 for normal response and other for exception;

[0093] The tenth bit is the state bit of whether function 2 is connected successfully, 0x01 for normal response and other for exception.

[0094] Table 1 Format of data intelligent processing control device transmitted to system board card by data output module

[0095]

[0096] In addition to the data transmission mode of the data intelligent processing control device sending data to the system board card through the data output module, in another embodiment, the data intelligent processing unit can also be sent by the system board card, and Table 2 below shows an example of the format of the sending command sent by the system board card to the data intelligent processing unit.

[0097] Table 2 System board card sends data intelligent processing unit sending command format

[0098]

[0099] The meanings of the positions in Table 2 above are as follows:

[0100] The first bit of the sent data is fixed at 0x80, indicating that this instruction is a query command;

[0101] The second bit is whether to enable function 1;

[0102] Bits 3 and 4 are function 1, and the calculation method is 256*Byte1+Byte2;

[0103] The fifth bit is whether to enable function 2;

[0104] Bits 6 and 7 are function 2, and the calculation method is 256*Byte1+Byte2;

[0105] Bits 8 and 9 are function 2, and the calculation method is 256*Byte1+Byte2.

[0106] In addition, as can be seen from the above, the data intelligent processing process can be used not only for processing the function data of the conventional cutting operation of the laser cutting machine, but also for complex application scenarios that require real-time monitoring and early warning, so in an embodiment, the data processing module also analyzes the pictures saved after the network port processing unit reads the video stream of the camera, determines whether there is a person, and if there is, outputs an alarm to the system board card through the data output module, and the system board card controls the laser cutting machine to stop to prevent personnel from being harmed.

[0107] Further, in one or more embodiments of the present specification, the data intelligent processing control device further comprises an industrial computer and a display; wherein the industrial computer is connected with the display and the system interaction unit respectively. Preferably, in an embodiment, before the signal input unit and / or the network port processing unit acquire the data to be analyzed, the method further comprises: transmitting the data to be analyzed acquired by the system interaction unit to the signal input module through the industrial computer.

[0108] Further, in one or more embodiments of the present specification, the processing result data is transmitted to the preset system board card through the data output module, specifically including the following process:

[0109] If the data processing unit determines that the processing result data does not correspond to the preset alarm state value of the to-be-analyzed data, the processing result data is transmitted to the industrial computer through the data output module, so that the industrial computer controls the display to display the processing result data. If the data processing unit determines that the processing result data corresponds to the preset alarm state value of the to-be-analyzed data, the industrial computer controls the display to display the first prompt information and controls the data output module to transmit the processing result data to the preset system board card. It can be understood that the first prompt information is used to prompt the functional abnormality of the current laser cutting machine corresponding to the to-be-analyzed data.

[0110] For the intelligent processing control device including the industrial computer, the to-be-analyzed data acquired by the system interaction unit can be transmitted to the signal input module through the industrial computer, so that real-time monitoring of the data is realized. At the same time, according to whether the processing result data corresponds to the preset alarm state value, the system can give feedback immediately, such as displaying the processing result data or the first prompt information for further processing or alarm. This real-time monitoring and immediate feedback mechanism helps to discover and handle abnormal situations in time, ensures the normal operation of the laser cutting machine, and reduces manual intervention and improves the automation degree of the system.

[0111] As shown in Figure 6 , a structural diagram of a data intelligent processing device for laser cutting is provided in one or more embodiments of the present specification. It can be known from Figure 6 that in one or more embodiments of the present specification, a data intelligent processing device for laser cutting is applied to an intelligent processing control device, the intelligent processing control device includes a system interaction unit, a signal input module, a data processing module, a data output module, and a network port processing unit connected with the data output module and a network port integration module connected with the network port processing unit, and the device includes:

[0112] at least one processor; and

[0113] a memory in communication connection with the at least one processor; wherein

[0114] the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute any of the above-mentioned data intelligent processing methods for laser cutting.

[0115] The various embodiments in this specification describe the application in progressive stages. Each stage builds on the previous stages, and each stage can be described in the context of similar or identical subject matter as in other stages. Each stage is intended to highlight a distinct advancement in the application over the previous stage. For example, the device, apparatus, and non-transitory computer storage medium embodiments are described more simply than the method embodiments because they are substantially similar to the method embodiments. The relevant portions of the method embodiments are referenced.

[0116] The above description only illustrates certain embodiments of the specification. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims can be performed in a different order than the order in which they are recited and still achieve desirable results. In addition, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve the desired results. In certain implementations, multitasking and parallel processing can be advantageous or necessary.

[0117] The above description is merely one or more embodiments of the specification and is not intended to limit the specification. One or more embodiments of the specification can have various modifications and changes for those skilled in the art. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of one or more embodiments of the specification shall be included in the scope of the claims of the specification.

Claims

1. A data intelligent processing method for laser cutting, characterized by, The method is applied to an intelligent processing control device, and the intelligent processing control device comprises a system interaction unit, a signal input module, a data processing module, a data output module, a network port processing unit connected with the data output module, and a network port integration module connected with the network port processing unit. The method comprises the following steps: Obtaining to-be-analyzed data based on the signal input module and the network port processing unit; wherein the to-be-analyzed data corresponding to the signal input module is obtained based on the system interaction unit and a preset sensor, and the to-be-analyzed data corresponding to the network port processing unit is obtained based on the network port integration module; Processing the to-be-analyzed data and setting data corresponding to the to-be-analyzed data by the data processing module to obtain processing result data; 2. The method for data intelligence processing for laser cutting of claim 1, wherein, Transmitting the processing result data to a preset system board card through the data output module, so as to parse the processing result data by the system board card, and to display the processing result data on the interface of the system board card. The method comprises the following steps: Obtaining the initial setting parameters of the system board card through the system interaction unit, and inputting the initial setting parameters into the signal input module; Integrating the initial setting parameters based on the signal input module, determining the parameter range of each function of the current laser cutting machine, and taking the parameter range as the first to-be-analyzed data; Obtaining the collection data of the current laser cutting machine based on a preset sensor, and integrating the collection data based on the signal input module to obtain the second to-be-analyzed data; wherein the second to-be-analyzed data comprises water quality data of a water cooler, pressure data of a differential pressure filter, temperature data on a laser head, temperature data in an electric control cabinet, and current data of each branch in the electric control cabinet; Uniformly connecting the network segments of a camera and a laser of the current laser cutting machine based on the network port integration module, so as to read the real-time data of the camera and the laser located in the same network segment; 3. The method for data intelligence processing for laser cutting of claim 2, wherein, Inputting the real-time data corresponding to each IP address into the network port processing unit, and saving the real-time data based on a preset time interval by the network port processing unit to obtain to-be-analyzed data. Processing the to-be-analyzed data and setting data corresponding to the to-be-analyzed data by the data processing module to obtain processing result data, which comprises the following steps: If the to-be-analyzed data is obtained based on the signal input module, the data processing module receives the second to-be-analyzed data based on a Boolean signal; Determining the current laser cutting machine function corresponding to the second to-be-analyzed data, and determining the first to-be-analyzed data corresponding to the second to-be-analyzed data as the setting data corresponding to the to-be-analyzed data; Comparing the setting data corresponding to the to-be-analyzed data and the second to-be-analyzed data corresponding to the current laser cutting machine function in sequence according to the alarm strategy corresponding to each current laser cutting machine function to obtain processing result data.

4. The method for data intelligence processing for laser cutting of claim 2, wherein, The data processing module processes the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data, and obtains processing result data, specifically including: If the to-be-analyzed data is obtained based on the network port processing unit, the data processing module performs binaryzation processing on the to-be-analyzed data, and obtains processed to-be-analyzed data; The data processing module performs filtering processing on the processed to-be-analyzed data, and obtains filtered to-be-analyzed data, and performs low-confidence processing on the filtered to-be-analyzed data according to the setting data preset by the system board card, and obtains the processing result data; Before the data processing module performs binaryzation processing on the to-be-analyzed data to obtain processed to-be-analyzed data, the method further includes: Obtain real-time data collected by the network port integration module to perform grayscale processing on the real-time data based on the network port processing unit, and obtain grayscale image data corresponding to the real-time data; Filter the grayscale image data based on a preset Gaussian filter, and divide the filtered grayscale image data into regions based on a preset size; Detect the filtered grayscale image data of each region based on a preset human feature image file, and determine the to-be-analyzed data containing human features.

5. The method for data intelligence processing for laser cutting of claim 1, wherein, After the data processing module processes the to-be-analyzed data and the setting data corresponding to the to-be-analyzed data to obtain processing result data, the method further includes: Determine the alarm state value corresponding to each function of the current laser cutting machine based on the system board card; If it is determined based on the data processing module that the processing result data does not correspond to the preset alarm state value of the to-be-analyzed data, iteratively detect the to-be-analyzed data; If it is determined based on the data processing module that the processing result data corresponds to the preset alarm state value of the to-be-analyzed data, transmit the processing result data to the preset system board card through the data output module.

6. The method for data intelligence processing for laser cutting of claim 1, wherein, The preset sensor and the signal input module are communicatively connected based on a preset communication protocol; wherein the preset communication protocol includes: RS485 transmission protocol, RS232 transmission protocol, TTL transmission protocol.

7. The method for data intelligence processing for laser cutting of claim 1, wherein, Transmit the processing result data to the preset system board card through the data output module, specifically including: Preprocess the processing result data based on the data output module to obtain to-be-transmitted result data; wherein the preprocessing includes: data cleaning, data formatting, data calibration; Determine the communication protocol between the data output module and the preset system board card through the data output module, so as to logically aggregate the to-be-transmitted result data according to the communication protocol to obtain corresponding to-be-transmitted result data packet; wherein the communication protocol is RS485 communication protocol; Encapsulate the to-be-transmitted result data packet into a recognizable format of the preset system board card based on the data output module, and transmit the encapsulated to-be-transmitted result data packet to the preset system board card based on the communication protocol.

8. The method for data intelligence processing for laser cutting of claim 1, wherein, The intelligent processing control device further comprises an industrial computer and a display; wherein the industrial computer is connected with the display and the system interaction unit respectively; Before the signal input module and the network port processing unit obtain the data to be analyzed, the method further comprises: based on the industrial computer, the system interaction unit obtains the data to be analyzed, and transmits the data to the signal input module.

9. The method for data intelligence processing for laser cutting of claim 8, wherein, The processing result data is transmitted to the preset system board card through the data output module, specifically including: If the data processing module determines that the processing result data does not correspond to the preset alarm state value of the data to be analyzed, the processing result data is transmitted to the industrial computer through the data output module, so as to control the display to display the processing result data based on the industrial computer; If the data processing module determines that the processing result data corresponds to the preset alarm state value of the data to be analyzed, the display is controlled to display the first prompt information based on the industrial computer, and the data output module is controlled to transmit the processing result data to the preset system board card; wherein the first prompt information is used to prompt the function abnormality of the current laser cutting device corresponding to the data to be analyzed.

10. A data intelligent processing device for laser cutting, characterized by, The application is applied to an intelligent processing control device, and the intelligent processing control device comprises a system interaction unit, a signal input module, a data processing module, a data output module, a network port processing unit connected with the data output module, and a network port integration module connected with the network port processing unit. The device comprises: At least one processor; and The memory is in communication connection with the at least one processor; wherein The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the data intelligent processing method for laser cutting in any one of claims 1-9.

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