A method for detecting the flatness of a shielding cover based on laser measurement technology

Abstract

The present invention discloses a method for detecting the flatness of a shielding cover based on laser measurement technology, which relates to the field of laser measurement technology and effectively reduces the influence of processing quality on the flatness of the shielding cover packaging. According to the historical laser signal spectrum, a sequence of standard product dynamic models under each production step is established. At the same time, according to the fluctuations of the historical laser signal spectrum at each time point, several groups of horizontal fluctuation vectors are set on the outer surface of the standard product dynamic model. The real-time laser signal spectrum of each production step of the metal product in the real-time state is collected, a two-dimensional product model is established according to the real-time laser signal spectrum, and several real-time horizontal fluctuation vectors are set at the edge position of the two-dimensional product model. A sequence of standard product dynamic models under each production step is established. By comparing the real-time horizontal fluctuation vectors on the two-dimensional product model with the horizontal fluctuation vectors on the standard product dynamic model, it is judged whether there is an abnormality in the processing process of the metal product or the packaging process of the shielding cover according to the comparison result.

Description

Technical Field

[0001] The present invention relates to the technical field of laser measurement, and specifically, to a method for detecting the flatness of a shielding cover based on laser measurement technology. Background Art

[0002] In modern industrial production, the manufacturing process of metal products has extremely high requirements for precision and quality control. Especially in the manufacturing of electronic devices, as a key component, the processing quality and packaging process stability of the metal shielding cover directly affect the performance and service life of the device. And when the processing quality is unqualified, it will also directly or indirectly lead to the packaging quality of the shielding cover.

[0003] In the existing metal product processing and shielding cover packaging processes, traditional mechanical contact detection methods are usually adopted, and data is obtained through the physical contact between a probe and the product surface. This method has disadvantages such as wear, slow measurement speed, and susceptibility to environmental interference. In recent years, due to its high precision, non-contact, and fast response characteristics, laser measurement technology has gradually become an important means for quality monitoring in the metal product processing and shielding cover packaging processes.

[0004] When the existing laser scanning system processes shielding covers with complex shapes, especially in the case of curved surfaces or irregular surfaces, it is difficult to achieve an ideal measurement accuracy level. This is mainly due to the focusing and scattering problems of the laser beam, resulting in unstable data acquisition.

[0005] Therefore, how to reduce or eliminate the influence of processing quality on the flatness of the shielding cover packaging while improving the measurement accuracy of laser scanning is a difficult point in the existing technology. For this reason, a method for detecting the flatness of a shielding cover based on laser measurement technology is provided. Summary of the Invention

[0006] In order to solve the above technical problems, the purpose of the present invention is to provide a method for detecting the flatness of a shielding cover based on laser measurement technology.

[0007] To achieve the above purpose, the present invention provides the following technical solutions:

[0008] A method for detecting the flatness of a shielding cover based on laser measurement technology includes the following steps:

[0009] Step S1, set multiple processing sections on the production line according to the production steps of metal products, install multiple laser sensors in each processing section, and during the process that each metal product passes through the processing section in sequence along the conveyor belt, collect the historical laser signal spectra of each metal product from three emission angles through the laser sensors;

[0010] Step S2: Based on the historical laser signal spectra of metal products under normal production in several production steps, establish a sequence of standard product dynamic models for each production step. At the same time, according to the fluctuations of the historical laser signal spectra at each time point, set several groups of horizontal fluctuation vectors on the outer surface of the standard product dynamic model.

[0011] Step S3: Collect the real-time laser signal spectra of metal products at each production step in the real-time state. Establish a two-dimensional product model based on the real-time laser signal spectra, and set several real-time horizontal fluctuation vectors at the edge position of the two-dimensional product model. Establish a sequence of standard product dynamic models for each production step. By comparing the real-time horizontal fluctuation vectors on the two-dimensional product model with the horizontal fluctuation vectors on the standard product dynamic model, judge whether there are abnormalities in the processing process or the shielding cover packaging process of the metal product according to the comparison results.

[0012] Further, the production steps of the metal product include stamping, cleaning, and packaging. Install corresponding production equipment on the production line according to the production steps of the metal product, and connect each production equipment in sequence through a conveyor belt. Divide the production equipment corresponding to the same production step into a group, and then divide three processing sections on the production line.

[0013] Further, the acquisition process of the historical laser signal spectra includes:

[0014] Bind a laser sensor to each production equipment in each processing section, and set numbers for each laser sensor. During the process of processing metal products on the production line, each laser sensor on the production line emits n strings of laser signals vertically and at an oblique angle of 45 degrees on both sides to the conveyor belt, and each string of laser signals is in a horizontal straight line on the conveyor belt.

[0015] When the conveyor belt conveys the metal products through each processing section in sequence, each laser signal passes through the metal product and generates corresponding laser reflection signal spectra, and mark the numbers and emission angles of the corresponding laser sensors for each laser reflection signal spectrum, and then collect several laser reflection signal spectra of various metal products under different production steps.

[0016] Further, the establishment process of the sequence of standard product dynamic models:

[0017] Select the laser reflection signal spectra of metal products under normal production at each production step, establish a two-dimensional coordinate system, and map the laser reflection signal spectra corresponding to the same type of metal product, the same production step, and generated by the same laser sensor onto the same two-dimensional coordinate system.

[0018] Set a number of analysis time points on the two-dimensional coordinate system, perform normal distribution on the amplitude values of the same analysis time point but different laser reflection signal spectra, and generate the normal amplitude value intervals at each analysis time point according to the normal distribution results;

[0019] Connect the normal amplitude value intervals of each analysis time point in sequence to obtain the normal laser reflection signal spectra corresponding to each production device of the corresponding type of metal product under the execution of the corresponding production steps;

[0020] Establish the corresponding standard product dynamic model according to each normal laser reflection signal spectrum, then overlap and map the standard product dynamic models generated by the laser signals at different emission angles of the same laser sensor, and sequentially associate the standard product dynamic models generated by each laser sensor on the same processing section to obtain the standard product dynamic model sequence.

[0021] Further, the establishment process of the horizontal fluctuation vector includes:

[0022] Along the running direction of the conveyor belt, set m outer surface starting points distributed in a columnar straight line on the outer surface of each standard product dynamic model in the standard product dynamic model sequence, and set n outer surface detection points distributed side by side and parallel to the distribution of the laser signals on the conveyor belt. Connect the adjacent outer surface starting points and outer surface detection points in the same row in sequence to obtain n standard horizontal fluctuation vectors with equal modulus lengths, where both n and m are natural numbers greater than 0.

[0023] Further, the process of establishing a two-dimensional product model according to the real-time laser signal spectrum includes:

[0024] Whenever a metal product passes through the laser signal of a laser sensor along the conveyor belt, generate the corresponding real-time laser reflection signal spectrum;

[0025] Set the defect detection frequency according to the time length between each analysis time point. Whenever a defect detection frequency starts, establish the corresponding two-dimensional product model according to the real-time laser reflection signal spectrum, and adopt the process of establishing the standard horizontal fluctuation vector on the outer surface of the standard product dynamic model to set n real-time horizontal fluctuation vectors at the edge position of the two-dimensional product model.

[0026] Further, the process of comparing the real-time horizontal fluctuation vector with the horizontal fluctuation vector includes:

[0027] Establish a three-dimensional coordinate system, and map the real-time horizontal fluctuation vectors generated at each defect detection frequency to the three-dimensional coordinate system in sequence with the standard horizontal fluctuation vectors in the same sequence on the corresponding standard product dynamic model according to the generation time sequence of the real-time horizontal fluctuation vectors;

[0028] Match each real - time horizontal fluctuation vector with each standard horizontal fluctuation vector pairwise in sequence, and then obtain the dot product between the matched real - time horizontal fluctuation vector and the standard horizontal fluctuation vector;

[0029] Set a dot - product threshold, and then judge whether the dot product between each real - time horizontal fluctuation vector and the standard horizontal fluctuation vector is less than or equal to the dot - product threshold. If the dot product is less than or equal to the dot - product threshold, it is judged that the position of the metal product associated with the corresponding real - time horizontal fluctuation vector is normal; otherwise, it is judged as suspected abnormal.

[0030] Further, the process of judging whether there is an abnormality in the processing process or the shielding cover packaging process of the metal product includes:

[0031] If after the metal product passes through the laser signals of three laser sensors at the same position, on the generated two - dimensional product model, there are two or more times when the dot product between the real - time horizontal fluctuation vector and the corresponding standard horizontal fluctuation vector at the same position is greater than the dot - product threshold, it is judged that there are abnormal defects in the relevant position of the metal product;

[0032] When the metal product completely passes through the laser signals at three emission angles of a laser sensor, generate a real - time product stage model according to the three emission angles to generate a real - time laser reflection signal spectrum, and mark the position of abnormal defects on the real - time product stage model;

[0033] Judge in sequence whether the real - time product stage models generated in the stamping, cleaning, or packaging steps carry markings of abnormal defect positions, and judge whether there are abnormalities in the processing process or the shielding cover packaging process of the metal product according to the judgment results.

[0034] Compared with the prior art, the beneficial effects of the present invention are:

[0035] 1. The present invention sends laser signals at different emission angles from the same position through a laser sensor. Then, when the metal product moves along the conveyor belt, the laser reflection signal spectra generated at each emission angle are complementary to each other. Therefore, the standard product dynamic models corresponding to the laser reflection signal spectra at different emission angles of the same laser sensor are overlapped, making the standard product dynamic model more accurate. While improving the measurement accuracy of laser scanning, it lays a data foundation for subsequent judgment of whether there are abnormalities in the production process.

[0036] 2. The present invention judges in sequence whether the real - time product stage models generated in the stamping, cleaning, and packaging steps carry markings of abnormal defect positions, minimizing the influence of the previous production step on the defect detection result of the next production step, and effectively improving the accuracy of judging the flatness of the shielding cover packaging. Description of the Drawings

[0037] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments recorded in the present invention.

[0038] Figure 1 It is the flowchart of the method of the present invention. Detailed implementation manners

[0039] To make the objectives, technical solutions and advantages of the present invention clearer, the following will describe the technical solutions of the present invention in detail. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other implementation manners obtained by those of ordinary skill in the art without creative efforts fall within the scope protected by the present invention.

[0040] As Figure 1 shown, a method for detecting the flatness of a shielding cover based on laser measurement technology includes the following steps:

[0041] Step S1: Set multiple processing sections on the production line according to the production steps of metal products, and install multiple laser sensors in each processing section. During the process that each metal product passes through the processing sections in sequence along the conveyor belt, collect the historical laser signal spectra of each metal product from three emission angles through the laser sensors;

[0042] The specific implementation process of the said step S1 includes:

[0043] The production steps of the metal products include stamping, cleaning, and packaging. Install corresponding production equipment on the production line according to the production steps of the metal products, and connect each production equipment in sequence through the conveyor belt. Group the production equipment corresponding to the same production step into one group, and then divide three processing sections on the production line. It should be noted that since the process complexities of each production step are different, the lengths of the processing sections of each production step are different;

[0044] The stamping step includes compressing metal raw materials into metal products with corresponding shapes according to production requirements;

[0045] The cleaning step is used to clean the surface of the metal product;

[0046] The packaging step is used to install a shielding cover on the metal product;

[0047] Bind a laser sensor to each production equipment in each processing section, and set numbers for each laser sensor, where the numbers are a1, a2,..., a i , b1, b2,..., b j , c1, c2,..., ck , where i, j, and k are natural numbers greater than 0, and a i , b j , and c k respectively represent the i-th, j-th, and k-th sensors of the first, second, and third processing sections;

[0048] It should be noted that the spacing distances between the respective laser sensors are equal, and the lengths of the processing sections in different production steps are not completely equal;

[0049] During the process of the production line processing metal products, the respective laser sensors located on the production line emit n strings of laser signals vertically and at an angle of 45 degrees obliquely to both sides to the conveyor belt, and each string of laser signals is in a horizontal straight line on the conveyor belt;

[0050] When the conveyor belt conveys the metal products through the respective processing sections in sequence, each laser signal passes through the metal products and generates corresponding laser reflection signal spectra, and the numbers and emission angles of the corresponding laser sensors are marked on each laser reflection signal spectrum, thereby collecting several laser reflection signal spectra of various metal products under different production steps.

[0051] Step S2: According to the historical laser signal spectra of metal products under normal production in several production steps, establish a standard product dynamic model sequence for each production step. At the same time, according to the fluctuations of the historical laser signal spectra at each time point, several groups of horizontal fluctuation vectors are set on the outer surface of the standard product dynamic model;

[0052] The specific implementation process of the said step S2 includes:

[0053] Since the laser sensors emit a row of laser signals in three directions, the laser reflection signals generated when the laser signals directly irradiate on the conveyor belt are a series of relatively smooth spectra without obvious fluctuations;

[0054] Furthermore, when the metal products pass through each row of laser signals in sequence under the drive of the conveyor belt, due to the production requirements of the metal products, the irregularities on the surfaces of the metal products in different production steps, and since the metal products are more convex relative to the conveyor belt itself, when the metal products pass through the front and rear time nodes of the laser signals, the laser reflection signal spectra collected by the corresponding laser sensors change significantly. And due to the irregular parts on the surface of the metal products, after the first significant change in the laser reflection signal spectrum, a series of irregular local fluctuations occur until no local fluctuations occur after the second significant change;

[0055] Select the laser reflection signal spectra of metal products determined by the staff to be normal at each production step, establish a two-dimensional coordinate system, and map the laser reflection signal spectra corresponding to the same type of metal product, the same production step, and generated by the same laser sensor onto the same two-dimensional coordinate system;

[0056] Set several analysis time points on the two-dimensional coordinate system, perform a normal distribution on the amplitude values of different laser reflection signal spectra at the same analysis time point, and select the values in the quarter part of the center of the normal distribution curve relative to the length of the entire normal distribution curve as the normal amplitude value interval corresponding to the analysis time point;

[0057] Connect the normal amplitude value intervals of each analysis time point in sequence to obtain the normal laser reflection signal spectra corresponding to each production device when the corresponding type of metal product performs the corresponding production steps;

[0058] Establish the corresponding standard product dynamic model according to each normal laser reflection signal spectrum, and then overlap and map the standard product dynamic models generated by the laser signals at different emission angles by the same laser sensor;

[0059] It should be noted that during the process of the production equipment processing the metal product, there will be different degrees of interaction with the metal product, resulting in different degrees of loss when the laser signal contacts the metal product. Therefore, laser signals with different emission angles are sent from the same position by the laser sensor. Then, when the metal product moves along the conveyor belt, the laser reflection signal spectra generated by each emission angle are complementary to each other. Therefore, the standard product dynamic models corresponding to the laser reflection signal spectra at different emission angles of the same laser sensor are overlapped, making the standard product dynamic model more accurate and laying a data foundation for subsequent judgment of whether there are abnormalities in the production process;

[0060] Associate the standard product dynamic models generated by each laser sensor on the same processing section in sequence to obtain a standard product dynamic model sequence;

[0061] Along the running direction of the conveyor belt, set m outer surface starting points distributed in a straight line column on the outer surface of each standard product dynamic model in the standard product dynamic model sequence, and set n outer surface detection points distributed side by side and parallel to the distribution of the laser signals on the conveyor belt. Connect the adjacent outer surface starting points and outer surface detection points in the same row in sequence, and then obtain n standard horizontal fluctuation vectors with equal modulus lengths, where both n and m are natural numbers greater than 0;

[0062] Repeat the above process of generating the standard horizontal fluctuation vectors to obtain the standard horizontal fluctuation vectors of various types of metal products passing through different production equipment.

[0063] Step S3: Collect the real-time laser signal spectrum of each production step of the metal product in real time. Establish a two-dimensional product model based on the real-time laser signal spectrum, and set a number of real-time horizontal fluctuation vectors at the edge position of the two-dimensional product model. Establish a sequence of standard product dynamic models for each production step. By comparing the real-time horizontal fluctuation vectors on the two-dimensional product model with the horizontal fluctuation vectors on the standard product dynamic model, determine whether there are abnormalities in the processing process or the shielding cover packaging process of the metal product according to the comparison results;

[0064] The specific implementation process of the said step S3 includes:

[0065] Workers assign production tasks to each production line. The production tasks include the type of metal to be produced and the production quantity. Retrieve the corresponding sequence of standard product dynamic models according to the type of production task;

[0066] Whenever the metal product passes through the laser signal of a laser sensor along the conveyor belt, generate the corresponding real-time laser reflection signal spectrum;

[0067] Set the defect detection frequency according to the time length between each analysis time point. Whenever a defect detection frequency starts, establish the corresponding two-dimensional product model according to the real-time laser reflection signal spectrum, and adopt the process of establishing standard horizontal fluctuation vectors on the outer surface of the standard product dynamic model to set n real-time horizontal fluctuation vectors at the edge position of the two-dimensional product model;

[0068] Establish a three-dimensional coordinate system, and map the real-time horizontal fluctuation vectors generated under each defect detection frequency to the three-dimensional coordinate system in sequence according to the generation time order of the real-time horizontal fluctuation vectors, and map them to the standard horizontal fluctuation vectors of the same sequence on the corresponding standard product dynamic model;

[0069] Match each real-time horizontal fluctuation vector with each standard horizontal fluctuation vector in sequence, and then obtain the dot product between the matched real-time horizontal fluctuation vector and the standard horizontal fluctuation vector;

[0070] Set the dot product threshold, and then judge whether the dot product between each real-time horizontal fluctuation vector and the standard horizontal fluctuation vector is less than or equal to the dot product threshold. If the dot product is less than or equal to the dot product threshold, judge that the position of the metal product associated with the corresponding real-time horizontal fluctuation vector is normal, otherwise judge it as suspected abnormal;

[0071] If after the metal product passes through the laser signals of the same laser sensor three times, there are two or more times that the dot product between the real-time horizontal fluctuation vectors and the corresponding standard horizontal fluctuation vectors at the same position on the generated two-dimensional product model is greater than the dot product threshold, then judge that there are abnormal defects at the relevant position of the metal product;

[0072] After the metal product completely passes through the laser signals at the three emission angles of a laser sensor, a real-time product stage model is generated based on the three emission angles to generate a real-time laser reflection signal spectrum, and the abnormal defect positions are marked on the real-time product stage model. Then, it is sequentially determined whether the real-time product stage models generated in the stamping, cleaning, and packaging steps carry the markings of abnormal defect positions;

[0073] If the real-time product stage model generated in the stamping step carries the markings of abnormal defect positions, it is determined that the stamping process corresponding to the corresponding production equipment is unqualified, and then a product stamping abnormality prompt is generated based on the abnormal defect positions to the staff;

[0074] If the real-time product stage model generated in the cleaning step carries the markings of abnormal defect positions, it is determined that the cleaning step causes defects in the metal product at the abnormal defect positions, and then a product cleaning abnormality prompt is generated based on the abnormal defect positions to the staff;

[0075] If the real-time product stage model generated in the packaging step carries the markings of abnormal defect positions, it is determined that the installation of the shielding cover of the corresponding metal product is unqualified, resulting in non-compliance with the production standards at the abnormal defect positions, and then a shielding cover installation abnormality prompt is generated based on the abnormal defect positions to the staff;

[0076] Repeat the above process of detecting whether there are abnormalities in each production step of the metal product until the production quantity in the production task is completed.

[0077] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for detecting the flatness of a shielding cover based on laser measurement technology, characterized in that, It includes the following steps: Step S1: Set multiple processing sections on the production line according to the production steps of metal products, and install multiple laser sensors in each processing section. During the process that each metal product passes through the processing sections in sequence along the conveyor belt, collect the historical laser signal spectra of each metal product from three emission angles through the laser sensors; Step S2: According to the historical laser signal spectra of metal products under normal production in several production steps, establish a sequence of standard product dynamic models for each production step. At the same time, according to the fluctuations of the historical laser signal spectra at each time point, set several groups of horizontal fluctuation vectors on the outer surface of the standard product dynamic models; The establishment process of the horizontal fluctuation vectors includes: Along the running direction of the conveyor belt, set m outer surface starting points distributed in a straight line on the outer surface of each standard product dynamic model, and set n outer surface detection points distributed side by side and parallel to the distribution of laser signals on the conveyor belt. Connect the adjacent outer surface starting points and outer surface detection points in the same row in sequence, and then obtain n standard horizontal fluctuation vectors with equal modulus lengths, where both n and m are natural numbers greater than 0; Step S3: Collect the real-time laser signal spectra of metal products in each production step in the real-time state, establish a two-dimensional product model according to the real-time laser signal spectra, and set several real-time horizontal fluctuation vectors at the edge position of the two-dimensional product model. Establish a sequence of standard product dynamic models for each production step. By comparing the real-time horizontal fluctuation vectors on the two-dimensional product model with the horizontal fluctuation vectors on the standard product dynamic models, judge whether there are abnormalities in the processing process or the shielding cover packaging process of the metal products according to the comparison results; The process of comparing the real-time horizontal fluctuation vectors with the horizontal fluctuation vectors includes: Establish a three-dimensional coordinate system, and according to the generation time sequence of the real-time horizontal fluctuation vectors, map the real-time horizontal fluctuation vectors generated at each defect detection frequency to the three-dimensional coordinate system in sequence with the standard horizontal fluctuation vectors in the same sequence on the corresponding standard product dynamic models; Match each real-time horizontal fluctuation vector with each standard horizontal fluctuation vector in sequence pairwise, and then obtain the dot product between the matched real-time horizontal fluctuation vector and the standard horizontal fluctuation vector; Set a dot product threshold, and then judge whether the dot product between each real-time horizontal fluctuation vector and the standard horizontal fluctuation vector is less than or equal to the dot product threshold. If the dot product is less than or equal to the dot product threshold, judge that the position of the metal product associated with the corresponding real-time horizontal fluctuation vector is normal, otherwise judge it as suspected abnormal.

2. The flatness detection method of the shielding cover based on laser measurement technology according to claim 1, characterized in that, The production steps of the metal products include stamping, cleaning, and packaging. Install corresponding production equipment on the production line according to the production steps of the metal products, and connect each production equipment in sequence through the conveyor belt. Divide the production equipment corresponding to the same production step into a group, and then divide three processing sections on the production line.

3. The flatness detection method of the shielding cover based on the laser measurement technology according to claim 2, wherein, The production equipment is bound with a laser sensor, and each laser sensor is set with a number. During the process of processing metal products on the production line, each laser sensor on the production line emits n strings of laser signals vertically and at an angle of 45 degrees obliquely to both sides towards the conveyor belt, and each string of laser signals is in a horizontal straight line on the conveyor belt.

4. The flatness detection method of a shielding cover based on laser measurement technology according to claim 3, characterized in that, The process of collecting the historical laser signal spectrum includes: Bind a laser sensor to each production equipment, and set a number for each laser sensor. During the process of processing metal products on the production line, each laser sensor on the production line emits n strings of laser signals vertically and at an angle of 45 degrees obliquely to both sides towards the conveyor belt, and each string of laser signals is in a horizontal straight line on the conveyor belt; When the conveyor belt conveys metal products through each processing section in sequence, each laser signal passes through the metal product and generates a corresponding laser reflection signal spectrum, and mark the number and emission angle of the laser sensor for each laser reflection signal spectrum, thereby collecting several laser reflection signal spectra of the metal product under different production steps.

5. The flatness detection method of the shielding cover based on the laser measurement technology according to claim 4, characterized in that The process of establishing the standard product dynamic model sequence: Select the laser reflection signal spectra of metal products under each production step under normal production, establish a two-dimensional coordinate system, and map the laser reflection signal spectra corresponding to the same type of metal product, the same production step, and generated by the same laser sensor onto the same two-dimensional coordinate system; Set several analysis time points on the two-dimensional coordinate system, perform normal distribution on the amplitude values of different laser reflection signal spectra at the same analysis time point, and generate the normal amplitude value interval at each analysis time point according to the normal distribution result; Connect the normal amplitude value intervals of each analysis time point in sequence to obtain the normal laser reflection signal spectrum corresponding to each production equipment of the corresponding type of metal product under the execution of the corresponding production step; Establish a corresponding standard product dynamic model according to each normal laser reflection signal spectrum, and then overlap and map the standard product dynamic models generated by laser signals at different emission angles by the same laser sensor, and then sequentially associate the standard product dynamic models corresponding to each laser sensor on the same processing section to obtain the standard product dynamic model sequence.

6. The flatness detection method of a shielding cover based on laser measurement technology according to claim 1, wherein The process of establishing a two-dimensional product model according to the real-time laser signal spectrum includes: Whenever a metal product passes through the laser signal of a laser sensor along with the conveyor belt, a corresponding real-time laser reflection signal spectrum is generated; Set the defect detection frequency according to the time length between each analysis time point. Whenever a defect detection frequency starts, establish a corresponding two-dimensional product model according to the real-time laser reflection signal spectrum, and adopt the process of establishing a standard horizontal fluctuation vector on the outer surface of the standard product dynamic model to set n real-time horizontal fluctuation vectors at the edge position of the two-dimensional product model.

7. A method for detecting the flatness of a shielding cover based on laser measurement technology according to claim 1, characterized in that, If after the metal product passes through the three laser signals of the same laser sensor, on the corresponding two-dimensional product model, the dot product between the real-time horizontal fluctuation vectors and the corresponding standard horizontal fluctuation vectors at the same position is greater than the dot product threshold for two or more times, it is determined that there is an abnormal defect at the relevant position of the metal product.

8. A method for detecting the flatness of a shielding cover based on laser measurement technology according to claim 7, characterized in that The process of determining whether there are abnormalities in the processing process of metal products or the shielding cover packaging process includes: After the metal product completely passes through the laser signals at three emission angles of a laser sensor, a real-time product stage model is generated according to the three emission angles to generate a real-time laser reflection signal spectrum, and the abnormal defect positions are marked on the real-time product stage model; Judge in turn whether the real-time product stage models generated in the stamping, cleaning or packaging steps are marked with abnormal defect positions, and judge whether there are abnormalities in the processing process of metal products or the shielding cover packaging process according to the judgment results.

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