Gear stress defect detection method and system based on magnetic memory effect

Abstract

The invention relates to the field of gear defect detection, and discloses a gear stress defect detection method and system based on a magnetic memory effect, and the method comprises the following steps: carrying out cleaning treatment on a target gear, and carrying out surface magnetization treatment on the target gear through magnetization equipment to obtain a surface-magnetized target gear. And performing magnetic memory scanning on the surface magnetized target gear through a magnetic memory scanner, performing data analysis on the obtained magnetic memory data of the surface magnetized target gear after the magnetic memory scanning, and obtaining and correcting a stress abnormal area of the surface magnetized target gear. According to the invention, the stress defect detection of the gear can be realized in a magnetic memory effect mode, the magnetic memory detection technology does not cause any damage to the gear, and the magnetic memory detection technology has high sensitivity and precision and is an innovative non-destructive detection technology.

Description

Technical Field

[0001] The invention relates to the field of gear defect detection, and in particular to a gear stress defect detection method and system based on magnetic memory effect. Background Art

[0002] If the gear design is unreasonable, the gear will be subjected to excessive load in the process of transmitting torque, thus generating large stress. At the same time, poor manufacturing process of the gear, such as large gear surface roughness and poor tooth surface hardness, will also increase the stress of the gear. After the gear is subjected to stress, it may deform, causing the geometric shape of the gear to change, thereby affecting the transmission efficiency of the gear. In order to improve the stress on the gear, if the direct disassembly analysis method is used, the efficiency of stress monitoring will be reduced. A gear stress defect detection method based on magnetic memory effect is proposed. The gear stress defect detection method based on magnetic memory effect is an innovative non-destructive detection technology, which uses the magnetic memory effect of magnetic materials to detect stress states and defects in gears. The magnetic memory effect refers to the change in the magnetic state of a magnetic material when it is subjected to external stress or magnetic field. This change will form a change in the magnetic field distribution on the surface of the material, thereby forming a magnetic memory pattern. This magnetic memory pattern can be detected and analyzed by a magnetic sensor to obtain information on the defects and stress state of the material. Summary of the invention

[0003] The present invention overcomes the deficiencies of the prior art and provides a gear stress defect detection method and system based on the magnetic memory effect.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is:

[0005] The first aspect of the present invention provides a gear stress defect detection method based on magnetic memory effect, comprising the following steps:

[0006] A magnetic sensor is selected to act on a target gear for stress defect detection, and the target gear is cleaned to obtain a surface-cleaned target gear;

[0007] Laser scanning technology and ant colony algorithm are introduced, and the surface of the clean target gear is magnetized by magnetization equipment to obtain the surface magnetized target gear;

[0008] Performing magnetic memory scanning on the surface magnetized target gear by means of a magnetic memory scanner, and processing scanning signal data obtained by the magnetic memory scanning;

[0009] The magnetic memory data of the surface magnetized target gear is analyzed, and based on the analysis result, the stress abnormality area of ​​the surface magnetized target gear is determined, and the abnormality correction is performed on the stress abnormality area of ​​the surface magnetized target gear.

[0010] Furthermore, in a preferred embodiment of the present invention, the magnetic sensor acting on the target gear for stress defect detection is selected, and the target gear is cleaned to obtain a surface-cleaned target gear, specifically:

[0011] Acquire all gears that need to be inspected for stress defects, mark them as gears to be inspected, and among all gears to be inspected, mark the gears to be inspected that are about to be inspected for stress defects as target gears;

[0012] Obtaining the instruction manual of the target gear, determining the component structure of the target gear based on the instruction manual of the target gear, obtaining a big data network, analyzing the component structure of the target gear based on the big data network, retrieving the type of magnetic sensor that can perform a complete magnetic memory scan on the component structure of the target gear, calibrating it as a qualified magnetic sensor type, and selecting a magnetic sensor of the qualified magnetic sensor type and calibrating it as a target magnetic sensor;

[0013] Performing a surface cleaning treatment on the target gear to obtain a preliminarily cleaned target gear, and sampling surface material on the preliminarily cleaned target gear to obtain a surface material sample of the preliminarily cleaned target gear;

[0014] Performing a compound type test on the surface material sample of the preliminary cleaned target gear, determining the compound type of the surface material sample of the preliminary cleaned target gear, calibrating it as the pollutant compound type, and determining the surface material type of the preliminary cleaned gear, calibrating it as the target surface material type;

[0015] Retrieving and obtaining a target cleaning scheme in a big data network, wherein the target cleaning scheme can clean the preliminary clean target gear based on the type of the pollutant compound, and the target cleaning scheme will not react with the surface material of the preliminary clean gear of the target surface material type when it is in effect;

[0016] The target cleaning scheme is output to obtain a surface-cleaned target gear.

[0017] Furthermore, in a preferred embodiment of the present invention, the laser scanning technology and the ant colony algorithm are introduced, and the surface cleaning target gear is subjected to surface magnetization treatment by a magnetization device to obtain a surface magnetized target gear, specifically:

[0018] Obtaining a magnetizing device, wherein the magnetizing device is a device that can perform surface magnetization treatment on a surface cleaning target gear, and the surface magnetization treatment is to apply a magnetic field on the surface cleaning target gear;

[0019] Obtaining the magnetization range of the magnetization device and the occupied ranges of different surfaces of the surface cleaning target gear. If the magnetization range of the magnetization device completely covers the occupied ranges of all surfaces of the surface cleaning target gear, the surface cleaning target gear is directly magnetized by the magnetization device to obtain the surface cleaning target gear after surface magnetization, which is defined as the surface magnetized target gear.

[0020] If there is any surface cleaning target gear whose surface occupies a range that cannot be completely covered by the magnetization range of the magnetization device, the surface of the corresponding surface cleaning target gear is calibrated as a type of surface cleaning target gear surface;

[0021] Acquire a laser scanning device, perform laser scanning on a target cleaning target gear based on the laser scanning device, construct a laser scanning model of the target cleaning target gear in combination with the component structure of the target gear, calibrate it as a target laser scanning model, and mark a class of surface cleaning target gear surfaces in the target laser scanning model;

[0022] In the target laser scanning model, an ant colony algorithm is introduced, and a surface edge point is determined on the surface of a type of surface-cleaning target gear in the target laser scanning model and calibrated as the path starting point;

[0023] The ant colony algorithm is set, wherein the ant colony algorithm is set to adjust the occupied range of the path in the ant colony algorithm to the magnetization range of the magnetization device, and the set ant colony algorithm is applied to a surface of a type of surface-cleaning target gear of the target laser scanning model, and all paths that can completely magnetize the surface of a type of surface-cleaning target gear of the target laser scanning model starting from the starting point of the path are obtained, and are calibrated as magnetization paths to be analyzed;

[0024] Among all the magnetization paths to be analyzed, the magnetization path to be analyzed with the shortest path length is selected and calibrated as the target magnetization path. The magnetization device is controlled to perform surface magnetization treatment on the surface of a first-class surface-cleaning target gear based on the target magnetization path, and the magnetization device is controlled to perform direct magnetization treatment on the surface of the target clean target gear that is not a first-class surface-cleaning target gear surface, so as to obtain a surface magnetized target gear.

[0025] Furthermore, in a preferred embodiment of the present invention, the magnetic memory scanning is performed on the surface magnetized target gear by the magnetic memory scanner, and the scanning signal data obtained by the magnetic memory scanning is processed, specifically:

[0026] Acquire a magnetic memory scanner, wherein the magnetic memory scanner is integrated with a target magnetic sensor, the magnetic sensor can perform magnetic memory scanning on the magnetized metal surface, and the magnetic memory scanner can perform data preprocessing on the scan data obtained after the magnetic memory scanning;

[0027] By means of the magnetic memory scanner, a magnetic memory scan is performed on the surface of the magnetized target gear, and the scan data obtained after the magnetic memory scan is stored in the magnetic memory scanner and calibrated as magnetic memory scan data;

[0028] Wherein, the magnetic memory scanning data is the surface magnetic field distribution data and surface magnetic field intensity data of the surface magnetized target gear;

[0029] In the magnetic memory scanner, frequency analysis is performed on the magnetic memory scanning data to obtain the data frequency of the magnetic memory scanning data, and a data standard frequency range of the magnetic memory scanning data is preset;

[0030] If the data frequency of the magnetic memory scanning data is not completely maintained within the data standard frequency range, a sliding average filtering algorithm is introduced to filter the magnetic memory scanning data so that the data frequency of the magnetic memory scanning data is completely maintained within the data standard frequency range to obtain qualified magnetic memory scanning data, and the qualified magnetic memory scanning data is signal converted to obtain a qualified magnetic memory scanning electrical signal;

[0031] A signal analysis device is introduced and integrated with a magnetic memory scanner. The magnetic memory scanner integrated with the signal analysis device performs signal analysis on qualified magnetic memory scanning electrical signals to generate gear surface magnetic domain distribution characteristic data, gear surface magnetic domain boundary characteristic data, and gear surface magnetic field signal intensity characteristic data of the surface magnetized target gear.

[0032] The gear surface magnetic domain distribution characteristic data, gear surface magnetic domain boundary characteristic data and gear surface magnetic field signal intensity characteristic data of the surface magnetized target gear are collectively referred to as the surface magnetized target gear magnetic memory data.

[0033] Furthermore, in a preferred embodiment of the present invention, the magnetic memory data of the surface magnetized target gear is analyzed, the stress abnormality area of ​​the surface magnetized target gear is determined based on the analysis result, and the stress abnormality area of ​​the surface magnetized target gear is corrected abnormally, specifically:

[0034] Constructing a two-dimensional data representation space, and importing the magnetic memory data of the surface magnetized target gear into the two-dimensional data representation space, generating a two-dimensional visualization pattern of the magnetic memory of the surface magnetized target gear, and calibrating it as a target pattern;

[0035] The target pattern is a characteristic curve, and the characteristic curve analysis is performed on the target pattern to calculate the area sizes of all closed areas on the target pattern, wherein different closed areas represent different areas on the surface magnetized target gear, and the surface magnetic field mutation sizes of different areas on the surface magnetized target gear are calculated based on the area sizes of the closed areas;

[0036] Based on the big data network, the stress concentration degree-surface magnetic field mutation size comparison spectrum is retrieved and calibrated as the target comparison spectrum. The surface magnetic field mutation sizes of different areas on the surface magnetized target gear are imported into the target comparison spectrum, and the stress concentration degree of different areas on the surface magnetized target gear is calculated.

[0037] The maximum stress concentration degree is preset, and the area on the surface magnetized target gear where the stress concentration degree is greater than the maximum stress concentration degree is marked as the stress abnormal area of ​​the surface magnetized target gear;

[0038] A stress anomaly root cause analysis is performed on the stress anomaly area of ​​the surface magnetized target gear, and based on the stress anomaly root cause analysis result, an abnormal correction is performed on the stress anomaly area of ​​the surface magnetized target gear.

[0039] Furthermore, in a preferred embodiment of the present invention, the stress abnormality region of the surface magnetized target gear is subjected to stress abnormality root cause analysis, and based on the stress abnormality root cause analysis result, the stress abnormality region of the surface magnetized target gear is subjected to abnormality correction, specifically:

[0040] Obtain standard design gear parameters of the stress abnormality region of the surface magnetized target gear through the instruction manual of the target gear, and construct a three-dimensional model of the stress abnormality region of the surface magnetized target gear through a three-dimensional modeling method, and obtain actual gear parameters of the stress abnormality region of the surface magnetized target gear based on the three-dimensional model of the stress abnormality region of the surface magnetized target gear;

[0041] If the actual gear parameters of the surface magnetized target gear in the stress abnormality region are less than the standard design gear parameters, the surface magnetized target gear is scrapped;

[0042] If, in the surface magnetized target gear, there is no actual gear parameter less than the standard design gear parameter in the stress abnormal area, but there is an actual gear parameter greater than the standard design gear parameter, then the stress abnormal area of ​​the corresponding surface magnetized target gear where the actual gear parameter is greater than the standard design gear parameter is marked as the design abnormal area, and the design gear area repair solution of the design abnormal area is retrieved in the big data network and output;

[0043] If the surface magnetized target gear still has a stress abnormality region after the design gear region repair plan of the design abnormality region is output, lubrication treatment is performed on the stress abnormality region of the surface magnetized target gear, and it is determined whether the surface magnetized target gear still has a stress abnormality region after the lubrication treatment;

[0044] If so, the surface magnetized target gear is scrapped; if not, the surface magnetized target gear is calibrated as a stress-free target gear.

[0045] The second aspect of the present invention further provides a gear stress defect detection system based on magnetic memory effect, the gear stress defect detection system comprising a memory and a processor, the memory storing a gear stress defect detection method, and when the gear stress defect detection method is executed by the processor, the following steps are implemented:

[0046] A magnetic sensor is selected to act on a target gear for stress defect detection, and the target gear is cleaned to obtain a surface-cleaned target gear;

[0047] Laser scanning technology and ant colony algorithm are introduced, and the surface of the clean target gear is magnetized by magnetization equipment to obtain the surface magnetized target gear;

[0048] Performing magnetic memory scanning on the surface magnetized target gear by means of a magnetic memory scanner, and processing scanning signal data obtained by the magnetic memory scanning;

[0049] The magnetic memory data of the surface magnetized target gear is analyzed, and based on the analysis result, the stress abnormality area of ​​the surface magnetized target gear is determined, and the abnormality correction is performed on the stress abnormality area of ​​the surface magnetized target gear.

[0050] The present invention solves the technical defects existing in the background technology, and has the following beneficial effects: the target gear is cleaned and the surface of the target gear is magnetized by a magnetizing device to obtain a surface magnetized target gear. The surface magnetized target gear is subjected to a magnetic memory scan by a magnetic memory scanner, and the magnetic memory data of the surface magnetized target gear obtained after the magnetic memory scan is analyzed to obtain the stress abnormality area of ​​the surface magnetized target gear and make corrections. The present invention can realize the stress defect detection of the gear by means of the magnetic memory effect. The magnetic memory detection technology will not cause any damage to the gear, and has high sensitivity and accuracy. It is an innovative non-destructive detection technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0052] Figure 1 A flow chart of a gear stress defect detection method based on magnetic memory effect is shown;

[0053] Figure 2 A flow chart of a method for determining an abnormal stress area and a correction scheme for a surface magnetized target gear is shown;

[0054] Figure 3 A program view of a gear stress defect detection system based on magnetic memory effect is shown. DETAILED DESCRIPTION

[0055] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0056] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0057] Figure 1 A flow chart of a gear stress defect detection method based on magnetic memory effect is shown, comprising the following steps:

[0058] S102: selecting a magnetic sensor to act on a target gear for stress defect detection, and cleaning the target gear to obtain a surface-cleaned target gear;

[0059] S104: Introducing laser scanning technology and ant colony algorithm, and performing surface magnetization treatment on the surface clean target gear through a magnetization device to obtain a surface magnetized target gear;

[0060] S106: performing a magnetic memory scan on the surface magnetized target gear by means of a magnetic memory scanner, and processing scan signal data obtained by the magnetic memory scan;

[0061] S108: Analyze the magnetic memory data of the surface magnetized target gear, determine the stress abnormality area of ​​the surface magnetized target gear based on the analysis result, and perform abnormal correction on the stress abnormality area of ​​the surface magnetized target gear.

[0062] Furthermore, in a preferred embodiment of the present invention, the magnetic sensor acting on the target gear for stress defect detection is selected, and the target gear is cleaned to obtain a surface-cleaned target gear, specifically:

[0063] Acquire all gears that need to be inspected for stress defects, mark them as gears to be inspected, and among all gears to be inspected, mark the gears to be inspected that are about to be inspected for stress defects as target gears;

[0064] Obtaining the instruction manual of the target gear, determining the component structure of the target gear based on the instruction manual of the target gear, obtaining a big data network, analyzing the component structure of the target gear based on the big data network, retrieving the type of magnetic sensor that can perform a complete magnetic memory scan on the component structure of the target gear, calibrating it as a qualified magnetic sensor type, and selecting a magnetic sensor of the qualified magnetic sensor type and calibrating it as a target magnetic sensor;

[0065] Performing a surface cleaning treatment on the target gear to obtain a preliminarily cleaned target gear, and sampling surface material on the preliminarily cleaned target gear to obtain a surface material sample of the preliminarily cleaned target gear;

[0066] Performing a compound type test on the surface material sample of the preliminary cleaned target gear, determining the compound type of the surface material sample of the preliminary cleaned target gear, calibrating it as the pollutant compound type, and determining the surface material type of the preliminary cleaned gear, calibrating it as the target surface material type;

[0067] Retrieving and obtaining a target cleaning scheme in a big data network, wherein the target cleaning scheme can clean the preliminary clean target gear based on the type of the pollutant compound, and the target cleaning scheme will not react with the surface material of the preliminary clean gear of the target surface material type when it is in effect;

[0068] The target cleaning scheme is output to obtain a surface-cleaned target gear.

[0069] It should be noted that after the target gear is determined, if the target gear is subjected to stress defect detection by means of magnetic memory effect, it is necessary to obtain a suitable magnetic sensor, namely, a target magnetic sensor, because target gears of different structures require different types of magnetic sensors, and some target gear structures require special magnetic sensors to scan and obtain data such as magnetic field strength. And the target gear needs to be cleaned before stress detection, because if there are pollutants such as dust and oil on the target gear, when the magnetic field is applied, the magnetic field may not be applied evenly due to the presence of pollutants, resulting in errors in the location of stress defects when scanning later. Therefore, cleaning is required, and the cleaning process includes dust removal and oil removal. After dust removal, the oily substances on the gear surface are sampled and analyzed, and compounds that can remove the oily substances and will not damage the gear surface are selected to clean the oily substances to prevent the compounds from corroding the gear. Finally, a target gear with a clean surface is obtained.

[0070] Furthermore, in a preferred embodiment of the present invention, the laser scanning technology and the ant colony algorithm are introduced, and the surface cleaning target gear is subjected to surface magnetization treatment by a magnetization device to obtain a surface magnetized target gear, specifically:

[0071] Obtaining a magnetizing device, wherein the magnetizing device is a device that can perform surface magnetization treatment on a surface cleaning target gear, and the surface magnetization treatment is to apply a magnetic field on the surface cleaning target gear;

[0072] Obtaining the magnetization range of the magnetization device and the occupied ranges of different surfaces of the surface cleaning target gear. If the magnetization range of the magnetization device completely covers the occupied ranges of all surfaces of the surface cleaning target gear, the surface cleaning target gear is directly magnetized by the magnetization device to obtain the surface cleaning target gear after surface magnetization, which is defined as the surface magnetized target gear.

[0073] If there is any surface cleaning target gear whose surface occupies a range that cannot be completely covered by the magnetization range of the magnetization device, the surface of the corresponding surface cleaning target gear is calibrated as a type of surface cleaning target gear surface;

[0074] Acquire a laser scanning device, perform laser scanning on a target cleaning target gear based on the laser scanning device, construct a laser scanning model of the target cleaning target gear in combination with the component structure of the target gear, calibrate it as a target laser scanning model, and mark a class of surface cleaning target gear surfaces in the target laser scanning model;

[0075] In the target laser scanning model, an ant colony algorithm is introduced, and a surface edge point is determined on the surface of a type of surface-cleaning target gear in the target laser scanning model and calibrated as the path starting point;

[0076] The ant colony algorithm is set, wherein the ant colony algorithm is set to adjust the occupied range of the path in the ant colony algorithm to the magnetization range of the magnetization device, and the set ant colony algorithm is applied to a surface of a type of surface-cleaning target gear of the target laser scanning model, and all paths that can completely magnetize the surface of a type of surface-cleaning target gear of the target laser scanning model starting from the starting point of the path are obtained, and are calibrated as magnetization paths to be analyzed;

[0077] Among all the magnetization paths to be analyzed, the magnetization path to be analyzed with the shortest path length is selected and calibrated as the target magnetization path. The magnetization device is controlled to perform surface magnetization treatment on the surface of a first-class surface-cleaning target gear based on the target magnetization path, and the magnetization device is controlled to perform direct magnetization treatment on the surface of the target clean target gear that is not a first-class surface-cleaning target gear surface, so as to obtain a surface magnetized target gear.

[0078] It should be noted that before the magnetizing device magnetizes the gear, it is necessary to determine whether the magnetizing device can fully magnetize a certain surface of the gear at one time, that is, to determine whether the magnetizing range of the magnetizing device directly includes the occupied range of a certain surface of the gear. If the storage surface cannot be fully magnetized at one time, it is necessary to use the magnetizing device to repeatedly magnetize the surface of the gear, that is, the surface of a type of surface cleaning target gear. Repeated magnetization requires the construction of a magnetization path to ensure that the path is shortest and uniform magnetization can be guaranteed. The construction of a target laser scanning model through a laser scanning device can more directly and clearly determine the magnetization path, so that the data can be directly visualized. The ant colony algorithm simulates that ants can leave pheromones on the path they pass through during movement as a carrier for information transmission and communication. Through this indirect communication mechanism, individual ants achieve the goal of collaboratively searching for the shortest path. Through the ant colony algorithm, a starting point is selected on the surface of a type of surface cleaning target gear of the laser scanning device. From the starting point, all points can be end points, and all magnetization paths from the starting point to the end point are obtained, and the occupied range of the magnetization path is adjusted to the magnetization range of the magnetization device, in order to reduce the repetition of the magnetization range. After obtaining the magnetization path to be analyzed, the path with the shortest length is selected as the output path. The surface that does not need to obtain the magnetization path is directly magnetized, and the surface that needs to obtain the magnetization path is magnetized according to the target magnetization path to obtain the surface magnetized target gear.

[0079] Furthermore, in a preferred embodiment of the present invention, the magnetic memory scanning is performed on the surface magnetized target gear by the magnetic memory scanner, and the scanning signal data obtained by the magnetic memory scanning is processed, specifically:

[0080] Acquire a magnetic memory scanner, wherein the magnetic memory scanner is integrated with a target magnetic sensor, the magnetic sensor can perform magnetic memory scanning on the magnetized metal surface, and the magnetic memory scanner can perform data preprocessing on the scan data obtained after the magnetic memory scanning;

[0081] By means of the magnetic memory scanner, a magnetic memory scan is performed on the surface of the magnetized target gear, and the scan data obtained after the magnetic memory scan is stored in the magnetic memory scanner and calibrated as magnetic memory scan data;

[0082] Wherein, the magnetic memory scanning data is the surface magnetic field distribution data and surface magnetic field intensity data of the surface magnetized target gear;

[0083] In the magnetic memory scanner, frequency analysis is performed on the magnetic memory scanning data to obtain the data frequency of the magnetic memory scanning data, and a data standard frequency range of the magnetic memory scanning data is preset;

[0084] If the data frequency of the magnetic memory scanning data is not completely maintained within the data standard frequency range, a sliding average filtering algorithm is introduced to filter the magnetic memory scanning data so that the data frequency of the magnetic memory scanning data is completely maintained within the data standard frequency range to obtain qualified magnetic memory scanning data, and the qualified magnetic memory scanning data is signal converted to obtain a qualified magnetic memory scanning electrical signal;

[0085] A signal analysis device is introduced and integrated with a magnetic memory scanner. The magnetic memory scanner integrated with the signal analysis device performs signal analysis on qualified magnetic memory scanning electrical signals to generate gear surface magnetic domain distribution characteristic data, gear surface magnetic domain boundary characteristic data, and gear surface magnetic field signal intensity characteristic data of the surface magnetized target gear.

[0086] The gear surface magnetic domain distribution characteristic data, gear surface magnetic domain boundary characteristic data and gear surface magnetic field signal intensity characteristic data of the surface magnetized target gear are collectively referred to as the surface magnetized target gear magnetic memory data.

[0087] It should be noted that the magnetic memory scanner is integrated with a selected target magnetic sensor. The function of the magnetic sensor is to monitor and record the changes in the magnetic field distribution on the gear surface to obtain magnetic memory scanning data. Subsequently, since the collected magnetic memory scanning data may have large frequency fluctuations, which will lead to inaccurate data, the data can be filtered by sliding average filtering, and the filtered data can be converted into signals, so that the signal analysis device can analyze the data. The gear surface magnetic domain distribution characteristic data, the gear surface magnetic domain boundary characteristic data, and the gear surface magnetic field signal intensity characteristic data reflect the stress state, defect characteristics and other information of the gear, and are collectively referred to as surface magnetized target gear magnetic memory data.

[0088] Figure 2 A flow chart of a method for determining an abnormal stress area and a correction scheme for a surface magnetized target gear is shown, comprising the following steps:

[0089] S202: Analyze the magnetic memory data of the surface magnetized target gear to determine the stress abnormality area of ​​the surface magnetized target gear;

[0090] S204: performing a stress anomaly root cause analysis on the stress anomaly region of the surface magnetized target gear, and performing an anomaly correction on the stress anomaly region of the surface magnetized target gear based on the stress anomaly root cause analysis result.

[0091] Furthermore, in a preferred embodiment of the present invention, the magnetic memory data of the surface magnetized target gear is analyzed, the stress abnormality area of ​​the surface magnetized target gear is determined based on the analysis result, and the stress abnormality area of ​​the surface magnetized target gear is corrected abnormally, specifically:

[0092] Constructing a two-dimensional data representation space, and importing the magnetic memory data of the surface magnetized target gear into the two-dimensional data representation space, generating a two-dimensional visualization pattern of the magnetic memory of the surface magnetized target gear, and calibrating it as a target pattern;

[0093] The target pattern is a characteristic curve, and the characteristic curve analysis is performed on the target pattern to calculate the area sizes of all closed areas on the target pattern, wherein different closed areas represent different areas on the surface magnetized target gear, and the surface magnetic field mutation sizes of different areas on the surface magnetized target gear are calculated based on the area sizes of the closed areas;

[0094] Based on the big data network, the stress concentration degree-surface magnetic field mutation size comparison spectrum is retrieved and calibrated as the target comparison spectrum. The surface magnetic field mutation sizes of different areas on the surface magnetized target gear are imported into the target comparison spectrum, and the stress concentration degree of different areas on the surface magnetized target gear is calculated.

[0095] The maximum stress concentration degree is preset, and the area on the surface magnetized target gear where the stress concentration degree is greater than the maximum stress concentration degree is calibrated as the stress abnormality area of ​​the surface magnetized target gear.

[0096] It should be noted that in the two-dimensional data representation space, the magnetic memory data of the surface magnetized target gear can be converted into a two-dimensional visualization pattern of the magnetic memory of the surface magnetized target gear. The two-dimensional visualization pattern of the magnetic memory of the surface magnetized target gear is a characteristic curve. The area of ​​the closed region in the curve can calculate the size of the surface magnetic field mutation in the region, and the size of the surface magnetic field mutation reflects the degree of stress concentration. Because during the scanning process, if the size of the surface magnetic field mutation is large, it proves that the stress concentration degree in this place is also large. After obtaining the target comparison map, the stress concentration degree of different areas on the surface magnetized target gear can be determined, and the areas with abnormal stress can be screened and marked as stress abnormal areas of the surface magnetized target gear.

[0097] Furthermore, in a preferred embodiment of the present invention, the stress abnormality region of the surface magnetized target gear is subjected to stress abnormality root cause analysis, and based on the stress abnormality root cause analysis result, the stress abnormality region of the surface magnetized target gear is subjected to abnormality correction, specifically:

[0098] Obtain standard design gear parameters of the stress abnormality region of the surface magnetized target gear through the instruction manual of the target gear, and construct a three-dimensional model of the stress abnormality region of the surface magnetized target gear through a three-dimensional modeling method, and obtain actual gear parameters of the stress abnormality region of the surface magnetized target gear based on the three-dimensional model of the stress abnormality region of the surface magnetized target gear;

[0099] If the actual gear parameters of the surface magnetized target gear in the stress abnormality region are less than the standard design gear parameters, the surface magnetized target gear is scrapped;

[0100] If, in the surface magnetized target gear, there is no actual gear parameter less than the standard design gear parameter in the stress abnormal area, but there is an actual gear parameter greater than the standard design gear parameter, then the stress abnormal area of ​​the corresponding surface magnetized target gear where the actual gear parameter is greater than the standard design gear parameter is marked as the design abnormal area, and the design gear area repair solution of the design abnormal area is retrieved in the big data network and output;

[0101] If the surface magnetized target gear still has a stress abnormality region after the design gear region repair plan of the design abnormality region is output, lubrication treatment is performed on the stress abnormality region of the surface magnetized target gear, and it is determined whether the surface magnetized target gear still has a stress abnormality region after the lubrication treatment;

[0102] If so, the surface magnetized target gear is scrapped; if not, the surface magnetized target gear is calibrated as a stress-free target gear.

[0103] It should be noted that the reason for the abnormal gear stress may be that the gear design is unreasonable, such as the deformation of the gear parameters due to long-term operation, or the large surface roughness of the gear and the poor hardness of the tooth surface, which will cause the gear to be subjected to uneven load during the torque transmission process, which will increase the stress. Therefore, it is necessary to determine the relationship between the actual gear parameters and the standard parameters of the stress abnormal area of ​​the surface magnetized target gear. If the actual gear parameters in the stress abnormal area are less than the standard parameters, that is, the gear cannot be repaired, such as the gear is missing, the gear is broken, etc., then the gear is directly scrapped and cannot be repaired. If the actual gear parameters in the stress abnormal area are greater than the standard parameters, it proves that the gear is still possible to repair, such as foreign matter on the gear, or there are bulges. At this time, the design gear area repair scheme of the design abnormal area can be retrieved and output through the big data network, that is, some schemes that can remove foreign matter or correct bulges on the gear can be retrieved. If there is still a stress abnormal area after the design gear area repair scheme is output, it proves that the reason for the stress abnormality on the gear may be that the lubricant is unqualified, which accelerates the wear of the gear and increases the gear stress. At this time, the lubricant is relubricated. If there is still a stress abnormal area, the gear cannot be used anymore and needs to be scrapped.

[0104] like Figure 3As shown, the second aspect of the present invention further provides a gear stress defect detection system based on magnetic memory effect, the gear stress defect detection system comprises a memory 31 and a processor 32, the memory 31 stores a gear stress defect detection method, and when the gear stress defect detection method is executed by the processor 32, the following steps are implemented:

[0105] A magnetic sensor is selected to act on a target gear for stress defect detection, and the target gear is cleaned to obtain a surface-cleaned target gear;

[0106] Laser scanning technology and ant colony algorithm are introduced, and the surface of the clean target gear is magnetized by magnetization equipment to obtain the surface magnetized target gear;

[0107] Performing magnetic memory scanning on the surface magnetized target gear by means of a magnetic memory scanner, and processing scanning signal data obtained by the magnetic memory scanning;

[0108] The magnetic memory data of the surface magnetized target gear is analyzed, and based on the analysis result, the stress abnormality area of ​​the surface magnetized target gear is determined, and the abnormality correction is performed on the stress abnormality area of ​​the surface magnetized target gear.

[0109] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A gear stress defect detection method based on magnetic memory effect, It is characterized in that The following steps are involved: A magnetic sensor is selected to act on a target gear for stress defect detection, and the target gear is cleaned to obtain a surface-cleaned target gear; Laser scanning technology and ant colony algorithm are introduced, and the surface of the clean target gear is magnetized by magnetization equipment to obtain the surface magnetized target gear; Performing magnetic memory scanning on the surface magnetized target gear by means of a magnetic memory scanner, and processing scanning signal data obtained by the magnetic memory scanning; The magnetic memory data of the surface magnetized target gear is analyzed, and based on the analysis result, the stress abnormality area of ​​the surface magnetized target gear is determined, and the abnormality correction is performed on the stress abnormality area of ​​the surface magnetized target gear.

2. According to the gear stress defect detection method based on magnetic memory effect described in claim 1, It is characterized in that The method of selecting a magnetic sensor for stress defect detection on a target gear and cleaning the target gear to obtain a surface-cleaned target gear is as follows: Acquire all gears that need to be inspected for stress defects, mark them as gears to be inspected, and among all gears to be inspected, mark the gears to be inspected that are about to be inspected for stress defects as target gears; Obtaining the instruction manual of the target gear, determining the component structure of the target gear based on the instruction manual of the target gear, obtaining a big data network, analyzing the component structure of the target gear based on the big data network, retrieving the type of magnetic sensor that can perform a complete magnetic memory scan on the component structure of the target gear, calibrating it as a qualified magnetic sensor type, and selecting a magnetic sensor of the qualified magnetic sensor type and calibrating it as a target magnetic sensor; Performing a surface cleaning treatment on the target gear to obtain a preliminarily cleaned target gear, and sampling surface material on the preliminarily cleaned target gear to obtain a surface material sample of the preliminarily cleaned target gear; Performing a compound type test on the surface material sample of the preliminary cleaned target gear, determining the compound type of the surface material sample of the preliminary cleaned target gear, calibrating it as the pollutant compound type, and determining the surface material type of the preliminary cleaned gear, calibrating it as the target surface material type; Retrieving and obtaining a target cleaning scheme in a big data network, wherein the target cleaning scheme can clean the preliminary clean target gear based on the type of the pollutant compound, and the target cleaning scheme will not react with the surface material of the preliminary clean gear of the target surface material type when it is in effect; The target cleaning scheme is output to obtain a surface-cleaned target gear.

3. According to the gear stress defect detection method based on magnetic memory effect described in claim 1, It is characterized in that The laser scanning technology and the ant colony algorithm are introduced, and the surface of the cleaned target gear is magnetized by a magnetizing device to obtain a surface magnetized target gear, specifically: Obtaining a magnetizing device, wherein the magnetizing device is a device that can perform surface magnetization treatment on a surface cleaning target gear, and the surface magnetization treatment is to apply a magnetic field on the surface cleaning target gear; Obtaining the magnetization range of the magnetization device and the occupied ranges of different surfaces of the surface cleaning target gear. If the magnetization range of the magnetization device completely covers the occupied ranges of all surfaces of the surface cleaning target gear, the surface cleaning target gear is directly magnetized by the magnetization device to obtain the surface cleaning target gear after surface magnetization, which is defined as the surface magnetized target gear. If there is any surface cleaning target gear whose surface occupies a range that cannot be completely covered by the magnetization range of the magnetization device, the surface of the corresponding surface cleaning target gear is calibrated as a type of surface cleaning target gear surface; Acquire a laser scanning device, perform laser scanning on a target cleaning target gear based on the laser scanning device, construct a laser scanning model of the target cleaning target gear in combination with the component structure of the target gear, calibrate it as a target laser scanning model, and mark a class of surface cleaning target gear surfaces in the target laser scanning model; In the target laser scanning model, an ant colony algorithm is introduced, and a surface edge point is determined on the surface of a type of surface-cleaning target gear in the target laser scanning model and calibrated as the path starting point; The ant colony algorithm is set, wherein the ant colony algorithm is set to adjust the occupied range of the path in the ant colony algorithm to the magnetization range of the magnetization device, and the set ant colony algorithm is applied to a surface of a type of surface-cleaning target gear of the target laser scanning model, and all paths that can completely magnetize the surface of a type of surface-cleaning target gear of the target laser scanning model starting from the starting point of the path are obtained, and are calibrated as magnetization paths to be analyzed; Among all the magnetization paths to be analyzed, the magnetization path to be analyzed with the shortest path length is selected and calibrated as the target magnetization path. The magnetization device is controlled to perform surface magnetization treatment on the surface of a first-class surface-cleaning target gear based on the target magnetization path, and the magnetization device is controlled to perform direct magnetization treatment on the surface of the target clean target gear that is not a first-class surface-cleaning target gear surface, so as to obtain a surface magnetized target gear.

4. According to the gear stress defect detection method based on magnetic memory effect described in claim 1, It is characterized in that The magnetic memory scanning is performed on the surface magnetized target gear by the magnetic memory scanner, and the scanning signal data obtained by the magnetic memory scanning is processed, specifically: Acquire a magnetic memory scanner, wherein the magnetic memory scanner is integrated with a target magnetic sensor, the magnetic sensor can perform magnetic memory scanning on the magnetized metal surface, and the magnetic memory scanner can perform data preprocessing on the scan data obtained after the magnetic memory scanning; By means of the magnetic memory scanner, a magnetic memory scan is performed on the surface of the magnetized target gear, and the scan data obtained after the magnetic memory scan is stored in the magnetic memory scanner and calibrated as magnetic memory scan data; Wherein, the magnetic memory scanning data is the surface magnetic field distribution data and surface magnetic field intensity data of the surface magnetized target gear; In the magnetic memory scanner, frequency analysis is performed on the magnetic memory scanning data to obtain the data frequency of the magnetic memory scanning data, and a data standard frequency range of the magnetic memory scanning data is preset; If the data frequency of the magnetic memory scanning data is not completely maintained within the data standard frequency range, a sliding average filtering algorithm is introduced to filter the magnetic memory scanning data so that the data frequency of the magnetic memory scanning data is completely maintained within the data standard frequency range to obtain qualified magnetic memory scanning data, and the qualified magnetic memory scanning data is signal converted to obtain a qualified magnetic memory scanning electrical signal; A signal analysis device is introduced and integrated with a magnetic memory scanner. The magnetic memory scanner integrated with the signal analysis device performs signal analysis on qualified magnetic memory scanning electrical signals to generate gear surface magnetic domain distribution characteristic data, gear surface magnetic domain boundary characteristic data, and gear surface magnetic field signal intensity characteristic data of the surface magnetized target gear. The gear surface magnetic domain distribution characteristic data, gear surface magnetic domain boundary characteristic data and gear surface magnetic field signal intensity characteristic data of the surface magnetized target gear are collectively referred to as the surface magnetized target gear magnetic memory data.

5. According to the gear stress defect detection method based on magnetic memory effect described in claim 1, It is characterized in that The method of performing data analysis on the magnetic memory data of the surface magnetized target gear, determining the stress abnormality area of ​​the surface magnetized target gear based on the analysis result, and performing abnormal correction on the stress abnormality area of ​​the surface magnetized target gear is specifically as follows: Constructing a two-dimensional data representation space, and importing the magnetic memory data of the surface magnetized target gear into the two-dimensional data representation space, generating a two-dimensional visualization pattern of the magnetic memory of the surface magnetized target gear, and calibrating it as a target pattern; The target pattern is a characteristic curve, and the characteristic curve analysis is performed on the target pattern to calculate the area sizes of all closed areas on the target pattern, wherein different closed areas represent different areas on the surface magnetized target gear, and the surface magnetic field mutation sizes of different areas on the surface magnetized target gear are calculated based on the area sizes of the closed areas; Based on the big data network, the stress concentration degree-surface magnetic field mutation size comparison spectrum is retrieved and calibrated as the target comparison spectrum. The surface magnetic field mutation sizes of different areas on the surface magnetized target gear are imported into the target comparison spectrum, and the stress concentration degree of different areas on the surface magnetized target gear is calculated. The maximum stress concentration degree is preset, and the area on the surface magnetized target gear where the stress concentration degree is greater than the maximum stress concentration degree is marked as the stress abnormal area of ​​the surface magnetized target gear; A stress anomaly root cause analysis is performed on the stress anomaly area of ​​the surface magnetized target gear, and based on the stress anomaly root cause analysis result, an abnormal correction is performed on the stress anomaly area of ​​the surface magnetized target gear.

6. According to the gear stress defect detection method based on magnetic memory effect described in claim 5, It is characterized in that The stress abnormality root cause analysis is performed on the stress abnormality area of ​​the surface magnetized target gear, and based on the stress abnormality root cause analysis result, the stress abnormality area of ​​the surface magnetized target gear is corrected abnormally, specifically: Obtain standard design gear parameters of the stress abnormality region of the surface magnetized target gear through the instruction manual of the target gear, and construct a three-dimensional model of the stress abnormality region of the surface magnetized target gear through a three-dimensional modeling method, and obtain actual gear parameters of the stress abnormality region of the surface magnetized target gear based on the three-dimensional model of the stress abnormality region of the surface magnetized target gear; If the actual gear parameters of the surface magnetized target gear in the stress abnormality region are less than the standard design gear parameters, the surface magnetized target gear is scrapped; If, in the surface magnetized target gear, there is no actual gear parameter less than the standard design gear parameter in the stress abnormal area, but there is an actual gear parameter greater than the standard design gear parameter, then the stress abnormal area of ​​the corresponding surface magnetized target gear where the actual gear parameter is greater than the standard design gear parameter is marked as the design abnormal area, and the design gear area repair solution of the design abnormal area is retrieved in the big data network and output; If the surface magnetized target gear still has a stress abnormality region after the design gear region repair plan of the design abnormality region is output, lubrication treatment is performed on the stress abnormality region of the surface magnetized target gear, and it is determined whether the surface magnetized target gear still has a stress abnormality region after the lubrication treatment; If so, the surface magnetized target gear is scrapped; if not, the surface magnetized target gear is calibrated as a stress-free target gear.

7. A gear stress defect detection system based on magnetic memory effect, It is characterized in that The gear stress defect detection system includes a memory and a processor, wherein the memory stores a gear stress defect detection method program, and when the gear stress defect detection method program is executed by the processor, the gear stress defect detection method steps according to any one of claims 1 to 6 are implemented: A magnetic sensor is selected to act on a target gear for stress defect detection, and the target gear is cleaned to obtain a surface-cleaned target gear; Laser scanning technology and ant colony algorithm are introduced, and the surface of the clean target gear is magnetized by magnetization equipment to obtain the surface magnetized target gear; Performing magnetic memory scanning on the surface magnetized target gear by means of a magnetic memory scanner, and processing scanning signal data obtained by the magnetic memory scanning; The magnetic memory data of the surface magnetized target gear is analyzed, and based on the analysis result, the stress abnormality area of ​​the surface magnetized target gear is determined, and the abnormality correction is performed on the stress abnormality area of ​​the surface magnetized target gear.

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