Strong magnetic rotor segmented integral magnetizing equipment and magnetizing method thereof

Abstract

The invention discloses a strong magnetic rotor segmented integral magnetizing device and a magnetizing method thereof, and relates to the technical field of strong magnetic rotors, the method can effectively optimize a magnetizing sequence through analysis based on a sensitivity coefficient Mgxs and current response time Dysc in combination with a sorting prediction model, and the magnetizing efficiency is improved. And the situation that the current fluctuation is too large or the load is uneven in the magnetizing process is further avoided, so that the magnetizing efficiency is improved, and energy waste is reduced. In the magnetizing process, the reverse magnetic field phenomenon possibly caused in the magnetizing switching process is recognized in time by monitoring the current difference between the adjacent magnetic sections and the change speed of the current difference in real time. By further optimizing the magnetizing sequence through the judgment coefficient Pdxs, mutual interference between front and rear magnetic sections and generation of a reverse magnetic field caused by improper arrangement of the sequence are reduced, so that uniform distribution of the magnetic field and stability of rotor performance are ensured.

Description

Technical Field

[0001] The invention relates to the technical field of strong magnetic rotors, in particular to a strong magnetic rotor segmented integral magnetizing device and a magnetizing method thereof. Background Art

[0002] As a key component of high-performance equipment such as motors, generators and magnetic levitation systems, the magnetic field strength and stability of the strong magnetic rotor directly affect the operating efficiency and reliability of the equipment. The magnetization process of the strong magnetic rotor usually needs to be carried out on multiple magnetic segments to ensure that the magnetic field of each magnetic segment is uniform and accurate, avoiding problems such as magnetic field degradation and performance degradation caused by uneven or improper magnetization. In order to improve the magnetization efficiency and system stability, the magnetization process of the strong magnetic rotor often requires the reasonable design of the magnetization sequence and magnetization current to reduce interference and overload between adjacent magnetic segments, thereby improving the overall magnetization effect.

[0003] At present, the existing methods for the magnetization process of strong magnetic rotors still have the following shortcomings: Blindness of the magnetization sequence: Traditional magnetization methods usually adopt a fixed magnetization sequence or sort based on experience, but due to the complexity and diversity of the rotor structure, this method ignores the difference in sensitivity of different magnetic segments to the magnetization current. And there is a lack of dynamic adjustment mechanism. In the existing technology, the magnetization sequence is often statically set, and the magnetization sequence between magnetic segments cannot be monitored and adjusted in real time. This makes it difficult to make timely adjustments in the actual magnetization process when the magnetization current changes too fast, too slow, or the magnetization switching is inappropriate, which may lead to problems such as reverse magnetic field and overload.

[0004] The shortcomings of the existing methods directly lead to some unpredictable abnormal phenomena in the magnetization process of the strong magnetic rotor, including but not limited to: the generation of reverse magnetic field: due to improper switching of the magnetization current, the current may be reversed too quickly, thereby generating a reverse magnetic field in the previous magnetic segment, affecting the magnetization effect of the subsequent magnetic segment. The generation of the reverse magnetic field not only affects the uniform distribution of the magnetic field, but may also lead to incomplete magnetization of the magnetic segment or unstable magnetic field strength, reducing the operating efficiency of the equipment. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a strong magnetic rotor segmented integral magnetizing device and a magnetizing method thereof, which solves the problems in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A method for segmented overall magnetization of a strong magnetic rotor, comprising the following steps: S1. Pre-acquire geometric data of the surface of the strong magnetic rotor, and divide the strong magnetic rotor into several groups of magnetic segments according to the geometric data, and perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data; S2. After feature extraction of relevant operation data, the sensitivity of each magnetic segment to the magnetization current is analyzed to generate a sensitivity coefficient Mgxs, and the magnetization load borne by each magnetic segment during the magnetization process is analyzed to generate a current response time Dysc. Combined with the trained sorting prediction model, the output sorting index Pxzb is fitted, and based on the value of the sorting index Pxzb, several groups of magnetic segments are magnetized and sorted in turn to obtain an initial sorting list; S3. Based on the initial sorting list, magnetization test operations are performed on several groups of magnetic segments in sequence. During the magnetization test, the current difference between magnetic segments in adjacent magnetization sequences is monitored in real time when the magnetic segments are magnetized and switched, so as to obtain relevant test data. Based on the test data, it is analyzed whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment when the magnetic segment is magnetized and switched, so as to obtain the determination coefficient Pdxs. S4. Based on the determination coefficient Pdxs, determine whether it is necessary to re-sort the magnetization of the several groups of magnetic segments. If necessary, generate an optimized sorting list, and perform magnetization operations on the several groups of magnetic segments based on the optimized sorting list.

[0007] Preferably, the specific steps of S1 include: S11, obtaining geometric data of the surface of the strong magnetic rotor in advance from the CAD file provided by the supplier, wherein the geometric data includes the radius of each point on the cross section of the strong magnetic rotor; at the same time, evenly dividing the strong magnetic rotor into a plurality of groups of regions, and analyzing the geometric states of the rotor surfaces in the plurality of groups of regions in combination with the geometric data, obtaining the flatness by calculation, and marking the plurality of groups of regions as different magnetic segments respectively according to the difference in the flatness values ​​of the rotor surfaces in the respective regions, and marking the regions with the same flatness values ​​as the same magnetic segments; S12, based on the groups of magnetic segments obtained in S11, magnetizing the groups of magnetic segments respectively to obtain relevant operation data, wherein the relevant operation data includes the magnetizing current of each magnetic segment in each monitoring period , strong magnetic field , the starting current of each magnetic segment during magnetization operation And the final current .

[0008] Preferably, the specific steps of S2 include: S21, extracting features from relevant operation data to obtain the magnetizing current of each magnetic segment in each monitoring period and magnetic field strength , based on the magnetizing current of each magnetic segment during each monitoring period and magnetic field strength , analyze the sensitivity of each magnetic segment to the magnetizing current to generate a sensitivity coefficient Mgxs, which is obtained by the following formula: ; In the formula, Indicates The sensitivity coefficient of the magnetic segment, N represents the monitoring period, i=1, 2, ..., N, Indicates The average magnetizing current during the monitoring period, It represents the average magnetizing current during the monitoring period. Indicates The average magnetic field strength during the monitoring period, Indicates the average magnetic field strength during the monitoring period.

[0009] Preferably, the specific step S2 also includes: S22, extracting features from relevant operation data to obtain the starting current of each magnetic segment during the magnetization operation And the final current , based on the starting current of each magnetic segment during magnetization operation And the final current , analyze the magnetization load of each magnetic segment during the magnetization process, analyze and calculate to obtain the current response time Dysc, and the current response time Dysc is obtained by the following formula: ; In the formula, Indicates The final current of the magnetic segment, Indicates The current response time of the magnetic segment, Indicates The starting current of the magnetic segment, Indicates the rate of change of current.

[0010] Preferably, the specific step S2 also includes: S23. Using deep learning technology and combining relevant operation data, a ranking prediction model is constructed. After training and dimensionless processing, a ranking index Pxzb is fitted and output. The ranking index Pxzb is obtained by the following formula: ; In the formula, Indicates Segment sorting index, Indicates The sensitivity coefficient of the magnetic segment, represents the maximum value of the sensitivity coefficient among all magnetic segments, represents the maximum value of the current response time in all magnetic segments, Indicates The current response time of the magnetic segment, and All represent weight values, among which, and The specific value is set by the user according to the situation.

[0011] Preferably, the specific step S2 also includes: S24. According to the method of obtaining the sorting index Pxzb in S23, the sorting indexes Pxzb of several groups of magnetic segments are obtained in sequence, and the sorting indexes Pxzb of several groups of magnetic segments are sorted in ascending order according to the numerical values ​​to obtain an initial sorting list, and the initial sorting list is input into step S3.

[0012] Preferably, the specific steps of S3 include: S31, receiving the initial sorting list in step S24, and according to the initial sorting list, magnetizing the strong magnetic rotor to test each magnetic segment in the order of the initial sorting list, and in the process of the magnetizing test, using several groups of monitoring instruments to monitor in real time the current difference between the magnetic segments of adjacent magnetizing sequences in the process of magnetizing and switching the magnetic segments, so as to obtain relevant test data, wherein the relevant test data includes the current value I of the magnetic segments of adjacent magnetic sequences when magnetizing and switching, and the current change speed of the magnetic segments of adjacent magnetic sequences when magnetizing and switching when testing several groups of magnetic segments according to the magnetizing order in the initial sorting list. .

[0013] Preferably, the specific step S3 also includes: S32. According to the relevant test data, when the magnetic segments are switched, whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment is analyzed, and after dimensionless processing, the determination coefficient Pdxs is obtained. The determination coefficient Pdxs is obtained by the following formula: ; In the formula, and Indicates the current value of adjacent magnetic segments during magnetization switching. Indicates the current change speed of adjacent magnetic segments during magnetization switching. and All represent weight values, among which, and The specific value is set by the user according to the situation.

[0014] Preferably, the specific steps of S4 include: S41, presetting an evaluation threshold K, and comparing and analyzing the evaluation threshold K with the determination coefficient Pdxs to determine whether it is necessary to re-sequence the magnetization of several groups of magnetic segments. The specific determination steps are as follows: S411. If the determination coefficient Pdxs exceeds the evaluation threshold value K, it indicates that there is a reverse magnetic field caused by a problem with the magnetization sequence, and it is determined that the magnetization sequence between the corresponding magnetic segments needs to be re-sorted. At this time, the initial sorting list obtained in step S24 is optimized. The specific optimization content is: on the basis of the initial sorting list, the magnetic segments of adjacent magnetic sequences are sorted separately, wherein the magnetic segments of adjacent magnetic sequences include the currently monitored magnetic segment and the previous magnetic segment; S4111, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and when the current magnetic segment is at the last position in the initial sort list, the order of the previous magnetic segment is advanced by one position; S4112, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and the previous magnetic segment is at the first place in the initial sorting list, the order of the current magnetic segment is moved back one place; S4113, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and the previous magnetic segment is not located at the first position in the initial sorting list, and the current magnetic segment is not located at the last position in the initial sorting list, then the order of the current magnetic segment is moved back by one position or the order of the previous magnetic segment is moved forward by one position; S4114, if the starting current of the current magnetic segment <Starting current of the previous magnetic segment , at this time, the order of the previous magnetic segment is moved back three places; S412. If the determination coefficient Pdxs does not exceed the evaluation threshold K, it indicates that there is no reverse magnetic field caused by the problem of magnetization sequence, and it is determined that there is no need to re-sort the magnetization sequence between the corresponding magnetic segments, and the initial sorting list obtained in step S24 is maintained.

[0015] A strong magnetic rotor segmented integral magnetization device, comprising a collection module, a preliminary sorting module, a preliminary sorting fault analysis module and a sorting optimization module; The acquisition module is used to obtain geometric data of the surface of the strong magnetic rotor in advance, and divide the strong magnetic rotor into several groups of magnetic segments according to the geometric data, and perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data; The preliminary sorting module is used to analyze the sensitivity of each magnetic segment to the magnetizing current after feature extraction of relevant operation data to generate a sensitivity coefficient Mgxs, and analyze the magnetizing load borne by each magnetic segment during the magnetizing process to generate a current response time Dysc, and fit the output sorting index Pxzb in combination with the trained sorting prediction model. Based on the value of the sorting index Pxzb, several groups of magnetic segments are magnetized and sorted in turn to obtain an initial sorting list; The preliminary sorting fault analysis module is used to perform magnetization test operations on a plurality of groups of magnetic segments in sequence based on the initial sorting list, and in the process of magnetization test, monitor in real time the current difference between magnetic segments in adjacent magnetization sequences when the magnetic segments are magnetized and switched, so as to obtain relevant test data, and analyze, based on the test data, whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment when the magnetic segments are magnetized and switched, so as to obtain the determination coefficient Pdxs; The sorting optimization module is used to determine whether it is necessary to re-sort the magnetization of several groups of magnetic segments based on the determination coefficient Pdxs. If necessary, an optimized sorting list is generated, and magnetization operations are performed on several groups of magnetic segments based on the optimized sorting list.

[0016] The present invention provides a strong magnetic rotor segmented integral magnetization device and a magnetization method thereof, which have the following beneficial effects: This method can effectively optimize the magnetization sequence by combining the sorting prediction model based on the analysis of the sensitivity coefficient Mgxs and the current response time Dysc, further avoiding the situation of excessive current fluctuation or uneven load during the magnetization process, thereby improving the magnetization efficiency and reducing energy waste. During the magnetization process, by real-time monitoring the current difference and its change rate between adjacent magnetic segments, the reverse magnetic field phenomenon that may be caused during the magnetization switching process can be timely identified. The further optimization of the magnetization sequence by the determination coefficient Pdxs reduces the mutual interference between the front and rear magnetic segments and the generation of reverse magnetic fields caused by improper sequence arrangement, thereby ensuring the uniform distribution of the magnetic field and the stability of the rotor performance. Reduce the risk of equipment damage and extend the life of the equipment: A reasonable magnetization sequence can avoid problems such as overheating and magnetic field attenuation that may occur during the magnetization process, reduce the damage caused by uneven load of the magnetization current on the magnetic segment, and reduce the damage to the rotor structure caused by excessive temperature or excessive current fluctuations. Through this method of optimizing the magnetization sequence, not only the safety of the magnetization operation is improved, but also the service life of the rotor and the entire equipment is extended. Real-time feedback and adjustment to enhance the flexibility of the magnetization process: This method can flexibly adjust the magnetization sequence and timely adjust the magnetization strategy by real-time monitoring the current changes and magnetic field responses during magnetization switching during the magnetization test. If unstable or unsatisfactory magnetization effects (such as reverse magnetic fields) are found during the magnetization process, the magnetization sequence can be quickly identified and optimized by comparing the determination coefficient Pdxs with the evaluation threshold K, thereby enhancing the flexibility and adaptability of the magnetization process and improving the accuracy of the entire magnetization operation.

[0017] (2) In steps S21 and S22, by monitoring and analyzing the magnetization current and magnetic field strength in detail, the sensitivity of each magnetic segment to the magnetization current and the magnetization load can be accurately quantified. By calculating the sensitivity coefficient and current response time, more accurate magnetization parameters can be provided for each magnetic segment. Especially in complex magnetization operations, this accurate analysis helps to avoid over-magnetization or under-magnetization, ensure that the current and magnetic field strength of each magnetic segment during the magnetization process are within the appropriate range, and improve the magnetization quality and stability. Based on the analysis results of the sensitivity coefficient, the magnetic segments that are more sensitive to the magnetization current can be identified, so that these magnetic segments can be magnetized first, further reducing the reverse magnetic field or energy waste caused by uneven magnetization or too fast current changes.

[0018] (3) Step S24 further realizes the automatic optimization of the magnetization sequence by sorting each magnetic segment according to the sorting index. This automated sorting method can eliminate the influence of human subjective factors on the magnetization sequence, thereby ensuring a more efficient and stable magnetization operation. In addition, this method can effectively improve the time efficiency of the entire magnetization process and reduce the complexity of scheduling and manual intervention. Improve the quality and stability of magnetization: The initial sorting list obtained is based on accurate sorting indicators, which helps to optimize the current difference between magnetic segments during the magnetization process and reduce the influence of current fluctuations on the magnetization effect, thereby avoiding magnetic field instability or reverse magnetic field caused by improper magnetization sequence. Through this optimization process, not only can the current control accuracy during the magnetization process be improved, but also the magnetization quality and equipment operation stability can be effectively improved.

[0019] (4) Through the analysis based on the test data in step S32, it can be accurately determined whether the magnetization operation of the next magnetic segment will affect the previous magnetic segment during the magnetization switch, thereby causing a reverse magnetic field. This analysis can provide a scientific basis for adjusting the magnetization sequence, avoid magnetic field instability or reverse magnetic field phenomena caused by improper magnetization sequence, and improve the accuracy and safety of the magnetization operation. Dynamically optimize the magnetization sequence to reduce the reverse magnetic field: Based on the calculation of the determination coefficient, the magnetization sequence that may cause a reverse magnetic field during the magnetization process can be accurately identified, and the magnetization sequence can be adjusted in time. If the test results show that certain magnetization sequences are prone to cause reverse magnetic fields, corresponding measures can be taken to optimize them, thereby avoiding the influence of unstable magnetic fields and improving the safety of the magnetization process and the operating stability of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic flow chart of a method for segmented overall magnetization of a strong magnetic rotor according to the present invention; Figure 2 This is a block diagram of a strong magnetic rotor segmented integral magnetization device of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Example 1 See also Figure 1 The present invention provides a method for magnetizing a strong magnetic rotor segmented as a whole, comprising the following steps: S1. Pre-acquire geometric data of the surface of the strong magnetic rotor, and divide the strong magnetic rotor into several groups of magnetic segments according to the geometric data, and perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data; S2. After feature extraction of relevant operation data, the sensitivity of each magnetic segment to the magnetization current is analyzed to generate a sensitivity coefficient Mgxs, and the magnetization load borne by each magnetic segment during the magnetization process is analyzed to generate a current response time Dysc. Combined with the trained sorting prediction model, the output sorting index Pxzb is fitted, and based on the value of the sorting index Pxzb, several groups of magnetic segments are magnetized and sorted in turn to obtain an initial sorting list; S3. Based on the initial sorting list, magnetization test operations are performed on several groups of magnetic segments in sequence. During the magnetization test, the current difference between magnetic segments in adjacent magnetization sequences is monitored in real time when the magnetic segments are magnetized and switched, so as to obtain relevant test data. Based on the test data, it is analyzed whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment when the magnetic segment is magnetized and switched, so as to obtain the determination coefficient Pdxs. S4. Based on the determination coefficient Pdxs, determine whether it is necessary to re-sort the magnetization of the several groups of magnetic segments. If necessary, generate an optimized sorting list, and perform magnetization operations on the several groups of magnetic segments based on the optimized sorting list.

[0023] In this embodiment, by pre-acquiring and analyzing the rotor geometry data, each magnetic segment can be divided, and the magnetization sequence can be performed according to the characteristics of each magnetic segment (such as current sensitivity and load conditions), ensuring that the change of the magnetization current meets the needs of each magnetic segment. This optimized sequence can reduce repeated adjustments during the magnetization process, thereby reducing energy waste, improving magnetization efficiency, and shortening the magnetization time. Through a detailed analysis of the sensitivity of each magnetic segment, generating a sensitivity coefficient and monitoring the current difference during the magnetization process, the problem of magnetic field unevenness can be effectively avoided, and the reverse magnetic field or magnetic field attenuation caused by improper magnetization sequence can be avoided, thereby ensuring that the magnetization process of each magnetic segment is more independent and accurate, and the uniformity and stability of the overall magnetic field are guaranteed. When arranging the magnetization sequence, by analyzing the change of the magnetization current and monitoring the current difference in real time, it can be determined whether a reverse magnetic field is generated due to a sequence problem. Based on this, the magnetization sequence can be dynamically adjusted to avoid the generation of unnecessary reverse magnetic fields and ensure that the magnetic field is always stable during the entire magnetization process. By comprehensively analyzing the magnetization load of each magnetic segment and its current response time, and optimizing the magnetization sequence in combination with the sorting model, the resonance effect generated during the magnetization process of the magnetic segment can be effectively avoided. The resonance phenomenon often leads to increased rotor vibration, which in turn affects the stability of the equipment. The present invention further reduces this instability by reasonably arranging the magnetization sequence, which helps to improve the long-term stable operation of the equipment. By obtaining the determination coefficient Pdxs, it is possible to evaluate in real time whether the current magnetization sequence leads to the generation of a reverse magnetic field. If an abnormal situation caused by a sequence problem is found, the system can automatically generate an optimized sorting list and adjust the magnetization sequence. This dynamic optimization mechanism ensures that the magnetization process is always in a relatively good state, avoiding the degradation of equipment performance caused by magnetization sequence problems.

[0024] Example 2 Please refer to Figure 1 , specifically: S1 specific steps include: S11, obtaining geometric data of the surface of the strong magnetic rotor in advance from the CAD file provided by the supplier, wherein the geometric data includes the radius of each point on the cross section of the strong magnetic rotor; at the same time, evenly dividing the strong magnetic rotor into a plurality of groups of regions, and analyzing the geometric states of the rotor surfaces in the plurality of groups of regions in combination with the geometric data, obtaining the flatness by calculation, and marking the plurality of groups of regions as different magnetic segments respectively according to the difference in the flatness values ​​of the rotor surfaces in the respective regions, and marking the regions with the same flatness values ​​as the same magnetic segments; The flatness is obtained by the ratio between the radii at each point on the cross section of the strong magnetic rotor; it is a dimensionless parameter used to describe the flatness of the rotor shape or structure.

[0025] S12, based on the groups of magnetic segments obtained in S11, magnetizing the groups of magnetic segments respectively to obtain relevant operation data, wherein the relevant operation data includes the magnetizing current of each magnetic segment in each monitoring period , strong magnetic field , the starting current of each magnetic segment during magnetization operation And the final current .

[0026] In this embodiment, by obtaining the geometric data of the surface of the strong magnetic rotor in advance and combining the calculation of the flatness of the rotor surface, the rotor can be accurately divided into several magnetic segments. By performing a detailed analysis of each magnetic segment and reasonably dividing the magnetic segments according to the flatness difference of each region, a more accurate regional division basis can be provided for the subsequent magnetization operation, avoiding the division error caused by the previous manual division method, so that the magnetization operation of each magnetic segment is more targeted and accurate. By using the geometric data in the CAD file provided by the supplier, not only the accuracy and reliability of the data are guaranteed, but also the geometric characteristics of the rotor can be quickly and comprehensively obtained. The comprehensive analysis of the geometric state of the rotor surface (such as radius and flatness, etc.) helps to have a deeper understanding of the physical characteristics that the rotor may encounter during the magnetization process, and then formulate a relatively optimal strategy for the magnetization operation of each magnetic segment. Compared with traditional manual measurement and adjustment, this method not only saves a lot of time and energy, but also further improves the accuracy of the operation. By marking different areas as different magnetic segments according to the difference in flatness, the needs of different magnetic segments during the magnetization process can be accurately identified. Flatness is an important parameter of the rotor geometry, and its difference can directly affect the magnetization efficiency and magnetic field distribution.

[0027] Example 3 Please refer to Figure 1 , specifically: S2 specific steps include: S21, extracting features from relevant operation data to obtain the magnetizing current of each magnetic segment in each monitoring period and magnetic field strength , based on the magnetizing current of each magnetic segment during each monitoring period and magnetic field strength , analyze the sensitivity of each magnetic segment to the magnetizing current to generate a sensitivity coefficient Mgxs, which is obtained by the following formula: ; In the formula, Indicates The sensitivity coefficient of the magnetic segment, N represents the monitoring period, i=1, 2, ..., N, Indicates The average magnetizing current during the monitoring period, It represents the average magnetizing current during the monitoring period. Indicates The average magnetic field strength during the monitoring period, Indicates the average magnetic field strength during the monitoring period.

[0028] The above magnetizing current is monitored and obtained through a current sensor; The magnetic field strength can be monitored by a Hall sensor.

[0029] The specific steps of S2 also include: S22, extracting features from relevant operation data to obtain the starting current of each magnetic segment during the magnetization operation And the final current , based on the starting current of each magnetic segment during magnetization operation And the final current , analyze the magnetization load of each magnetic segment during the magnetization process, analyze and calculate to obtain the current response time Dysc, and the current response time Dysc is obtained by the following formula: ; In the formula, Indicates The final current of the magnetic segment, Indicates The current response time of the magnetic segment, Indicates The starting current of the magnetic segment, Indicates the rate of change of current.

[0030] In this embodiment, the magnetization sensitivity of each magnetic segment is accurately analyzed: by extracting the characteristics of the magnetization current and magnetic field strength, based on the current and magnetic field data of each magnetic segment during the monitoring period, the sensitivity coefficient Mgxs is generated, which can accurately reflect the sensitivity of each magnetic segment to the magnetization current. This analysis not only helps to identify which magnetic segments are more sensitive to changes in the magnetization current, but also provides a basis for the subsequent optimization of the magnetization sequence and the precise control of the magnetization current, ensuring that the current regulation of each magnetic segment during the magnetization process is more accurate, thereby improving the overall magnetization efficiency and stability. Optimize magnetization load management to avoid overload: by analyzing the starting current and final current of each magnetic segment and calculating the current response time Dysc, the load of each magnetic segment during the magnetization process can be accurately evaluated. This analysis can help identify which magnetic segments are under excessive load during the magnetization process, thereby warning of possible overload. Based on these data, the magnetization operation parameters and sequence can be optimized, further reducing the risk of overheating or magnetic field instability due to excessive load in some magnetic segments, and extending the service life of the equipment. Improve the accuracy of magnetizing current control: By calculating the current response time Dysc and the rate of change of the magnetizing current, the change process of the magnetizing current can be monitored in real time, and the rate of change of the magnetizing current can be adjusted according to the current response time. This can not only improve the current regulation accuracy during the magnetizing process, but also avoid unnecessary current fluctuations during the magnetizing process, ensure the stability of the magnetizing operation, and prevent the reverse magnetic field or uneven magnetic field caused by current fluctuations. In summary, through the feature extraction and analysis of parameters such as the magnetizing current and magnetic field intensity, the starting current and the final current, and the current response time, the segmented overall magnetizing method of the strong magnetic rotor of the present invention can improve the accuracy of the magnetizing operation, optimize the magnetizing sequence, reduce the problem of uneven magnetizing load, effectively improve the magnetizing efficiency, reduce the risk of equipment failure, and realize intelligent regulation during the magnetizing process.

[0031] Example 4 Please refer to Figure 1 Specifically: S2 includes the following specific steps: S23. Using deep learning technology and combining relevant operation data, a ranking prediction model is constructed. After training and dimensionless processing, a ranking index Pxzb is fitted and output. The ranking index Pxzb is obtained by the following formula: ; In the formula, Indicates Segment sorting index, Indicates The sensitivity coefficient of the magnetic segment, represents the maximum value of the sensitivity coefficient among all magnetic segments, represents the maximum value of the current response time in all magnetic segments, Indicates The current response time of the magnetic segment, and All represent weight values, among which, , and The specific value is set by the user according to the situation.

[0032] The specific steps of S2 also include: S24. According to the method of obtaining the sorting index Pxzb in S23, the sorting indexes Pxzb of several groups of magnetic segments are obtained in sequence, and the sorting indexes Pxzb of several groups of magnetic segments are sorted in ascending order according to the numerical values ​​to obtain an initial sorting list, and the initial sorting list is input into step S3.

[0033] In this embodiment, accurate magnetization sequence prediction and optimization: by using deep learning technology, combined with magnetization operation data to build a sorting prediction model, the sorting index of each magnetic segment can be accurately predicted during the magnetization process. Through model training and dimensionless processing, the inaccuracy caused by manual intervention can be avoided, and the magnetization sequence of the magnetic segment can be effectively predicted based on the sensitivity coefficient and current response time. This method ensures the scientificity and systematicness of the magnetization sequence, avoids the unreasonable magnetization sequence caused by improper human operation, and thus improves the overall efficiency and stability of the magnetization operation. Comprehensive consideration of the balance between the sensitivity coefficient and the current response time: by comprehensively considering the sorting index of the sensitivity coefficient and the current response time, the influence of the two can be balanced. This method ensures that the sensitivity of the magnetic segment to the current change can be taken into account during the magnetization process, and the energy waste or overload risk in the magnetization process due to the excessive current response time can be avoided. By sorting the values ​​of the sorting index according to size, the order arrangement in the magnetization process can be optimized. This sorting method ensures the efficiency of the magnetization operation, avoids multiple adjustments and unnecessary current fluctuations, improves the reliability of the entire magnetization operation process, and reduces the probability of failure.

[0034] Example 5 Please refer to Figure 1 , specifically: S3 specific steps include: S31, receiving the initial sorting list in step S24, and according to the initial sorting list, magnetizing the strong magnetic rotor to test each magnetic segment in the order of the initial sorting list, and in the process of the magnetizing test, using several groups of monitoring instruments to monitor in real time the current difference between the magnetic segments of adjacent magnetizing sequences in the process of magnetizing and switching the magnetic segments, so as to obtain relevant test data, wherein the relevant test data includes the current value I of the magnetic segments of adjacent magnetic sequences when magnetizing and switching, and the current change speed of the magnetic segments of adjacent magnetic sequences when magnetizing and switching when testing several groups of magnetic segments according to the magnetizing order in the initial sorting list. .

[0035] The specific steps of S3 also include: S32. According to the relevant test data, when the magnetic segments are switched, whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment is analyzed, and after dimensionless processing, the determination coefficient Pdxs is obtained. The determination coefficient Pdxs is obtained by the following formula: ; In the formula, and Indicates the current value of adjacent magnetic segments during magnetization switching. Indicates the current change speed of adjacent magnetic segments during magnetization switching. and All represent weight values, among which, , and The specific value is set by the user according to the situation.

[0036] In this embodiment, real-time monitoring and current difference capture: through the real-time monitoring instrument introduced in step S31, the current difference between adjacent magnetic segments during the magnetization process is carefully tracked, and the current change can be accurately captured during the magnetization switching of the magnetic segments. This high-precision real-time monitoring can promptly detect current fluctuations or mutations, ensure the stability of the magnetization operation, and provide accurate data support for subsequent analysis of whether a reverse magnetic field will be generated. Monitoring of current change speed improves data accuracy: during the magnetization switching process, in addition to monitoring the current value, the current change speed is also recorded and analyzed in real time. This additional analysis dimension can further reveal the trend and speed of current fluctuations, which helps to evaluate the stability and sequence rationality of the magnetization operation. Monitoring and analysis of the current change speed can effectively avoid abnormalities in the magnetization process caused by excessively fast or unstable current fluctuations, thereby improving the controllability of the magnetization operation. Optimization judgment based on determination coefficient Pdxs: The determination coefficient obtained after dimensionless processing in step S32 provides a reliable quantitative basis for analyzing whether the magnetization switching leads to a reverse magnetic field. The determination coefficient combines the weight information of the current value and the current change rate, and can effectively identify which magnetization switching sequences will cause excessive current changes, thereby causing reverse changes or instability in the magnetic field. Through this coefficient, it is possible to accurately determine whether there is a problem with the magnetization sequence, avoiding subjective bias in human experience judgment.

[0037] Example 6 Please refer to Figure 1 , specifically: S4 specific steps include: S41, presetting an evaluation threshold K, and comparing and analyzing the evaluation threshold K with the determination coefficient Pdxs to determine whether it is necessary to re-sequence the magnetization of several groups of magnetic segments. The specific determination steps are as follows: Obtain multiple groups of determination coefficients Pdxs through continuous testing, and combine with statistical algorithms to obtain the average determination coefficient and the standard deviation of the determination coefficient. According to the average determination coefficient and the standard deviation of the determination coefficient, set the evaluation threshold K, K = average determination coefficient + k * standard deviation of the determination coefficient; where k represents a constant, usually with a value of 1-3, corresponding to different confidence levels, and the specific value is set by the user (according to actual conditions); S411. If the determination coefficient Pdxs exceeds the evaluation threshold value K, it indicates that there is a reverse magnetic field caused by a problem with the magnetization sequence, and it is determined that the magnetization sequence between the corresponding magnetic segments needs to be re-sorted. At this time, the initial sorting list obtained in step S24 is optimized. The specific optimization content is: on the basis of the initial sorting list, the magnetic segments of adjacent magnetic sequences are sorted separately, wherein the magnetic segments of adjacent magnetic sequences include the currently monitored magnetic segment and the previous magnetic segment; S4111, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and when the current magnetic segment is at the last position in the initial sort list, the order of the previous magnetic segment is advanced by one position; S4112, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and the previous magnetic segment is at the first place in the initial sorting list, the order of the current magnetic segment is moved back one place; S4113, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and the previous magnetic segment is not located at the first position in the initial sorting list, and the current magnetic segment is not located at the last position in the initial sorting list, then the order of the current magnetic segment is moved back by one position or the order of the previous magnetic segment is moved forward by one position; S4114, if the starting current of the current magnetic segment <Starting current of the previous magnetic segment , at this time, the order of the previous magnetic segment is moved back three places; S412. If the determination coefficient Pdxs does not exceed the evaluation threshold K, it indicates that there is no reverse magnetic field caused by the problem of magnetization sequence, and it is determined that there is no need to re-sort the magnetization sequence between the corresponding magnetic segments, and the initial sorting list obtained in step S24 is maintained.

[0038] In this embodiment, intelligent sorting optimization is used to avoid reverse magnetic field: by setting the evaluation threshold and comparing and analyzing with the determination coefficient, it is possible to accurately determine whether the reverse magnetic field occurs due to problems in the magnetization sequence. When the determination coefficient exceeds the evaluation threshold, the system automatically identifies potential problems in the magnetization sequence and performs intelligent optimization. This automated optimization process can effectively avoid the reverse magnetic field phenomenon caused by improper magnetization sequence, thereby ensuring the safety and stability of the rotor magnetization operation. Flexible magnetization sequence adjustment mechanism: when re-sorting the magnetization sequence, the system adopts flexible adjustment methods according to different situations, such as comparing the starting current of the current magnetic segment and the previous magnetic segment to determine the direction of the sequence adjustment (forward or backward). This flexible sorting optimization mechanism ensures that the magnetization operation can be dynamically adjusted according to real-time monitoring data, thereby avoiding magnetic field instability or equipment damage caused by unreasonable magnetization sequence as much as possible. Detailed magnetization sorting strategy to ensure stable current: specific sorting rules, such as comparing and adjusting the starting current of the current magnetic segment and the previous magnetic segment, can more accurately regulate the magnetization sequence and avoid current mutations or unstable magnetization processes. Through sequencing adjustments under different circumstances, the system effectively controls current changes during the magnetization process, avoids potential problems caused by current imbalance, and improves magnetization efficiency and equipment operation reliability.

[0039] Example 7 Please refer to Figure 2 ,Specifically: A strong magnetic rotor segmented overall magnetization device, including a collection module, a preliminary sorting module, a preliminary sorting fault analysis module and a sorting optimization module; The acquisition module is used to obtain geometric data of the surface of the strong magnetic rotor in advance, and divide the strong magnetic rotor into several groups of magnetic segments according to the geometric data, and perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data; The preliminary sorting module is used to analyze the sensitivity of each magnetic segment to the magnetizing current after feature extraction of relevant operation data to generate a sensitivity coefficient Mgxs, and analyze the magnetizing load borne by each magnetic segment during the magnetizing process to generate a current response time Dysc, and fit the output sorting index Pxzb in combination with the trained sorting prediction model. Based on the value of the sorting index Pxzb, several groups of magnetic segments are magnetized and sorted in turn to obtain an initial sorting list; The preliminary sorting fault analysis module is used to perform magnetization test operations on a plurality of groups of magnetic segments in sequence based on the initial sorting list, and in the process of magnetization test, monitor in real time the current difference between magnetic segments in adjacent magnetization sequences when the magnetic segments are magnetized and switched, so as to obtain relevant test data, and analyze, based on the test data, whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment when the magnetic segments are magnetized and switched, so as to obtain the determination coefficient Pdxs; The sorting optimization module is used to determine whether it is necessary to re-sort the magnetization of several groups of magnetic segments based on the determination coefficient Pdxs. If necessary, an optimized sorting list is generated, and magnetization operations are performed on several groups of magnetic segments based on the optimized sorting list.

[0040] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for segmented overall magnetization of a strong magnetic rotor, characterized in that: The following steps are involved: S1. Pre-acquire geometric data of the surface of the strong magnetic rotor, and divide the strong magnetic rotor into several groups of magnetic segments according to the geometric data, and perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data; S2. After feature extraction of relevant operation data, the sensitivity of each magnetic segment to the magnetization current is analyzed to generate a sensitivity coefficient Mgxs, and the magnetization load borne by each magnetic segment during the magnetization process is analyzed to generate a current response time Dysc. Combined with the trained sorting prediction model, the output sorting index Pxzb is fitted, and based on the value of the sorting index Pxzb, several groups of magnetic segments are magnetized and sorted in turn to obtain an initial sorting list; S3. Based on the initial sorting list, magnetization test operations are performed on several groups of magnetic segments in sequence. During the magnetization test, the current difference between magnetic segments in adjacent magnetization sequences is monitored in real time when the magnetic segments are magnetized and switched, so as to obtain relevant test data. Based on the test data, it is analyzed whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment when the magnetic segment is magnetized and switched, so as to obtain the determination coefficient Pdxs. S4. Based on the determination coefficient Pdxs, determine whether it is necessary to re-sort the magnetization of several groups of magnetic segments. If necessary, generate an optimized sorting list, and perform magnetization operations on several groups of magnetic segments based on the optimized sorting list.

2. A method for segmented integral magnetization of a strong magnetic rotor according to claim 1, characterized in that: The specific steps of S1 include: S11, obtaining geometric data of the surface of the strong magnetic rotor in advance from the CAD file provided by the supplier, wherein the geometric data includes the radius of each point on the cross section of the strong magnetic rotor; at the same time, evenly dividing the strong magnetic rotor into a plurality of groups of regions, and analyzing the geometric states of the rotor surfaces in the plurality of groups of regions in combination with the geometric data, obtaining the flatness by calculation, and marking the plurality of groups of regions as different magnetic segments respectively according to the difference in the flatness values ​​of the rotor surfaces in the respective regions, and marking the regions with the same flatness values ​​as the same magnetic segments; S12, based on the several groups of magnetic segments obtained in S11, magnetizing the several groups of magnetic segments respectively to obtain relevant operation data, wherein the relevant operation data includes the magnetizing current of each magnetic segment in each monitoring period , strong magnetic field , the starting current of each magnetic segment during magnetization operation And the final current .

3. A method for segmented integral magnetization of a strong magnetic rotor according to claim 2, characterized in that: The specific steps of S2 include: S21, extracting features from relevant operation data to obtain the magnetizing current of each magnetic segment in each monitoring period and magnetic field strength , based on the magnetizing current of each magnetic segment during each monitoring period and magnetic field strength , analyze the sensitivity of each magnetic segment to the magnetizing current to generate a sensitivity coefficient Mgxs, which is obtained by the following formula: ； In the formula, Indicates The sensitivity coefficient of the magnetic segment, N represents the monitoring period, i=1, 2, ..., N, Indicates The average magnetizing current during the monitoring period, It represents the average magnetizing current during the monitoring period. Indicates The average magnetic field strength during the monitoring period, Indicates the average magnetic field strength during the monitoring period.

4. A method for segmented integral magnetization of a strong magnetic rotor according to claim 3, characterized in that: The specific steps of S2 also include: S22, extracting features from relevant operation data to obtain the starting current of each magnetic segment during the magnetization operation And the final current , based on the starting current of each magnetic segment during magnetization operation And the final current , analyze the magnetization load of each magnetic segment during the magnetization process, analyze and calculate to obtain the current response time Dysc, and the current response time Dysc is obtained by the following formula: ； In the formula, Indicates The final current of the magnetic segment, Indicates The current response time of the magnetic segment, Indicates The starting current of the magnetic segment, Indicates the rate of change of current.

5. A method for segmented integral magnetization of a strong magnetic rotor according to claim 4, characterized in that: The specific steps of S2 also include: S23. Using deep learning technology and combining relevant operation data, a ranking prediction model is constructed. After training and dimensionless processing, a ranking index Pxzb is fitted and output. The ranking index Pxzb is obtained by the following formula: ； In the formula, Indicates Segment sorting index, Indicates The sensitivity coefficient of the magnetic segment, represents the maximum value of the sensitivity coefficient among all magnetic segments, represents the maximum value of the current response time in all magnetic segments, Indicates The current response time of the magnetic segment, and All represent weight values, among which, and The specific value is set by the user according to the situation.

6. A method for segmented integral magnetization of a strong magnetic rotor according to claim 5, characterized in that: The specific steps of S2 also include: S24. According to the method of obtaining the sorting index Pxzb in S23, the sorting indexes Pxzb of several groups of magnetic segments are obtained in sequence, and the sorting indexes Pxzb of several groups of magnetic segments are sorted in ascending order according to the numerical values ​​to obtain an initial sorting list, and the initial sorting list is input into step S3.

7. A method for segmented integral magnetization of a strong magnetic rotor according to claim 6, characterized in that: The specific steps of S3 include: S31, receiving the initial sorting list in step S24, and according to the initial sorting list, performing a magnetization test operation on each magnetic segment of the strong magnetic rotor in the order of the initial sorting list, and in the process of the magnetization test operation, using several groups of monitoring instruments to monitor in real time the current difference between the magnetic segments of adjacent magnetization sequences in the process of magnetizing and switching the magnetic segments, so as to obtain relevant test data, wherein the relevant test data includes the current values ​​of the magnetic segments of adjacent magnetic sequences obtained by real-time monitoring when testing several groups of magnetic segments according to the magnetization order in the initial sorting list, when performing magnetization switching. And the current change speed of the adjacent magnetic sequence magnetic segments during magnetization switching .

8. A method for segmented integral magnetization of a strong magnetic rotor according to claim 7, characterized in that: The specific steps of S3 also include: S32. According to the relevant test data, when the magnetic segments are switched, whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment is analyzed, and after dimensionless processing, the determination coefficient Pdxs is obtained. The determination coefficient Pdxs is obtained by the following formula: ； In the formula, and Indicates the current value of adjacent magnetic segments during magnetization switching. Indicates the current change speed of adjacent magnetic segments during magnetization switching. and All represent weight values, among which, and The specific value is set by the user according to the situation.

9. A method for segmented integral magnetization of a strong magnetic rotor according to claim 8, characterized in that: The specific steps of S4 include: S41, presetting an evaluation threshold K, and comparing and analyzing the evaluation threshold K with the determination coefficient Pdxs to determine whether it is necessary to re-sequence the magnetization of several groups of magnetic segments. The specific determination steps are as follows: S411. If the determination coefficient Pdxs exceeds the evaluation threshold value K, it indicates that there is a reverse magnetic field caused by a problem with the magnetization sequence, and it is determined that the magnetization sequence between the corresponding magnetic segments needs to be re-sorted. At this time, the initial sorting list obtained in step S24 is optimized. The specific optimization content is: on the basis of the initial sorting list, the magnetic segments of adjacent magnetic sequences are sorted separately, wherein the magnetic segments of adjacent magnetic sequences include the currently monitored magnetic segment and the previous magnetic segment; S4111, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and when the current magnetic segment is at the last position in the initial sort list, the order of the previous magnetic segment is advanced by one position; S4112, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and the previous magnetic segment is at the first place in the initial sorting list, the order of the current magnetic segment is moved back one place; S4113, if the starting current of the current magnetic segment ≥Starting current of the previous magnetic segment , and the previous magnetic segment is not located at the first position in the initial sorting list, and the current magnetic segment is not located at the last position in the initial sorting list, then the order of the current magnetic segment is moved back by one position or the order of the previous magnetic segment is moved forward by one position; S4114, if the starting current of the current magnetic segment <Starting current of the previous magnetic segment , at this time, the order of the previous magnetic segment is moved back three places; S412. If the determination coefficient Pdxs does not exceed the evaluation threshold K, it indicates that there is no reverse magnetic field caused by the problem of magnetization sequence, and it is determined that there is no need to re-sort the magnetization sequence between the corresponding magnetic segments, and the initial sorting list obtained in step S24 is maintained.

10. A strong magnetic rotor segmented overall magnetization device, used to implement a strong magnetic rotor segmented overall magnetization method as described in any one of claims 1 to 9, characterized in that: It includes a collection module, a preliminary sorting module, a preliminary sorting fault analysis module and a sorting optimization module; The acquisition module is used to obtain geometric data of the surface of the strong magnetic rotor in advance, and divide the strong magnetic rotor into several groups of magnetic segments according to the geometric data, and perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data; The preliminary sorting module is used to analyze the sensitivity of each magnetic segment to the magnetizing current after feature extraction of relevant operation data to generate a sensitivity coefficient Mgxs, and analyze the magnetizing load borne by each magnetic segment during the magnetizing process to generate a current response time Dysc, and fit the output sorting index Pxzb in combination with the trained sorting prediction model. Based on the value of the sorting index Pxzb, several groups of magnetic segments are magnetized and sorted in turn to obtain an initial sorting list; The preliminary sorting fault analysis module is used to perform magnetization test operations on a plurality of groups of magnetic segments in sequence based on the initial sorting list, and in the process of magnetization test, monitor in real time the current difference between magnetic segments in adjacent magnetization sequences when the magnetic segments are magnetized and switched, so as to obtain relevant test data, and analyze, based on the test data, whether the magnetization process of the next magnetic segment will affect the reverse magnetic field of the previous magnetic segment when the magnetic segments are magnetized and switched, so as to obtain the determination coefficient Pdxs; The sorting optimization module is used to determine whether it is necessary to re-sort the magnetization of several groups of magnetic segments based on the determination coefficient Pdxs. If necessary, an optimized sorting list is generated, and magnetization operations are performed on several groups of magnetic segments based on the optimized sorting list.

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