A strong magnetic rotor segmented integral magnetization device and its magnetization method

Abstract

The present invention discloses a segmented integral magnetization device for a high-strength magnetic rotor and a magnetization method thereof, which relates to the technical field of high-strength magnetic rotors. Through the analysis based on the sensitivity coefficient Mgxs and the current response time Dysc, combined with the sorting prediction model, this method can effectively optimize the magnetization sequence, further avoid 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 between adjacent magnetic segments and its change speed, the reverse magnetic field phenomenon that may occur during the magnetization switching process can be identified in a timely manner. Through the further optimization of the magnetization sequence by the determination coefficient Pdxs, the mutual interference between the front and rear magnetic segments and the generation of reverse magnetic field caused by improper sequence arrangement are reduced, thereby ensuring the uniform distribution of the magnetic field and the stability of the rotor performance.

Description

Technical Field

[0001] The present invention relates to the technical field of high-strength magnetic rotors, and specifically to a high-strength magnetic rotor segmented integral magnetization device and a magnetization method thereof. Background Art

[0002] As a key component of high-performance devices such as motors, generators, and magnetic levitation systems, the magnetic field strength and stability of a high-strength magnetic rotor directly affect the operating efficiency and reliability of the device. The magnetization process of a high-strength 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, and to avoid problems such as magnetic field degradation and performance decline caused by uneven or improper magnetization. In order to improve the magnetization efficiency and system stability, the magnetization process of a high-strength magnetic rotor often needs to reduce the interference and overload between adjacent magnetic segments by reasonably designing the magnetization sequence and magnetization current, thereby improving the overall magnetization effect.

[0003] Currently, for the magnetization process of high-strength magnetic rotors, the existing methods still have the following deficiencies: blindness of the magnetization sequence: traditional magnetization methods usually adopt a fixed magnetization sequence or sort according to experience. However, due to the complexity and difference of the rotor structure, this method ignores the sensitivity difference of different magnetic segments to the magnetization current. And there is a lack of a 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 during the actual magnetization process when the magnetization current changes too fast, too slow, or the magnetization switching is improper, which may lead to problems such as reverse magnetic fields and overloads.

[0004] The disadvantages of the existing methods directly lead to some unpredictable abnormal phenomena during the magnetization process of high-strength magnetic rotors. These phenomena include but are not limited to: generation of reverse magnetic fields: due to improper switching of the magnetization current, the current may reverse too quickly, resulting in a reverse magnetic field in the previous magnetic segment, affecting the magnetization effect of subsequent magnetic segments. The generation of reverse magnetic fields not only affects the uniform distribution of the magnetic field, but may also cause incomplete magnetization of the magnetic segment or unstable magnetic field strength, reducing the operating efficiency of the device. Summary of the Invention

[0005] Aiming at the deficiencies of the existing technology, the present invention provides a high-strength magnetic rotor segmented integral magnetization device and a magnetization method thereof, which solve the problems in the above background art.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: A high-strength magnetic rotor segmented integral magnetization method includes the following steps:

[0007] S1. Pre-acquire the geometric data on the surface of the high-strength magnetic rotor, and divide the high-strength 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;

[0008] S2. After extracting the features of the relevant operation data, analyze the sensitivity of each magnetic segment to the magnetizing current 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. Combine the trained sorting prediction model, fit and output a sorting index Pxzb. Based on the value of the sorting index Pxzb, sequentially perform magnetizing sorting on several groups of magnetic segments to obtain an initial sorting list;

[0009] S3. Based on the initial sorting list, sequentially perform magnetizing test operations on several groups of magnetic segments. During the magnetizing test, real-time monitor the current difference between the magnetic segments in adjacent magnetizing orders when the magnetizing of the magnetic segment is switched to obtain relevant test data. According to the test data, analyze whether the magnetizing process of the next magnetic segment will affect the occurrence of a reverse magnetic field in the previous magnetic segment to obtain a determination coefficient Pdxs;

[0010] S4. Based on the determination coefficient Pdxs, judge whether it is necessary to re-perform magnetizing sorting on several groups of magnetic segments. If necessary, generate an optimized sorting list and perform magnetizing operations on several groups of magnetic segments based on the optimized sorting list.

[0011] Preferably, the specific steps of S1 include:

[0012] S11. First, obtain the geometric data of the surface of the high-strength magnetic rotor from the CAD file provided by the supplier. The geometric data includes the radii of points on the cross-section of the high-strength magnetic rotor. At the same time, evenly divide the high-strength magnetic rotor into several groups of regions, and combine the geometric data to analyze the geometric state of the rotor surface in several groups of regions. Calculate the flatness, and according to the difference in the flatness values of the rotor surface in each region, mark several groups of regions as different magnetic segments respectively, and mark the regions with the same flatness value as the same magnetic segment;

[0013] S12. Based on the several groups of magnetic segments obtained in S11, perform magnetizing operations on several groups of magnetic segments respectively to obtain relevant operation data. Among them, the relevant operation data includes the magnetizing current of each magnetic segment in each monitoring period , magnetic field strength , the starting current of each magnetic segment when performing the magnetizing operation and the final current .

[0014] Preferably, the specific steps of S2 include:

[0015] S21. After extracting the features of the relevant operation data, 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 in each monitoring period and magnetic field intensity , analyze the sensitivity of each magnetic segment to the magnetization current to generate a sensitivity coefficient Mgxs, and the sensitivity coefficient Mgxs is obtained through the following formula:

[0016] ;

[0017] In the formula, represents the sensitivity coefficient of the th magnetic segment, N represents the monitoring period, and i = 1, 2,..., N, represents the average magnetization current during the th monitoring period, represents the average magnetization current during the monitoring period, represents the average magnetic field intensity during the th monitoring period, represents the average magnetic field intensity during the monitoring period.

[0018] Preferably, the specific steps of S2 further include:

[0019] S22. After extracting the features of the relevant operation data, obtain the starting current of each magnetic segment during the magnetization operation and the final current . Based on the starting current and the final current of each magnetic segment during the magnetization operation, analyze the magnetization load situation borne by each magnetic segment during the magnetization process, and analyze and calculate to obtain the current response time Dysc. The current response time Dysc is obtained through the following formula:

[0020] ;

[0021] In the formula, represents the final current of the th magnetic segment, represents the current response time of the th magnetic segment, represents the starting current of the th magnetic segment, represents the current change rate.

[0022] Preferably, the specific steps of S2 further include:

[0023] S23. Utilize deep learning technology and combine relevant operation data to construct a sorting prediction model. After training and dimensionless processing, fit and output a sorting index Pxzb. The sorting index Pxzb is obtained through the following formula:

[0024] ;

[0025] In the formula, represents the sorting index of the nth magnetic segment, represents the sensitivity coefficient of the nth magnetic segment, represents the maximum value of the sensitivity coefficients among all magnetic segments, represents the maximum value of the current response times among all magnetic segments, represents the current response time of the nth magnetic segment, and both represent weight values. Among them, and The specific numerical values are set by the user according to the situation.

[0026] Preferably, the specific steps of S2 further include:

[0027] S24. According to the method of obtaining the sorting index Pxzb in S23, obtain the sorting indexes Pxzb of several groups of magnetic segments in sequence, and sort the sorting indexes Pxzb of several groups of magnetic segments from small to large according to the numerical size to obtain an initial sorting list, and input the initial sorting list into step S3.

[0028] Preferably, the specific steps of S3 include:

[0029] S31. Receive the initial sorting list in step S24, and according to the initial sorting list, perform magnetization test operations on each magnetic segment of the strong magnetic rotor in the front-back order in the initial sorting list. During the magnetization test operation, use several groups of monitoring instruments to monitor the current difference between adjacent magnetized magnetic segments in real time during the process of magnetizing and switching magnetic segments to obtain relevant test data. Among them, the relevant test data includes the current value I of the adjacent magnetic segments in the magnetic order and the current change speed of the adjacent magnetic segments in the magnetic order when performing magnetization switching, which are obtained by real-time monitoring when testing several groups of magnetic segments according to the magnetization order in the initial sorting list. .

[0030] Preferably, the specific steps of S3 further include:

[0031] S32. According to the relevant test data, analyze whether the process of magnetizing the next magnetic segment will affect the occurrence of a reverse magnetic field in the previous magnetic segment during the magnetizing and switching of the magnetic segment, and after dimensionless processing, obtain a judgment coefficient Pdxs. The judgment coefficient Pdxs is obtained through the following formula:

[0032] ;

[0033] In the formula, and Indicates the magnetic segments of adjacent magnetic orders and the current value during magnetization switching, Indicates the magnetic segments of adjacent magnetic orders and the current change rate during magnetization switching, and both represent weight values, where, and The specific values are set by the user according to the situation.

[0034] Preferably, the specific steps of S4 include:

[0035] S41. Preset an evaluation threshold K, and by comparing and analyzing the evaluation threshold K with the determination coefficient Pdxs, determine whether it is necessary to re - magnetize and sort several groups of magnetic segments. The specific judgment steps are as follows:

[0036] S411. If the determination coefficient Pdxs exceeds the evaluation threshold K, it indicates that there is a reverse magnetic field caused by the magnetization order problem currently, and it is determined that it is necessary to re - sort the magnetization order between the corresponding magnetic segments at this time. At this time, optimize the initial sorting list obtained in step S24. The specific optimization content is: on the basis of the initial sorting list, stagger the sorting of the magnetic segments of adjacent magnetic orders, where the magnetic segments of adjacent magnetic orders include the currently monitored magnetic segment and the previous magnetic segment;

[0037] S4111. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the current magnetic segment is at the last position in the initial sorting list, at this time, move the order of the previous magnetic segment forward by one position;

[0038] S4112. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the previous magnetic segment is at the first position in the initial sorting list, at this time, move the order of the current magnetic segment backward by one position;

[0039] S4113. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the previous magnetic segment is not at the first position in the initial sorting list, and the current magnetic segment is not at the last position in the initial sorting list, at this time, move the order of the current magnetic segment backward by one position or move the order of the previous magnetic segment forward by one position;

[0040] S4114. If the starting current of the current magnetic segment < the starting current of the previous magnetic segment , at this time, move the order of the previous magnetic segment backward by three positions;

[0041] 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 the magnetization sequence at present, and it is judged that it is not necessary to re-sort the magnetization sequence between the corresponding magnetic segments for the time being, and the initial sorting list obtained in step S24 is maintained.

[0042] A strong magnetic rotor segmented integral magnetization device, including an acquisition module, a preliminary sorting module, a preliminary sorting fault analysis module and a sorting optimization module;

[0043] The acquisition module is used to pre-acquire the geometric data on 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;

[0044] The preliminary sorting module is used to analyze the sensitivity of each magnetic segment to the magnetization current by extracting features from the relevant operation data to generate a sensitivity coefficient Mgxs, and analyze the magnetization load situation borne by each magnetic segment during the magnetization process to generate a current response time Dysc. Combining with the trained sorting prediction model, it fits and outputs a sorting index Pxzb. Based on the value of the sorting index Pxzb, the several groups of magnetic segments are magnetized and sorted in sequence to obtain an initial sorting list;

[0045] The preliminary sorting fault analysis module is used to perform magnetization test operations on several groups of magnetic segments in sequence based on the initial sorting list, and during the magnetization test, it monitors in real time the current difference situation between the magnetic segments with adjacent magnetization sequences when the magnetization of the magnetic segment is switched to obtain relevant test data, and based on the test data, analyzes whether the magnetization process of the next magnetic segment will affect the previous magnetic segment to generate a reverse magnetic field when the magnetization of the magnetic segment is switched to obtain a determination coefficient Pdxs;

[0046] The sorting optimization module is used to judge whether it is necessary to re-sort several groups of magnetic segments based on the determination coefficient Pdxs. If so, it generates an optimized sorting list and performs magnetization operations on several groups of magnetic segments based on the optimized sorting list.

[0047] The present invention provides a strong magnetic rotor segmented integral magnetization device and its magnetization method, which have the following beneficial effects:

[0048] Through the analysis based on the sensitivity coefficient Mgxs and the current response time Dysc, combined with the sorting prediction model, this method can effectively optimize the magnetization sequence, further avoid excessive current fluctuations or uneven loads during the magnetization process, thereby improving the magnetization efficiency and reducing energy waste. During the magnetization process, by real-time monitoring the current difference between adjacent magnetic segments and its change rate, the reverse magnetic field phenomenon that may occur during the magnetization switching process can be identified in a timely manner. Through the further optimization of the magnetization sequence by the determination coefficient Pdxs, the mutual interference between the front and rear magnetic segments and the generation of reverse magnetic fields caused by improper sequence arrangement are reduced, thereby ensuring the uniform distribution of the magnetic field and the stability of the rotor performance. Reducing the risk of equipment damage and extending the equipment life: 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 loads of the magnetization current on the magnetic segments, and reduce the damage to the rotor structure caused by excessive temperature or large 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, enhancing 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 change and magnetic field response during the magnetization switching in the magnetization test process. If unstable or unsatisfactory magnetization effects (such as reverse magnetic fields, etc.) are found during the magnetization process, through the comparison of the determination coefficient Pdxs and the evaluation threshold K, the magnetization sequence can be quickly identified and optimized, thereby enhancing the flexibility and adaptability of the magnetization process and improving the accuracy of the entire magnetization operation.

[0049] (2) In steps S21 and S22, through the detailed monitoring and analysis of the magnetization current and magnetic field strength, the sensitivity of each magnetic segment to the magnetization current and the magnetization load situation can be accurately quantified. By calculating the sensitivity coefficient and the 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, ensuring that the current and magnetic field strength during the magnetization process of each magnetic segment are within an appropriate range, and improving 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, and these magnetic segments can be preferentially arranged for magnetization, further reducing the reverse magnetic field or energy waste caused by uneven magnetization or rapid current changes.

[0050] (3) In step S24, by sorting each magnetic segment according to the sorting index, the automatic optimization of the magnetization sequence is further realized. This automatic 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 magnetization quality and stability: The obtained initial sorting list is based on accurate sorting indexes, which helps to optimize the current difference between magnetic segments during the magnetization process, reduce the influence of current fluctuations on the magnetization effect, and thus avoid the phenomena of unstable magnetic field 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 the operation stability of the equipment can be effectively improved.

[0051] (4) Through the analysis based on the test data in step S32, it can be accurately judged whether the magnetization operation of the next magnetic segment will affect the previous magnetic segment during the magnetization switching, thereby triggering a reverse magnetic field. This analysis can provide a scientific basis for adjusting the magnetization sequence and avoid the phenomena of unstable magnetic field or reverse magnetic field caused by improper magnetization sequence, improving the accuracy and safety of the magnetization operation. Dynamically optimize the magnetization sequence and 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 a timely manner. If the test results show that certain magnetization sequences are prone to triggering a reverse magnetic field, corresponding measures can be taken for optimization to avoid the influence of the unstable magnetic field and improve the safety of the magnetization process and the operation stability of the equipment. Brief Description of the Drawings

[0052] Figure 1 It is a schematic flow chart of a method for segmental integral magnetization of a high-strength magnetic rotor according to the present invention;

[0053] Figure 2 It is a block diagram of a device for segmental integral magnetization of a high-strength magnetic rotor according to the present invention. Detailed Embodiments

[0054] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0055] Embodiment 1

[0056] Please refer to Figure 1 , the present invention provides a method for segmental integral magnetization of a high-strength magnetic rotor, including the following steps:

[0057] S1. Pre-acquire the geometric data of the surface of the high-strength magnetic rotor, divide the high-strength 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;

[0058] S2. After extracting features from the relevant operation data, analyze the sensitivity of each magnetic segment to the magnetization current to generate a sensitivity coefficient Mgxs, analyze the magnetization load situation borne by each magnetic segment during the magnetization process to generate a current response time Dysc, and combine with the trained sorting prediction model to fit and output a sorting index Pxzb. Based on the value of the sorting index Pxzb, perform magnetization sorting on the several groups of magnetic segments in sequence to obtain an initial sorting list;

[0059] S3. Based on the initial sorting list, perform magnetization test operations on the several groups of magnetic segments in sequence, and during the magnetization test, monitor in real time the current difference situation between the magnetic segments of adjacent magnetization orders when the magnetization of the magnetic segment is switched to obtain relevant test data, and based on the test data, analyze whether the process of magnetizing the next magnetic segment will affect the occurrence of a reverse magnetic field in the previous magnetic segment when the magnetization of the magnetic segment is switched to obtain a determination coefficient Pdxs;

[0060] S4. Based on the determination coefficient Pdxs, judge whether it is necessary to re-perform magnetization sorting on 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.

[0061] In this embodiment, by pre-acquiring and analyzing the geometric data of the rotor, each magnetic segment can be divided, and magnetization sorting can be performed according to the characteristics of each magnetic segment (such as current sensitivity and load conditions) to ensure that the change in the magnetization current meets the requirements of each magnetic segment. This optimized sorting can reduce the repeated adjustment during the magnetization process, thereby reducing energy waste, improving the magnetization efficiency, and shortening the magnetization time. By analyzing the sensitivity of each magnetic segment in detail, generating a sensitivity coefficient, and monitoring the current difference during the magnetization process, the problem of uneven magnetic field can be effectively avoided, and the phenomenon of reverse magnetic field or magnetic field attenuation caused by improper magnetization sequence can be avoided. Thus, it ensures that the magnetization process of each magnetic segment is more independent and accurate, and guarantees the uniformity and stability of the overall magnetic field. When arranging the magnetization sequence, by analyzing the change in the magnetization current and monitoring the current difference in real time, it can be determined whether there is a reverse magnetic field generated due to the sequence problem. Based on this, the magnetization sequence can be dynamically adjusted to avoid generating unnecessary reverse magnetic fields and ensure that the magnetic field remains stable throughout the 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 an increase in rotor vibration, which in turn affects the stability of the equipment. However, through the reasonable arrangement of the magnetization sequence, the present invention further reduces this instability, which helps to improve the long-term stable operation of the equipment. By obtaining the determination coefficient Pdxs, it can be evaluated in real time whether the current magnetization sequence has caused the generation of a reverse magnetic field. If an abnormal situation caused by the sequence problem is found, the system can automatically generate an optimized sorting list to adjust the magnetization sequence. This dynamic optimization mechanism ensures that the magnetization process is always in a relatively optimal state and avoids the decline in equipment performance caused by the magnetization sequence problem.

[0062] Embodiment 2

[0063] Please refer to Figure 1 , specifically: The specific steps of S1 include:

[0064] S11. First, obtain the geometric data of the surface of the high-strength magnetic rotor from the CAD file provided by the supplier. The geometric data includes the radii at various points on the cross-section of the high-strength magnetic rotor. At the same time, the high-strength magnetic rotor is evenly divided into several groups of regions, and in combination with the geometric data, analyze the geometric state of the surface of the rotor within several groups of regions. Calculate the flatness, and according to the difference in the flatness values of the surface of the rotor within each region, mark several groups of regions as different magnetic segments respectively, and mark the regions with the same flatness value as the same magnetic segment;

[0065] Among them, the flatness is obtained by the ratio between the radii at various points on the cross-section of the high-strength magnetic rotor; it is a dimensionless parameter used to describe the flatness of the shape or structure of the rotor.

[0066] S12. Based on several groups of magnetic segments obtained in S11, perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data, where the relevant operation data includes the magnetization current of each magnetic segment within each monitoring period , magnetic field strength , the starting current of each magnetic segment during the magnetization operation and the final current .

[0067] In this embodiment, by pre-obtaining the geometric data on the surface of the strong magnetic rotor and combining it with the calculation of the flatness of the rotor surface, the rotor can be accurately divided into several magnetic segments. Through detailed analysis of each magnetic segment and based on the flatness differences in each region, the magnetic segments are reasonably divided, which can provide a more accurate basis for regional division for subsequent magnetization operations, avoiding the division errors caused by the previous manual division method, and thus making the magnetization operation of each magnetic segment 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 ensured, but also the geometric characteristics of the rotor can be obtained quickly and comprehensively. The comprehensive analysis of the geometric state of the rotor surface (such as radius and flatness, etc.) helps to more deeply understand 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. This method not only saves a lot of time and effort compared with the traditional manual measurement and adjustment, but also further improves the operation accuracy. By marking different regions as different magnetic segments according to the size differences of flatness, the requirements of different magnetic segments during the magnetization process can be accurately identified. Flatness is an important parameter of the rotor geometry, and its differences can directly affect the magnetization efficiency and magnetic field distribution.

[0068] Embodiment 3

[0069] Please refer to Figure 1 , specifically: The specific steps of S2 include:

[0070] S21. After extracting the features of the relevant operation data, obtain the magnetization current of each magnetic segment within each monitoring period and the magnetic field strength . Based on the magnetization current of each magnetic segment within each monitoring period and the magnetic field strength , analyze the sensitivity of each magnetic segment to the magnetization current to generate a sensitivity coefficient Mgxs. The sensitivity coefficient Mgxs is obtained through the following formula:

[0071] ;

[0072] In the formula, represents the sensitivity coefficient of the th magnetic segment, N represents the monitoring period, i = 1, 2,..., N, represents the average magnetization current during the monitoring period, represents the average magnetization current during the monitoring cycle, represents the average magnetic field intensity during the monitoring period, represents the average magnetic field intensity during the monitoring cycle.

[0073] The above magnetization current is monitored and obtained through a current sensor;

[0074] The magnetic field intensity can be monitored and obtained through a Hall sensor.

[0075] The specific steps of S2 further include:

[0076] S22. After extracting the characteristics of the relevant operation data, the starting current of each magnetic segment during the magnetization operation is obtained and the final current , based on the starting current and the final current of each magnetic segment during the magnetization operation, analyze the magnetization load situation borne by 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 through the following formula:

[0077] ;

[0078] In the formula, represents the final current of the th magnetic segment, represents the current response time of the th magnetic segment, represents the

[0079] 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.

[0080] Example 4

[0081] Please refer to Figure 1 Specifically: S2 includes the following specific steps:

[0082] 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:

[0083] ;

[0084] 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 among all magnetic segments, Represents the Current response time of the magnetic segment, And Both represent weight values, where, , And The specific values are set by the user according to the situation.

[0085] The specific steps of S2 also include:

[0086] S24. According to the method of obtaining the sorting index Pxzb in S23, obtain the sorting indexes Pxzb of several groups of magnetic segments in sequence, and sort the sorting indexes Pxzb of several groups of magnetic segments from small to large according to the numerical size to obtain the initial sorting list, and input the initial sorting list into step S3.

[0087] In this embodiment, accurate prediction and optimization of the magnetization order: By using deep learning technology and combining magnetization operation data to construct a sorting prediction model, the sorting indexes of each magnetic segment can be accurately predicted during the magnetization process. Through the training and dimensionless processing of the model, the inaccuracy caused by manual intervention can be avoided, and the magnetization order of the magnetic segments can be effectively predicted based on the sensitivity coefficient and the current response time. This method ensures the scientificity and systematicness of the magnetization order, avoids the unreasonable magnetization order caused by improper manual 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 indexes of the sensitivity coefficient and the current response time, the influence of both can be balanced. This method ensures that during the magnetization process, both the sensitivity of the magnetic segment to current changes can be taken into account, and the energy waste or overload risk during the magnetization process caused by excessive current response time can be avoided. By sorting the numerical values of the sorting indexes according to the size, the order arrangement during 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 failures.

[0088] Embodiment 5

[0089] Please refer to Figure 1 , specifically: The specific steps of S3 include:

[0090] S31. Receive the initial sorting list in step S24. According to the initial sorting list, perform magnetization testing operations on each magnetic segment of the strong magnetic rotor in the front-back order in the initial sorting list. During the magnetization testing operation, use several groups of monitoring instruments to continuously monitor the current difference between adjacent magnetized segments during the magnetization switching of magnetic segments, so as to obtain relevant test data. Among them, the relevant test data includes the current value I of adjacent magnetic segments with adjacent magnetic orders during magnetization switching and the current change rate of adjacent magnetic segments with adjacent magnetic orders during magnetization switching, which are obtained by real-time monitoring when testing several groups of magnetic segments in the magnetization order in the initial sorting list. 。

[0091] The specific steps of S3 also include:

[0092] S32. According to the relevant test data, analyze whether the process of magnetizing the next magnetic segment will affect the occurrence of a reverse magnetic field in the previous magnetic segment during the magnetization switching of magnetic segments. After dimensionless processing, obtain the determination coefficient Pdxs. The determination coefficient Pdxs is obtained through the following formula:

[0093] ;

[0094] In the formula, and represent the current values of adjacent magnetic segments with adjacent magnetic orders during magnetization switching. represents the current change rate of adjacent magnetic segments with adjacent magnetic orders during magnetization switching. and both represent weight values. Among them, , and The specific values are set by the user according to the situation.

[0095] 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, enabling precise capture of current changes during the magnetization switching of magnetic segments. This high-precision real-time monitoring can promptly detect current fluctuations or mutations, ensuring the stability of the magnetization operation and providing accurate data support for subsequent analysis of whether a reverse magnetic field will be generated. Monitoring the current change rate improves data accuracy: During the magnetization switching process, in addition to monitoring the current value, the current change rate is also recorded and analyzed in real time. This additional analysis dimension can further reveal the trend and speed of current fluctuations, helping to evaluate the stability and sequence rationality of the magnetization operation. Monitoring and analyzing the current change rate can effectively avoid abnormalities in the magnetization process caused by too fast or unstable current fluctuations, thereby improving the controllability of the magnetization operation. Optimization judgment based on the determination coefficient Pdxs: The determination coefficient obtained through dimensionless processing in step S32 provides a reliable quantitative basis for analyzing whether the magnetization switching causes a reverse magnetic field. This 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 triggering reverse changes or instability of the magnetic field. Through this coefficient, it is possible to accurately judge whether there are problems with the magnetization sequence and avoid the subjective deviation of manual experience judgment.

[0096] Embodiment 6

[0097] Please refer to Figure 1 , specifically: The specific steps of S4 include:

[0098] S41. Preset an evaluation threshold K. By comparing and analyzing the evaluation threshold K with the determination coefficient Pdxs, it is determined whether it is necessary to reorder the magnetization of several groups of magnetic segments. The specific judgment steps are as follows:

[0099] Obtain multiple groups of determination coefficients Pdxs through continuous testing, and combine statistical algorithms to obtain the average determination coefficient and the standard deviation of the determination coefficient. Based on 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 taking values from 1 to 3, corresponding to different confidence levels, and the specific values are set by the user (according to the actual situation);

[0100] S411. If the determination coefficient Pdxs exceeds the evaluation threshold K, it indicates that there is a reverse magnetic field caused by the problem of the magnetization sequence at present, and it is determined that it is necessary to reorder the magnetization sequence between the corresponding magnetic segments at present. 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 with adjacent magnetic sequences are sorted in a staggered manner, where the magnetic segments with adjacent magnetic sequences include the currently monitored magnetic segment and the previous magnetic segment;

[0101] S4111. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the current magnetic segment is at the last position in the initial sorting list, then advance the order of the previous magnetic segment by one position at this time;

[0102] S4112. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the previous magnetic segment is at the first position in the initial sorting list, then retreat the order of the current magnetic segment by one position at this time;

[0103] S4113. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the previous magnetic segment is not at the first position in the initial sorting list, and the current magnetic segment is not at the last position in the initial sorting list, then retreat the order of the current magnetic segment by one position or advance the order of the previous magnetic segment by one position at this time;

[0104] S4114. If the starting current of the current magnetic segment < the starting current of the previous magnetic segment , then retreat the order of the previous magnetic segment by three positions at this time;

[0105] 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 magnetization order problem currently, and it is judged that there is no need to re - sort the magnetization order between the corresponding magnetic segments for the time being, and the initial sorting list obtained in step S24 is maintained.

[0106] 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.

[0107] Example 7

[0108] 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;

[0109] 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;

[0110] 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;

[0111] The preliminary sorting fault analysis module is used to perform magnetization tests on several groups of magnetic segments in sequence based on the initial sorting list. During the magnetization test, the current difference between adjacent magnetized segments during the magnetization switching of the magnetic segments is monitored in real time to obtain relevant test data. According to the test data, it is analyzed whether the magnetization process of the next magnetic segment will affect the occurrence of reverse magnetic field in the previous magnetic segment during the magnetization switching of the magnetic segments, so as to obtain the determination coefficient Pdxs;

[0112] The sorting optimization module is used to judge whether it is necessary to re-magnetize and sort several groups of magnetic segments based on the determination coefficient Pdxs. If necessary, an optimized sorting list is generated, and the magnetization operation is performed on several groups of magnetic segments based on the optimized sorting list.

[0113] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principle and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for integral magnetization of a segmented strong magnetic rotor, characterized in that: It includes the following steps: S1. Pre-acquire the 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 extracting features from relevant operation data, analyze the sensitivity of each magnetic segment to the magnetizing current 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. Combine the trained sorting prediction model to fit and output a sorting index Pxzb. Based on the value of the sorting index Pxzb, perform magnetizing sorting on several groups of magnetic segments in sequence to obtain an initial sorting list. The specific steps of S2 include: S21. After extracting features from relevant operation data, obtain the magnetizing current I and magnetic field strength of each magnetic segment during each monitoring period , based on the magnetizing current I and magnetic field strength of each magnetic segment during each monitoring period , analyze the sensitivity of each magnetic segment to the magnetizing current to generate a sensitivity coefficient Mgxs. The sensitivity coefficient Mgxs is obtained through the following formula: ； Wherein, represents the sensitivity coefficient of the j-th magnetic segment, N represents the monitoring period, and i = 1, 2,..., N, represents the average magnetization current during the i-th monitoring period, represents the average magnetization current during the monitoring period, represents the average magnetic field strength during the i-th monitoring period, represents the average magnetic field strength during the monitoring period; S22. After extracting the features of the relevant operation data, the starting current of each magnetic segment during the magnetizing operation is obtained. And the final current . Based on the starting current And the final current Of each magnetic segment during the magnetizing operation, analyze the magnetizing load situation borne by each magnetic segment during the magnetizing process, analyze and calculate to obtain the current response time Dysc, and the current response time Dysc is obtained through the following formula: ； In the formula, represents the final current of the j-th magnetic segment, represents the current response time of the j-th magnetic segment, represents the starting current of the j-th magnetic segment, represents the current change rate; S3. Based on the initial sorting list, perform magnetization test operations on several groups of magnetic segments in sequence, and during the magnetization test, monitor in real time the current difference between adjacent magnetized segments during the magnetization switching of the magnetic segments to obtain relevant test data, and based on the test data, analyze whether the magnetization process of the next magnetic segment will affect the occurrence of reverse magnetic field in the previous magnetic segment during the magnetization switching of the magnetic segment to obtain the determination coefficient Pdxs; S4. Based on the determination coefficient Pdxs, judge whether it is necessary to re-perform magnetization sorting on several groups of magnetic segments. If so, 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 integral magnetization of a segmented high-strength magnetic rotor according to claim 1, characterized in that: The specific steps of S1 include: S11. Pre-acquire the geometric data of the surface of the strong magnetic rotor from the CAD file provided by the supplier. The geometric data includes the radii of each point on the cross-section of the strong magnetic rotor; at the same time, evenly divide the strong magnetic rotor into several groups of regions, and combine the geometric data to analyze the geometric state of the rotor surface in the several groups of regions, calculate the flatness, and according to the difference in the flatness values of the rotor surface in each region, mark the several groups of regions as different magnetic segments respectively, and mark the regions with the same flatness value as the same magnetic segment; S12. Based on several groups of magnetic segments obtained in S11, perform magnetization operations on the several groups of magnetic segments respectively to obtain relevant operation data, where the relevant operation data includes the magnetization current I and magnetic field strength of each magnetic segment within each monitoring period , the starting current of each magnetic segment during the magnetization operation and the final current .

3. A method for integral magnetization of a segmented high-strength magnetic rotor according to claim 2, characterized in that: The specific steps of S2 also include: S23. Use deep learning technology and combine relevant operation data to construct a sorting prediction model. After training and dimensionless processing, fit and output the sorting index Pxzb. The sorting index Pxzb is obtained through the following formula: ； In the formula, represents the sorting index of the j-th magnetic segment, represents the sensitivity coefficient of the j-th magnetic segment, represents the maximum value of the sensitivity coefficients among all magnetic segments, represents the maximum value of the current response times among all magnetic segments, represents the current response time of the j-th magnetic segment, and both represent weight values, where and The specific values are set by the user according to the situation.

4. A method for segmental integral magnetization of a high-strength magnetic rotor according to claim 3, characterized in that: The specific steps of S2 also include: S24. According to the method of obtaining the sorting index Pxzb in S23, obtain the sorting indexes Pxzb of several groups of magnetic segments in sequence, and sort the sorting indexes Pxzb of several groups of magnetic segments from small to large according to the numerical size to obtain an initial sorting list, and input the initial sorting list into step S3.

5. A method for integral magnetization of a segmented strong magnetic rotor according to claim 4, characterized in that: The specific steps of S3 include: S31. Receive the initial sorting list in step S24, and according to the initial sorting list, perform magnetization testing operations on each magnetic segment of the strong magnetic rotor in the front-back order in the initial sorting list. During the magnetization testing operations, use several groups of monitoring instruments to continuously monitor the current difference between the magnetic segments in adjacent magnetization orders during the process of magnetization switching magnetic segments, so as to obtain relevant test data. Among them, the relevant test data includes the current value I when the magnetic segments in adjacent magnetic orders are magnetized and switched, and the current change speed when the magnetic segments in adjacent magnetic orders are magnetized and switched, which are obtained by continuously monitoring during the testing of several groups of magnetic segments in the magnetization order in the initial sorting list. .

6. A method for segmental integral magnetization of a high-strength magnetic rotor according to claim 5, characterized in that: The specific steps of S3 also include: S32. According to the relevant test data, analyze whether the magnetization process of the next magnetic segment will affect the occurrence of reverse magnetic field in the previous magnetic segment during the magnetization switching of the magnetic segment, and after dimensionless processing, obtain the determination coefficient Pdxs. The determination coefficient Pdxs is obtained through the following formula: ； In the formula, and represent the magnetic segments of adjacent magnetic orders, and the current value during magnetization switching, represent the magnetic segments of adjacent magnetic orders, and the current change rate during magnetization switching, and both represent weight values, where and The specific values are set by the user according to the situation.

7. A method for segmental integral magnetization of a high-strength magnetic rotor according to claim 6, characterized in that: The specific steps of S4 include: S41. Preset an evaluation threshold K, and compare and analyze the evaluation threshold K with the determination coefficient Pdxs to judge whether it is necessary to re-perform magnetization sorting on several groups of magnetic segments. The specific judgment steps are as follows: S411. If the determination coefficient Pdxs exceeds the evaluation threshold K, it indicates that there is a reverse magnetic field caused by the problem of the magnetization sequence currently, and it is determined that the magnetization sequence between the corresponding magnetic segments needs to be reordered. At this time, the initial sorting list obtained in step S24 is optimized. The specific optimization content is as follows: on the basis of the initial sorting list, the magnetic segments with adjacent magnetic sequences are sorted in a staggered manner, where the magnetic segments with adjacent magnetic sequences include the currently monitored magnetic segment and the previous magnetic segment; S4111. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the current magnetic segment is at the last position in the initial sorting list, then advance the order of the previous magnetic segment by one position at this time; S4112. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the previous magnetic segment is in the first place in the initial sorting list, then the order of the current magnetic segment is moved back one place at this time; S4113. If the starting current of the current magnetic segment ≥ the starting current of the previous magnetic segment , and the previous magnetic segment is not in the first position of the initial sorting list, and the current magnetic segment is not in the last position of the initial sorting list, then at this time, move the order of the current magnetic segment back by one position or move the order of the previous magnetic segment forward by one position; S4114. If the starting current of the current magnetic segment < the starting current of the previous magnetic segment , at this time, move the order of the previous magnetic segment back by three positions; 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 the magnetization sequence currently, and it is determined that it is not necessary to reorder the magnetization sequence between the corresponding magnetic segments temporarily, and the initial sorting list obtained in step S24 is maintained.

8. A segmented integral magnetization device for a strong magnetic rotor, which is used to implement the segmented integral magnetization method for a strong magnetic rotor according to any one of claims 1 to 7 above, and is characterized in that: It includes a data acquisition module, a preliminary sorting module, a preliminary sorting fault analysis module, and a sorting optimization module; The data acquisition module is used to pre-acquire the geometric data on the surface of the high-strength magnetic rotor, and divide the high-strength 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 magnetization current by extracting features from the relevant operation data to generate a sensitivity coefficient Mgxs, and analyze the magnetization load borne by each magnetic segment during the magnetization process to generate a current response time Dysc. Combining with the trained sorting prediction model, it fits and outputs a sorting index Pxzb. Based on the value of the sorting index Pxzb, the several groups of magnetic segments are magnetized and sorted in sequence to obtain an initial sorting list; The preliminary sorting fault analysis module is used to perform magnetization test operations on the several groups of magnetic segments in sequence based on the initial sorting list, and during the magnetization test, the current difference between the magnetic segments with adjacent magnetization sequences is monitored in real time when the magnetization of the magnetic segment is switched to obtain relevant test data. According to the test data, it is analyzed whether the magnetization process of the next magnetic segment will affect the previous magnetic segment to generate a reverse magnetic field when the magnetization of the magnetic segment is switched to obtain a determination coefficient Pdxs; The sorting optimization module is used to judge whether it is necessary to reorder the magnetization of the several groups of magnetic segments based on the determination coefficient Pdxs. If so, an optimized sorting list is generated, and the several groups of magnetic segments are magnetized based on the optimized sorting list.

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