A method and system for diagnosing a turn-to-turn short circuit fault in a dual three-phase Vernier generator

Abstract

The application discloses a kind of double three-phase vernier generator interturn short circuit fault diagnosis method and system, the method includes four stages of preparation, input, calculation and output: first, obtain voltage signal under different working conditions by finite element analysis, and extract fault characteristic quantity in combination with fast fourier transform;Second, set fault threshold and weight parameter;Then calculate fault discrimination coefficient to judge whether fault occurs, and further distinguish three kinds of faults of single winding single phase, single winding double phase and cross winding double phase, determine fault phase and evaluate fault degree by positioning coefficient simultaneously;Finally, output fault type, position and severity.The method realizes the accurate identification, positioning and quantitative evaluation of fault, and improves the accuracy and reliability of diagnosis.

Description

Technical Field

[0001] This invention belongs to the field of motor fault diagnosis technology, and specifically relates to a method and system for diagnosing inter-turn short-circuit faults in a dual three-phase vernier generator. Background Technology

[0002] Dual-phase three-phase vernier generators possess high torque density, high efficiency, and good fault tolerance, making them promising for applications in low-speed direct-drive power generation. However, under conditions of high voltage, high current, and complex mechanical vibration, the stator winding insulation is prone to aging or damage, leading to inter-turn short-circuit faults. These faults disrupt the symmetry of the air gap magnetic field distribution, resulting in increased motor torque pulsation and decreased operating performance. If not detected and addressed promptly, the fault may further evolve into phase-to-phase short circuits or ground faults, and in severe cases, even cause winding burnout, affecting the safe operation of the system.

[0003] Existing diagnostic methods for inter-turn short-circuit faults in dual-phase three-phase vernier generators mostly rely on single feature quantity analysis, which is easily affected by changes in operating conditions such as speed and number of short-circuit turns, leading to unstable fault feature extraction and limited diagnostic accuracy. In addition, existing methods are insufficient in fault type differentiation, fault phase location, and fault severity assessment, making it difficult to simultaneously ensure diagnostic accuracy and robustness, thus limiting the reliability and safety of generator system operation. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes a method and system for diagnosing inter-turn short-circuit faults in dual-three-phase vernier generators. The purpose is to solve the problems that inter-turn short-circuit fault diagnosis in dual-three-phase vernier generators is greatly affected by operating conditions, but the robustness and accuracy of characteristic quantity diagnosis are insufficient. This invention achieves the technical effects of high-precision identification, type differentiation, fault location, and severity assessment of inter-turn short-circuit faults.

[0005] The first aspect of the present invention provides a method for diagnosing inter-turn short-circuit faults in a dual three-phase vernier generator, comprising: S1: acquiring phase voltage signals of the six-phase windings of the dual three-phase vernier generator, and performing a fast Fourier transform on the phase voltage signals to extract the fundamental amplitude and second harmonic amplitude of each phase.

[0006] S2: Construct a set of fault characteristic quantities based on the phase voltage signal, including the phase voltage residual within the same winding, used to characterize the difference between phase voltages within the same three-phase winding; the phase voltage residual across windings, used to characterize the difference between corresponding phase voltages of two sets of three-phase windings; and the proportion of second harmonic content, which is the ratio of the second harmonic amplitude to the fundamental amplitude of each phase voltage.

[0007] S3: The above and The fault type discrimination coefficient is obtained by weighting and fusing the coefficients according to the first weight combination coefficient. and will With fault threshold The comparison is performed, and when λ≥μ, it is determined to be an inter-turn short circuit fault state; otherwise, it is determined to be a normal state.

[0008] S4: After determining that the fault is an inter-turn short circuit fault, the fault type is determined according to the combination relationship with the corresponding preset threshold, including single-winding single-phase fault (SWSP), single-winding two-phase fault (SWDP), and cross-winding two-phase fault (CWDP).

[0009] S5: The corresponding phase voltage residuals within the same winding, phase voltage residuals across windings, and the proportion of second harmonic content are weighted and fused according to the second weighting combination coefficient to obtain the fault location coefficient for each phase. and according to The magnitude of the fault determines the location of the faulty phase.

[0010] S6: Construct a fault severity assessment model based on the fault phase voltage characteristics and its second harmonic components, calculate the number of short-circuit turns or equivalent fault severity parameters, and output the fault type, fault phase location and fault severity.

[0011] The first weight combination is used to characterize fault discrimination sensitive features, the second weight combination is used to characterize fault location sensitive features, and the first weight combination and the second weight combination are set independently for different diagnostic targets to achieve differentiated fusion of multiple features in the fault discrimination and fault location process.

[0012] According to one embodiment of the present invention, the second harmonic content accounts for... It is the ratio of the second harmonic amplitude of the x-th phase voltage to the fundamental amplitude.

[0013] According to an embodiment of the present invention, the residual voltage of the same winding phase... The phase voltage residual across the winding is a function of the difference in voltage amplitude between any two phases within the same three-phase winding. It is a function of the difference in phase voltage amplitude between the two sets of three-phase windings.

[0014] According to an embodiment of the present invention, the fault type discrimination coefficient Depend on and By weight The calculation is as follows: in, This is the first weighting coefficient.

[0015] The fault threshold Based on the fault category discrimination coefficient under normal operating conditions The statistical distribution is determined.

[0016] In step S4, the fault type discrimination rules include: When there is only one set of windings Greater than the first preset threshold, and only one If the value exceeds the second preset threshold, it is determined to be SWSP.

[0017] When there is only one set of windings Greater than the first preset threshold, and two If the value exceeds the second preset threshold, it is determined to be SWDP.

[0018] When two sets of windings Both are greater than the first preset threshold, and both If the value exceeds the second preset threshold, it is determined to be CWDP.

[0019] The fault phase location coefficient Depend on , and According to the second weight The weighted fusion calculation is as follows: in, This is the second weighted combination coefficient.

[0020] According to one embodiment of the present invention, the fault severity assessment model is a multi-parameter fitting model constructed based on the correspondence between the voltage amplitude of the fault phase and the amplitude of the second harmonic under different short-circuit turns conditions obtained by finite element simulation, which is used to determine the number of short-circuit turns or the fault severity based on actual measurement data.

[0021] According to an embodiment of the present invention, the first weight combination coefficient satisfies: The second weighted combination coefficients satisfy: .

[0022] According to one embodiment of the present invention, the dual three-phase winding includes a first three-phase winding and a second three-phase winding, and there is a preset phase difference between the two windings.

[0023] A second aspect of the present invention provides a diagnostic system for inter-turn short-circuit faults in a dual three-phase vernier generator, comprising: The signal acquisition module is used to acquire the phase voltage signals of the six-phase windings of the dual three-phase vernier generator and extract the fundamental amplitude and second harmonic amplitude of each phase.

[0024] The signal processing module is used to construct the phase voltage residuals of the same winding. Phase voltage residual across windings and the proportion of second harmonic content .

[0025] The feature construction module is used to calculate the fault type discrimination coefficient. and will be related to the fault threshold The fault status is determined by comparison.

[0026] The fault diagnosis module is used to determine the fault based on the above. and The threshold combination relationship is used to determine the fault type.

[0027] The fault location module is used to calculate the fault location coefficient for each phase. And determine the location of the faulty phase.

[0028] The fault assessment module is used to calculate the number of short-circuit turns or fault severity parameters and output diagnostic results.

[0029] According to one embodiment of the present invention, the signal processing module includes a fast Fourier transform unit.

[0030] According to one embodiment of the present invention, the system is deployed in a dual three-phase vernier generator controller or an online monitoring device.

[0031] The technical effects achieved by this invention are as follows: First, by constructing a multi-feature fusion mechanism of phase voltage residual in the same winding, phase voltage residual across windings, and the proportion of second harmonic content, and by adopting a weighted strategy for discrimination and localization, the characteristic responses corresponding to different fault types have obvious distinguishability, thereby significantly improving the identification accuracy of inter-turn short-circuit faults.

[0032] Secondly, the influence of speed variation and short-circuit turn number variation on voltage signal is considered in combination with finite element analysis. By synergistic fusion of multiple features, the influence of single feature on operating condition disturbance is reduced, so that the diagnostic results remain stable under different operating conditions and the anti-interference capability of the system is improved.

[0033] Furthermore, by constructing fault type discrimination coefficients and fault phase location coefficients, the system can effectively distinguish between single-phase faults in a single winding, two-phase faults in a single winding, and two-phase faults across windings based on the characteristic combination variation relationship. At the same time, it can accurately determine the location of the specific fault phase, thereby improving the precision of diagnosis.

[0034] Finally, by establishing a fitting relationship model between fault voltage characteristics and the number of short-circuit turns, a quantitative assessment of the degree of inter-turn short-circuit faults can be achieved. This not only determines whether a fault has occurred but also reflects the severity of the fault, providing a basis for subsequent maintenance decisions. Attached Figure Description

[0035] Figure 1 This is a flowchart of a diagnostic method for inter-turn short circuit faults in a dual three-phase vernier generator according to an embodiment of the present invention; Figure 2 This is a schematic diagram of inter-turn short-circuit fault classification for a dual three-phase permanent magnet vernier generator disclosed in an embodiment of the present invention; Figure 3 This is a simulation diagram of the six-phase voltage of a motor under four conditions: normal, SWSP, SWDP, and CWDP, as disclosed in the embodiments of the present invention. Figure 4 This is a graph showing the variation of the second harmonic amplitude of the phase voltage under different short-circuit turns conditions under SWSP conditions, as disclosed in an embodiment of the present invention. Figure 5 This is a graph showing the variation of the second harmonic amplitude of the phase voltage under different short-circuit turns conditions under SWDP conditions, as disclosed in an embodiment of the present invention. Figure 6 This is a graph showing the variation of the second harmonic amplitude of the phase voltage under different short-circuit turns under CWDP conditions, as disclosed in an embodiment of the present invention. Figure 7 These are the fault characteristic quantities under the three conditions of SWSP, SWDP, and CWDP disclosed in the embodiments of the present invention. Pattern diagram; Figure 8 These are the fault characteristic quantities under the three conditions of SWSP, SWDP, and CWDP disclosed in the embodiments of the present invention. Pattern diagram; Figure 9 These are the fault characteristic quantities under the three conditions of SWSP, SWDP, and CWDP disclosed in the embodiments of the present invention. Pattern diagram; Figure 10 This is an experimental waveform diagram of the six-phase voltage of a motor under normal conditions, as disclosed in an embodiment of the present invention. Figure 11 This is an experimental waveform diagram of the six-phase voltage of a 20-turn motor under SWSP conditions disclosed in an embodiment of the present invention; Figure 12 This is an experimental waveform diagram of the six-phase voltage of a 20-turn motor under CWDP conditions with inter-turn short circuit, as disclosed in an embodiment of the present invention. Figure 13 This is a comparison diagram of the distribution of fault discrimination model coefficients λ under different fault states disclosed in the embodiments of the present invention; Figure 14 These are the fault phase location model coefficients under SWSP conditions disclosed in the embodiments of the present invention. Comparison chart; Figure 15 This is a block diagram of a diagnostic system for inter-turn short-circuit faults in a dual three-phase vernier generator, as disclosed in an embodiment of the present invention. Detailed Implementation

[0036] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0037] The technical solution of the present invention is illustrated below through specific embodiments. It should be understood that the one or more steps mentioned in the present invention do not preclude the existence of other methods and steps before or after the combined steps, or that other methods and steps may be inserted between these explicitly mentioned steps. It should also be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Unless otherwise stated, the numbering of each method step is only for the purpose of identifying each method step, and not for limiting the order of each method or limiting the scope of the present invention. Changes or adjustments to their relative relationships, without substantial changes to the technical content, can also be considered as within the scope of the present invention.

[0038] This invention discloses a diagnostic method for inter-turn short-circuit faults in dual three-phase vernier generators, applicable to online diagnosis of inter-turn short-circuit faults in dual three-phase permanent magnet vernier generators, enabling fault identification, fault phase location, and fault severity assessment. Figure 1 As shown, through finite element analysis, considering the influence of changes in rotational speed and number of short-circuit turns on the voltage signal, the voltage signal is acquired and then subjected to Fast Fourier Transform to determine the fault diagnosis quantity and define the fault characteristic quantity. In the input stage, the fault threshold μ and weight ω are set. In the calculation stage, the fault type discrimination coefficient λ is first calculated. If λ ≥ μ, it is determined to be a fault. It further distinguishes three fault types: single-winding single-phase fault (SWSP), single-winding two-phase fault (SWDP), and cross-winding two-phase fault (CWDP). Then, the fault phase location coefficient η is calculated. x It assesses the severity of the fault and ultimately outputs the fault type, location, and severity.

[0039] Specifically, the method includes the following steps: S1: Acquire the phase voltage signals of the six-phase windings of the dual three-phase vernier generator, and perform a fast Fourier transform on the phase voltage signals to extract the fundamental amplitude and second harmonic amplitude of each phase. The proportion of the second harmonic content is the ratio of the second harmonic amplitude of the x-th phase to the fundamental amplitude.

[0040] A generator inter-turn short-circuit fault model was established using a combination of multi-loop circuit method and finite element method, taking into account the influence of changes in the number of short-circuit turns on the voltage signal. The six-phase voltage signals of the generator were collected, and harmonic analysis was performed using fast Fourier transform to determine the amplitude of the second harmonic of the phase voltage as the fault diagnosis value.

[0041] S2: Construct a set of fault characteristic quantities based on the phase voltage signal. The set of fault characteristic quantities includes the phase voltage residual in the same winding, the phase voltage residual across windings, and the proportion of second harmonic content.

[0042] Define the phase voltage residual of the same winding Phase voltage residual across windings Harmonic content ratio Fault characteristic quantities are analyzed to determine their variation with fault severity. The phase voltage residual within the same winding characterizes the voltage difference between phases within the same three-phase winding, while the phase voltage residual across windings characterizes the voltage difference between corresponding phases of two sets of three-phase windings.

[0043] S3: Based on the fault identification target, and The first weight combination is used for weighted fusion to calculate the fault type discrimination coefficient. and will With fault threshold When comparing, If the fault condition is not met, it is determined to be an inter-turn short circuit fault state; otherwise, it is determined to be a normal state.

[0044] The fault feature quantities obtained after processing the measured data are substituted into the fault type discrimination model, and the fault type discrimination coefficients are... Depend on and By weight The fault type discrimination coefficient is obtained through fusion calculation. The formula is as follows: (1) if If the condition is determined to be an inter-turn short circuit fault, it is considered to be in a normal state; otherwise, it is considered to be in a normal state.

[0045] The fault threshold Obtained from historical data or experimental calibration under normal operating conditions.

[0046] S4: After determining the inter-turn short-circuit fault condition, according to the above... and Combinations exceeding the corresponding preset thresholds are used to identify fault types, including single-winding single-phase fault (SWSP), single-winding two-phase fault (SWDP), and cross-winding two-phase fault (CWDP).

[0047] Fault type discrimination rules include: when only one set of windings Greater than the first preset threshold, and only one If the value exceeds the second preset threshold, it is determined to be SWSP. When there is only one set of windings... Greater than the first preset threshold, and two When the value exceeds the second preset threshold, it is determined to be SWDP; when the two sets of windings Both are greater than the first preset threshold, and both If the value exceeds the second preset threshold, it is determined to be CWDP.

[0048] S5: Calculate the residual voltage of the corresponding phase voltages in the same winding. Phase voltage residual across windings and the proportion of second harmonic content According to the second weighted combination coefficient Weighted fusion is performed to obtain the fault location coefficients for each phase. and according to The magnitude of the fault determines the location of the faulty phase.

[0049] The fault phase location coefficient Depend on , and By weight The result is obtained through fusion calculation and satisfies... .

[0050] Specifically, the characteristic quantities are substituted into the fault phase location model to calculate the fault phase location coefficients. : (2) in The ratio of the second harmonic amplitude of phase X to the fundamental amplitude. , For phase X, take the residual; for single-phase faults, take... The phase corresponding to the maximum value is the faulty phase; in the case of a two-phase fault, take... The first two digits correspond to the faulty phase.

[0051] S6: Construct a fault severity assessment model based on the fault phase voltage characteristics and their harmonic components, calculate the number of short-circuit turns or equivalent fault severity parameters, and output the fault type, fault phase location, and fault severity. The first weight combination is used to characterize fault discrimination sensitive features, and the second weight combination is used to characterize fault location sensitive features. Furthermore, the first and second weight combinations are independently set for different diagnostic objectives to achieve differentiated fusion of multiple features in the fault discrimination and fault location processes.

[0052] Specifically, based on the maximum value of the fault phase voltage Second harmonic amplitude A fault assessment fitting curve is constructed using the number of short-circuit turns *n*. The number of short-circuit turns is calculated by inputting the fault phase voltage and the amplitude of the second harmonic, thereby assessing the severity of the fault. The formula is as follows: (3) The dual three-phase permanent magnet vernier generator has a neutral point isolation structure. The stator includes two sets of three-phase windings ABC and DEF, with a phase difference of 20.5° between the two sets of windings. The stator 24 teeth adopt a double non-uniform tooth modulation structure. The rotor is an external rotor structure and is equipped with 19 pairs of tangentially magnetized permanent magnets.

[0053] By fully considering the impact of operating conditions such as speed and number of short-circuit turns on the voltage signal through finite element analysis, and combining it with fast Fourier transform to extract multi-dimensional fault features, the robustness of diagnosis is improved. With the help of multi-feature fusion design of fault type discrimination coefficient and fault phase location coefficient, the fault type can be accurately distinguished, the fault phase can be located and the fault degree can be assessed. High-precision diagnosis can be achieved without complex and redundant algorithms, which not only improves the accuracy and reliability of fault diagnosis, but also reduces the complexity of diagnosis. It is suitable for the operation scenarios of dual three-phase permanent magnet vernier generators with high requirements for fault diagnosis accuracy.

[0054] like Figure 2 The diagram shown is a classification diagram of inter-turn short-circuit faults in a dual three-phase permanent magnet vernier generator according to this embodiment. Based on the location of the faulty winding and its phase, the faults are classified into three types: SWSP, SWDP, and CWDP. The existence of these three fault types is shown in Table 1.

[0055] Table 1 like Figure 3 The figure shows the six-phase voltage simulation diagram of the motor under four conditions: normal, SWSP, SWDP, and CWDP. Based on this, the FFT analysis results are as follows... Figure 4 , Figure 5 , Figure 6 As shown in the figure These represent the amplitudes of the second, third, fourth, and fifth harmonics, respectively. The number of short-circuit turns in the figure is 0, 10, 20, 25, 30, 35, 40, and 50 turns, respectively. The horizontal axis represents different short-circuit turn counts, with A10 representing a 10-turn short circuit, A20 representing a 20-turn short circuit, and so on. The figure shows that under three fault types and different short-circuit turn counts, the second harmonic amplitude exhibits a significant increasing trend compared to the third and higher harmonic components. This means the second harmonic component is most sensitive to changes in the number of short-circuit turns and can be used as a primary characteristic for assessing fault severity. Therefore, the phase voltage second harmonic amplitude is determined as the fault diagnostic value.

[0056] After determining the fault diagnostic quantities, the residual voltage of the phase in the same winding is defined accordingly. Phase voltage residual across windings Harmonic content ratio Three types of fault characteristic quantities are analyzed to understand how these quantities change with the severity of the fault. Figure 7 , Figure 8 , Figure 9 As shown. Among them. Figure 7 (a) Figure 7 (b) Figure 7 (c) Corresponding to the three fault types SWSP, SWDP and CWDP respectively. Figure 7 (a) is the phase voltage residual of the same winding under different short-circuit turns under SWSP conditions. Change pattern diagram Figure 7 (b) is the phase voltage residual of the same winding under different short-circuit turns under SWDP conditions. Change pattern diagram Figure 7 (c) represents the phase voltage residual of the same winding under different short-circuit turns under CWDP conditions. Chart showing the pattern of change.

[0057] like Figure 7 As shown, fault characteristic quantities under three fault types All values ​​show a significant increasing trend with the increase of the number of short-circuit turns, indicating that this characteristic quantity has good sensitivity to the degree of fault. Among them, under CWDP conditions... The largest variation was observed in SWDP, followed by SWSP, with relatively smaller variations, indicating significant differences among different fault types. Therefore, It can serve as an important characteristic quantity for distinguishing fault types and assessing the severity of faults.

[0058] in Figure 8 (a) Figure 8 (b) Figure 8 (c) Corresponding to the three fault types SWSP, SWDP and CWDP respectively. Figure 8 (a) Residual phase voltage across winding under SWSP conditions with different short-circuit turns Change pattern diagram Figure 8 (b) represents the phase voltage residual U across the winding under different short-circuit turns conditions under SWDP. MN Change pattern diagram Figure 8 (c) represents the phase voltage residual across the winding under different short-circuit turns conditions in CWDP. Chart showing the pattern of change.

[0059] like Figure 8 As shown, the residual voltage across the winding under the three fault types The change in voltage residuals can be used to determine the number of faulty phases. Under SWSP conditions, only one inter-winding phase voltage residual changes significantly; under SWDP and CWDP conditions, both show significant changes in the inter-winding phase voltage residuals. Therefore, Primarily used to distinguish between single-phase and two-phase faults, it can be combined with... Figure 7 In Based on the variations in different windings, we can further distinguish between two types of faults: SWDP and CWDP.

[0060] like Figure 9 As shown, under the premise that the fault exists, the faulty phase is accurately located. When different phases experience faults, the characteristic quantity of the second harmonic proportion of their corresponding phases is also shown. It is significantly higher than other phases, exhibiting obvious phase-sensitive characteristics. Under single-phase fault conditions, only the faulty phase... Significantly increased; under two-phase fault conditions, the two phases corresponding to the fault... At the same time, it increases significantly. Therefore, by comparing each phase... The relative size of the phase can be used to accurately locate the faulty phase.

[0061] First, the fault disrupts the system's symmetry, resulting in a residual voltage across the windings. The changes are significant, and the magnitude of these changes reflects the number of faulty phases. Secondly, the fault propagates within the windings, causing residual voltage differences within the same winding. The variation, and its range, are used to distinguish whether it is a cross-winding fault; finally, the fault introduces nonlinear distortion, resulting in a higher proportion of second harmonics. The fault phase increases significantly, thus enabling fault phase localization. Through the layer-by-layer discrimination of the above three types of characteristic quantities, accurate identification of the fault type and fault phase is achieved.

[0062] During the input phase, a fault threshold μ, fault type discrimination weights ω1 and ω2, and fault phase location weights are set. ,in , .

[0063] The fault threshold μ is determined by substituting the calculated feature values ​​of the motor under normal conditions into the fault type discrimination model.

[0064] The fault type discrimination weights ω1 and ω2 are determined according to... and Determine the sensitivity to faults and set... =0.6, ω2=0.4.

[0065] The fault phase location weight in accordance with , and Sensitivity to faulty phase determined, settings .

[0066] like Figure 10 , Figure 11 , Figure 12 The figure shows the experimental waveforms of the six-phase voltage of the motor under normal, SWSP and CWDP conditions. After processing the data with fast Fourier transform, the magnitude of each fault characteristic quantity is calculated. The algorithm can accurately distinguish the fault type and locate the fault phase, verifying the effectiveness of the algorithm.

[0067] Figure 13 The figure shows a comparison of the distribution of the fault discrimination model coefficients λ under different fault conditions. After the fault occurs, the value of λ exceeds the fault threshold μ, which verifies that the algorithm can accurately determine the occurrence of the fault.

[0068] Figure 14 For the fault phase location model coefficients η under SWSP conditions x Comparing the graphs, the value of ηA is ranked first, so it can be determined that phase A is the faulty phase, verifying that the algorithm can accurately locate the faulty phase.

[0069] Fault characteristic data under different short-circuit turn numbers are obtained through finite element simulation or experimental calibration, and a mapping relationship model between fault characteristic quantities and short-circuit turn numbers is established based on the data.

[0070] By fully considering the impact of operating conditions such as speed and number of short-circuit turns on the voltage signal through finite element analysis, and combining it with fast Fourier transform to extract multi-dimensional fault features, the robustness of diagnosis is improved. With the help of multi-feature fusion design of fault type discrimination coefficient and fault phase location coefficient, the fault type can be accurately distinguished, the fault phase can be located and the fault degree can be assessed. High-precision diagnosis can be achieved without complex and redundant algorithms, which not only improves the accuracy and reliability of fault diagnosis, but also reduces the complexity of diagnosis. It is suitable for the operation scenarios of dual three-phase permanent magnet vernier generators with high requirements for fault diagnosis accuracy.

[0071] The second aspect of this invention discloses a diagnostic system for inter-turn short-circuit faults in a dual three-phase vernier generator, such as... Figure 15 As shown, it includes: a signal acquisition module, used to acquire the phase voltage signals of the six-phase windings of the dual three-phase vernier generator, and to perform a fast Fourier transform on the phase voltage signals to extract the fundamental amplitude and second harmonic amplitude of each phase.

[0072] The signal processing module is used to construct fault characteristic quantities based on the phase voltage signal, the fault characteristic quantities including the phase voltage residuals in the same winding. Phase voltage residual across windings and the proportion of second harmonic content .

[0073] The feature construction module is used to fuse the fault feature quantities according to preset weights and calculate the fault type discrimination coefficient. and will be related to the fault threshold When comparing, At that time, the generator is determined to be in an inter-turn short-circuit fault state; The fault detection module is used to determine a fault state based on the aforementioned... and The changing combination relationship is used to identify the fault type, which includes single-winding single-phase fault (SWSP), single-winding two-phase fault (SWDP), and cross-winding two-phase fault (CWDP). The fault location module is used to locate the fault based on the , as well as Calculate the fault location coefficient for each phase. and according to The magnitude determines the location of the faulty phase; The fault assessment module is used to substitute the voltage characteristics of the faulty phase into the preset fault severity assessment model, calculate the number of short-circuit turns or equivalent fault severity parameters, and output the fault type, faulty phase location and fault severity.

[0074] The signal processing module includes a Fast Fourier Transform unit. The system is deployed in a dual three-phase vernier generator controller or an online monitoring device.

[0075] The technical effects achieved by this invention are as follows: First, by constructing a multi-feature fusion mechanism of phase voltage residual in the same winding, phase voltage residual across windings, and the proportion of second harmonic content, and by adopting a weighted strategy for discrimination and localization, the characteristic responses corresponding to different fault types have obvious distinguishability, thereby significantly improving the identification accuracy of inter-turn short-circuit faults.

[0076] Secondly, the influence of speed variation and short-circuit turn number variation on voltage signal is considered in combination with finite element analysis. By synergistic fusion of multiple features, the influence of single feature on operating condition disturbance is reduced, so that the diagnostic results remain stable under different operating conditions and the anti-interference capability of the system is improved.

[0077] Furthermore, by constructing fault type discrimination coefficients and fault phase location coefficients, the system can effectively distinguish between single-phase faults in a single winding, two-phase faults in a single winding, and two-phase faults across windings based on the characteristic combination variation relationship. At the same time, it can accurately determine the location of the specific fault phase, thereby improving the precision of diagnosis.

[0078] Finally, by establishing a fitting relationship model between fault voltage characteristics and the number of short-circuit turns, a quantitative assessment of the degree of inter-turn short-circuit faults can be achieved. This not only determines whether a fault has occurred but also reflects the severity of the fault, providing a basis for subsequent maintenance decisions.

[0079] The raw materials and instruments used in the examples are not subject to any specific restrictions on their source; they can be purchased from the market or prepared according to conventional methods known to those skilled in the art.

[0080] The foregoing description of specific exemplary embodiments of the invention is for illustrative and explanatory purposes. These descriptions are not intended to limit the invention to the precise forms disclosed, and it will be apparent that many changes and variations can be made in accordance with the foregoing teachings. The exemplary embodiments were chosen and described in order to explain the specific principles of the invention and its practical application, thereby enabling those skilled in the art to implement and utilize various different exemplary embodiments of the invention, as well as various different choices and variations. The scope of the invention is intended to be defined by the claims and their equivalents.

Claims

1. A method for diagnosing inter-turn short-circuit faults in a dual three-phase vernier generator, characterized in that, The method includes: S1: Acquire the phase voltage signals of the six-phase windings of the dual three-phase vernier generator, and perform a fast Fourier transform on the phase voltage signals to extract the fundamental amplitude and second harmonic amplitude of each phase. S2: Construct a set of fault characteristic quantities based on the phase voltage signal, including the phase voltage residual of the same winding. Used to characterize the voltage difference between phases within the same three-phase winding; phase voltage residual across windings. Used to characterize the difference between corresponding phase voltages of two sets of three-phase windings; second harmonic content ratio , which is the ratio of the second harmonic amplitude of each phase voltage to the fundamental amplitude; S3: The above and According to the first weight combination Weighted fusion is performed to obtain the fault type discrimination coefficient. and will With fault threshold When comparing, If the condition is normal, it is determined to be an inter-turn short circuit fault state; otherwise, it is determined to be a normal state. S4: After determining the inter-turn short-circuit fault condition, according to the above... and Combinations exceeding the corresponding preset thresholds are used to identify fault types, including single-winding single-phase fault (SWSP), single-winding two-phase fault (SWDP), and cross-winding two-phase fault (CWDP). S5: Calculate the residual voltage of the corresponding phase voltages in the same winding. Phase voltage residual across windings and the proportion of second harmonic content According to the second weighted combination coefficient Weighted fusion is performed to obtain the fault location coefficients for each phase. and according to The size determines the location of the fault phase. S6: Construct a fault severity assessment model based on the fault phase voltage characteristics and its second harmonic components, calculate the number of short-circuit turns or equivalent fault severity parameters, and output the fault type, fault phase location and fault severity. The first weight combination is used to characterize fault discrimination sensitive features, the second weight combination is used to characterize fault location sensitive features, and the first weight combination and the second weight combination are set independently for different diagnostic targets to achieve differentiated fusion of multiple features in the fault discrimination and fault location process.

2. The method according to claim 1, characterized in that, The proportion of second harmonic content It is the ratio of the second harmonic amplitude of the x-th phase voltage to the fundamental amplitude.

3. The method according to claim 1, characterized in that, The phase voltage residual of the same winding The phase voltage residual across the winding is a function of the difference in voltage amplitude between any two phases within the same three-phase winding. It is a function of the difference in phase voltage amplitude between the two sets of three-phase windings.

4. The method according to claim 1, characterized in that, The fault type discrimination coefficient Depend on and By weight The calculation is as follows: in, This is the first weighting coefficient.

5. The method according to claim 1, characterized in that, The fault threshold Based on the fault category discrimination coefficient under normal operating conditions The statistical distribution is determined.

6. The method according to claim 1, characterized in that, In step S4, the fault type discrimination rules include: When there is only one set of windings Greater than the first preset threshold, and only one If the value exceeds the second preset threshold, it is determined to be SWSP; When there is only one set of windings Greater than the first preset threshold, and two If the value exceeds the second preset threshold, it is determined to be SWDP; When two sets of windings Both are greater than the first preset threshold, and both If the value exceeds the second preset threshold, it is determined to be CWDP.

7. The method according to claim 1, characterized in that, The fault phase location coefficient Depend on , and According to the second weight The weighted fusion calculation is as follows: in, This is the second weighted combination coefficient.

8. The method according to claim 1, characterized in that, The fault severity assessment model is a multi-parameter fitting model constructed based on the correspondence between the voltage amplitude of the fault phase and the amplitude of the second harmonic under different short-circuit turns conditions obtained by finite element simulation. It is used to determine the number of short-circuit turns or the fault severity based on actual measurement data.

9. The method according to claim 1, characterized in that, The first weight combination coefficients satisfy: The second weighted combination coefficients satisfy: .

10. A diagnostic system for inter-turn short-circuit faults in a dual three-phase vernier generator, characterized in that, include: The signal acquisition module is used to acquire the phase voltage signals of the six-phase windings of the dual three-phase vernier generator and extract the fundamental amplitude and second harmonic amplitude of each phase. The signal processing module is used to construct the phase voltage residuals of the same winding. Phase voltage residual across windings and the proportion of second harmonic content ; The feature construction module is used to calculate the fault type discrimination coefficient. and will be related to the fault threshold Comparison is used to determine the fault status; The fault diagnosis module is used to determine the fault based on the above. and Threshold combinations are used to determine fault types; The fault location module is used to calculate the fault location coefficient for each phase. And determine the location of the faulty phase; The fault assessment module is used to calculate the number of short-circuit turns or fault severity parameters and output diagnostic results.

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