This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fa...This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.展开更多
The quality of the stator winding coil directly affects the performance of the motor.A dual-camera online machine vision detection method to detect whether the coil leads and winding regions were qualified was designe...The quality of the stator winding coil directly affects the performance of the motor.A dual-camera online machine vision detection method to detect whether the coil leads and winding regions were qualified was designed.A vision detection platform was designed to capture individual winding images,and an image processing algorithm was used for image pre-processing,template matching and positioning of the coil lead area to set up a coordinate system.After eliminating image noise by Blob analysis,the improved Canny algorithm was used to detect the location of the coil lead paint stripped region,and the time was reduced by about half compared to the Canny algorithm.The coil winding region was trained with the ShuffleNet V2-YOLOv5s model for the dataset,and the detect file was converted to the Open Neural Network Exchange(ONNX)model for the detection of winding cross features with an average accuracy of 99.0%.The software interface of the detection system was designed to perform qualified discrimination tests on the workpieces,and the detection data were recorded and statistically analyzed.The results showed that the stator winding coil qualified discrimination accuracy reached 96.2%,and the average detection time of a single workpiece was about 300 ms,while YOLOv5s took less than 30 ms.展开更多
In this study, we tried to improve the performance by giving a pre-swirling flow to the radial inflow that occurred in the semi-opened axial fan. In addition, the flow fields of rotor outlet were clarified experimenta...In this study, we tried to improve the performance by giving a pre-swirling flow to the radial inflow that occurred in the semi-opened axial fan. In addition, the flow fields of rotor outlet were clarified experimentally, and the effect of pre-swirling flow was considered. The experiment was carried out using a performance test wind tunnel with a square cross section of 880 mm. Three types of casings were prepared, in which the blade tip protruded 0%, 20%, and 40% of the meridional chord length. They were called R25, R15, and R05, respectively, in the casing bellmouth model code. Guide blades for generating a pre-swirling flow were installed on the vertical wall surface of the casing. In addition, a vertical wall was installed 60% upstream of the meridional chord length as an obstacle to prevent axial inflow. The velocity fields of the rotor outlet were measured using a hot-wire anemometer. From the results, the pre-swirling flow did not significantly affect the fan performance. When there was no obstacles wall upstream, there was a partial increase in efficiency, but the difference was not so large. When there was an obstacle wall upstream, the efficiency increased overall in the case of R15, but in the case of R05, the efficiency increased only in the low flow rate region, and conversely decreased in the high flow rate region. By observing the blade outlet flow fields when the performance was improved, it was confirmed that the influence of the tip leakage vortex was weakened.展开更多
基金supported in part by the National Natural Science Foundation of China(52177042)Natural Science Foundation of Hebei Province(E2020502031)+1 种基金the Fundamental Research Funds for the Central Universities(2017MS151),Suzhou Social Developing Innovation Project of Science and Technology(SS202134)the Top Youth Talent Support Program of Hebei Province([2018]-27).
文摘This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.
基金National Natural Science Foundation of China(No.U1831123)。
文摘The quality of the stator winding coil directly affects the performance of the motor.A dual-camera online machine vision detection method to detect whether the coil leads and winding regions were qualified was designed.A vision detection platform was designed to capture individual winding images,and an image processing algorithm was used for image pre-processing,template matching and positioning of the coil lead area to set up a coordinate system.After eliminating image noise by Blob analysis,the improved Canny algorithm was used to detect the location of the coil lead paint stripped region,and the time was reduced by about half compared to the Canny algorithm.The coil winding region was trained with the ShuffleNet V2-YOLOv5s model for the dataset,and the detect file was converted to the Open Neural Network Exchange(ONNX)model for the detection of winding cross features with an average accuracy of 99.0%.The software interface of the detection system was designed to perform qualified discrimination tests on the workpieces,and the detection data were recorded and statistically analyzed.The results showed that the stator winding coil qualified discrimination accuracy reached 96.2%,and the average detection time of a single workpiece was about 300 ms,while YOLOv5s took less than 30 ms.
文摘In this study, we tried to improve the performance by giving a pre-swirling flow to the radial inflow that occurred in the semi-opened axial fan. In addition, the flow fields of rotor outlet were clarified experimentally, and the effect of pre-swirling flow was considered. The experiment was carried out using a performance test wind tunnel with a square cross section of 880 mm. Three types of casings were prepared, in which the blade tip protruded 0%, 20%, and 40% of the meridional chord length. They were called R25, R15, and R05, respectively, in the casing bellmouth model code. Guide blades for generating a pre-swirling flow were installed on the vertical wall surface of the casing. In addition, a vertical wall was installed 60% upstream of the meridional chord length as an obstacle to prevent axial inflow. The velocity fields of the rotor outlet were measured using a hot-wire anemometer. From the results, the pre-swirling flow did not significantly affect the fan performance. When there was no obstacles wall upstream, there was a partial increase in efficiency, but the difference was not so large. When there was an obstacle wall upstream, the efficiency increased overall in the case of R15, but in the case of R05, the efficiency increased only in the low flow rate region, and conversely decreased in the high flow rate region. By observing the blade outlet flow fields when the performance was improved, it was confirmed that the influence of the tip leakage vortex was weakened.