The effect of excitation current intensity on the mechanical properties of ZL205 A castings solidified under a traveling magnetic field was studied. The results of the experiment indicate that the excitation current i...The effect of excitation current intensity on the mechanical properties of ZL205 A castings solidified under a traveling magnetic field was studied. The results of the experiment indicate that the excitation current intensity of the traveling magnetic field has a great influence on the mechanical properties of the ZL205 A castings. When the excitation current intensity is 15 A, the tensile strength and elongation of ZL205 A alloy castings increase 27.2% and 67.7%, respectively, compared with those of the same alloy solidified under gravity. The improvement of mechanical properties is attributed to the decrease of micro-porosity in the alloy. Under the traveling magnetic field, the feeding pressure in the alloy melt before solidification can be enhanced due to the electromagnetic force. Moreover, the melt flow induced by the traveling magnetic field can decrease the temperature gradient. The feeding resistance will be increased because the temperature gradient decrease. So traveling magnetic field has an optimum effect on feeding.展开更多
The power factor is the ratio between the active and apparent power,and it is available to determine the operational capability of the intended circuit or the parts.The excitation current of the synchronous motor is a...The power factor is the ratio between the active and apparent power,and it is available to determine the operational capability of the intended circuit or the parts.The excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether the motor is under the optimal operating status.Although the excitation current should predict with the experimental devices,such a method is unsuitable for online real-time prediction.The artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the model optimization is compared during the research process.In this article,the load current,power factor,and power factor errors available in the existing dataset are used as the input parameters for training the proposed artificial intelligence algorithms to select the optimal algorithm according to the training result,for this algorithm to have higher accuracy.The SMOGN(Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise)is selected for the research by which the data and the MFO(Moth-flame optimization algorithm)are created for the model to adjust and optimize the parameters automatically.In addition to enhancing the prediction accuracy for the excitation current,the automatic parameter adjusting method also allows the researchers not specializing in the professional algorithm to apply such application method more efficiently.The final result indicated that the prediction accuracy has reached“Mean Absolute Error(MAE)=0.0057,Root Mean Square Error(RMSE)=0.0093 andR2 score=0.9973”.Applying this method to themotor control would be much easier for the power factor adjustment in the future because it allows the motor to operate under the optimal power status to reduce energy consumption while enhancing working efficiency.展开更多
A differential excitation probe based on eddy current testing technology was designed. Sheet specimens of Q 235 steel with prefabricated micro-cracks of different widths and of aluminum with prefabricated micro-cracks...A differential excitation probe based on eddy current testing technology was designed. Sheet specimens of Q 235 steel with prefabricated micro-cracks of different widths and of aluminum with prefabricated micro-cracks of different depths were detected through the designed detection system. The characteristics of micro-cracks can be clearly showed after signals processing through the short-time Fourier transform（ STFT）. By changing the parameter and its value in detecting process,the factors including the excitation frequency and amplitude,the lift-off effect and the scanning direction were discussed,respectively. The results showed that the differential excitation probe was insensitive to dimension and surface state of the tested specimen,while it had a high degree of recognition for micro-crack detection. Therefore,when the differential excitation detection technology was used for inspecting micro-crack of turbine blade in aero-engine,and smoothed pseudo Wigner-Ville distribution was used for signal processing,micro-cracks of 0. 3 mm depth and 0. 1 mm width could be identified. The experimental results might be useful for further research on engineering test of turbine blades of aero-engine.展开更多
In deep drilling applications,such as those for geothermal energy,there are many challenges,such as those related to efficient operation of the drilling fluid(mud)pumping system.Legacy drilling rigs often use paired,p...In deep drilling applications,such as those for geothermal energy,there are many challenges,such as those related to efficient operation of the drilling fluid(mud)pumping system.Legacy drilling rigs often use paired,parallel-connected independent-excitation direct-current(DC)motors for mud pumps,that are supplied by a single power converter.This configuration results in electrical power imbalance,thus reducing its efficiency.This paper investigates this power imbalance issue in such legacy DC mud pump drive systems and offers an innovative solution in the form of a closed-loop control system for electrical load balancing.The paper first analyzes the drilling fluid circulation and electrical drive layout to develop an analytical model that can be used for electrical load balancing and related energy efficiency improvements.Based on this analysis,a feedback control system(so-called“current mirror”control system)is designed to balance the electrical load(i.e.,armature currents)of parallel-connected DC machines by adjusting the excitation current of one of the DC machines,thus mitigating the power imbalance of the electrical drive.Theproposed control systemeffectiveness has been validated,first through simulations,followed by experimental testing on a deep drilling rig during commissioning and field tests.The results demonstrate the practical viability of the proposed“current mirror”control system that can effectively and rather quickly equalize the armature currents of both DC machines in a parallel-connected electrical drive,and thus balance both the electrical and mechanical load of individual DC machines under realistic operating conditions of the mud pump electrical drive.展开更多
Large-scale synchronous condenser (LSC) has a broad application prospect in China's ultra-high voltage direct current (UHVDC) to provide dynamic reactive power. Loss of excitation (LOE) is an important grid-relate...Large-scale synchronous condenser (LSC) has a broad application prospect in China's ultra-high voltage direct current (UHVDC) to provide dynamic reactive power. Loss of excitation (LOE) is an important grid-related fault of LSC, resulting in uncontrolled reactive power consumption. However, due to the un obvious fault feature and UHVDC's diverse reactive power demands, LSC's LOE protection faces challenges in criterion and action mode configurations. Thus, this paper proposes a complete LOE protection strategy for the LSC used in UHVDC, including effective criterion and proper action mode. First, the defect of existing reverse reactive power-based protection is presented through an in-depth analysis of the LOE LSC's reactive power behavior. Then, excitation current difference between the measured value and equivalent actual value is identified as the new fault feature. Compared with existing reverse reactive power features which also appear in healthy LSC's leading phase conditions, this current difference feature only appears in the LO E process and thus is more typical. Since actual excitation current is unmeasurable in practice, an estimation model is built and validated by experiment and simulation. Moreover, the novel LOE protection strategy including current-based criterion and improved action mode is proposed. Through comparative simulation studies in PSCADIEMTDC, the novel protection exhibits superior performances compared to existing protection in LOE detection and commutation failure immunity improvement, as well as overvoltage suppression.展开更多
By applying ultrasonic-MIG welding as research object, the behaviors of welding arc were analyzed with varied ultrasonic parameters in welding using arc images recorded by high-speed camera. The influences of the curr...By applying ultrasonic-MIG welding as research object, the behaviors of welding arc were analyzed with varied ultrasonic parameters in welding using arc images recorded by high-speed camera. The influences of the current by exciting ultrasonic and the height and shape of ultrasonic radiator on welding arc were studied. Results showed that when the current was 150 mA, ultrasonic showed most distinct compressive effect on arc. The compressive volumes of arc length at different heights were calculated by adjusting the height of ultrasonic radiator continuously from 10 mm to 35 mm, there were three maximum points. The compressive degrees of them reduced successively. By utilizing different shapes of ultrasonic radiator, it revealed that ultrasonic radiator with spherical crown surface showed better compressive effect in a larger welding standard scope. When radius of radiator increased, axial compressive volume of arc enlarged, while an increasing curvature radius led to mare distinct radial compression of arc.展开更多
This study establishes for the first time a P2D-coupled non-ideal double-layer capacitor model(P2D-CNIC),which can be used for mechanism analysis under high-frequency periodic signal excitation.The novelty of this wor...This study establishes for the first time a P2D-coupled non-ideal double-layer capacitor model(P2D-CNIC),which can be used for mechanism analysis under high-frequency periodic signal excitation.The novelty of this work is the consideration of the generally neglected electric double-layer capacitance and its dispersion effects,especially the capacitance of the solid electrolyte interface(SEI)film.The dispersion effect of the model is verified by a periodic current excitation signal and the corresponding phase change in the voltage response.Under sinusoidal alternating current(AC)excitation,a comparative analysis was conducted between the traditional P2D model,the traditional P2D model coupled with the ideal double-layer capacitor(P2D-CIC),and the proposed P2D-CNIC mechanism model.Furthermore,three models were evaluated under periodic short-circuit pulse discharge conditions to verify the accuracy and reliability of P2D-CNIC.The simulation results are used to analyze the dominant order of faradaic and non-Faraday processes under sinusoidal AC excitation,thereby providing insights into the internal mechanism analysis of lithium batteries under high-frequency cycling conditions.展开更多
Artificial intelligence(AI)can potentially improve the reliability of transformer protection by fusing multiple features.However,owing to the data scarcity of inrush current and internal fault,the existing methods fac...Artificial intelligence(AI)can potentially improve the reliability of transformer protection by fusing multiple features.However,owing to the data scarcity of inrush current and internal fault,the existing methods face the problem of poor generalizability.In this paper,a denoising-classification neural network(DCNN)is proposed,one which inte-grates a convolutional auto-encoder(CAE)and a convolutional neural network(CNN),and is used to develop a reli-able transformer protection scheme by identifying the exciting voltage-differential current curve(VICur).In the DCNN,CAE shares its encoder part with the CNN,where the CNN combines the encoder and a classifier.Based on the inter-action of the CAE reconstruction process and the CNN classification process,the CAE regards the saturated features of the VICur as noise and removes them accurately.Consequently,it guides CNN to focus on the unsaturated features of the VICur.The unsaturated part of the VICur approximates an ellipse,and this significantly differentiates between a healthy and faulty transformer.Therefore,the unsaturated features extracted by the CNN help to decrease the data ergodicity requirement of AI and improve the generalizability.Finally,a CNN which is trained well by the DCNN is used to develop a protection scheme.PSCAD simulations and dynamic model experiments verify its superior performance.展开更多
基金financially supported by the National Basic Research Program of China(2011CB610406)the Natural Science Foundation of Hei Longjiang Province(JC201209)the National Natural Science Foundation of China(51425402)
文摘The effect of excitation current intensity on the mechanical properties of ZL205 A castings solidified under a traveling magnetic field was studied. The results of the experiment indicate that the excitation current intensity of the traveling magnetic field has a great influence on the mechanical properties of the ZL205 A castings. When the excitation current intensity is 15 A, the tensile strength and elongation of ZL205 A alloy castings increase 27.2% and 67.7%, respectively, compared with those of the same alloy solidified under gravity. The improvement of mechanical properties is attributed to the decrease of micro-porosity in the alloy. Under the traveling magnetic field, the feeding pressure in the alloy melt before solidification can be enhanced due to the electromagnetic force. Moreover, the melt flow induced by the traveling magnetic field can decrease the temperature gradient. The feeding resistance will be increased because the temperature gradient decrease. So traveling magnetic field has an optimum effect on feeding.
基金This work was supported by the Ministry of Science and Technology,Taiwan,under Grants MOST 110-2221-E-194-037,NSTC 111-2823-8-194-002,111-2221-E-194-052 and 11-2218-E-194-007。
文摘The power factor is the ratio between the active and apparent power,and it is available to determine the operational capability of the intended circuit or the parts.The excitation current of the synchronous motor is an essential parameter required for adjusting the power factor because it determines whether the motor is under the optimal operating status.Although the excitation current should predict with the experimental devices,such a method is unsuitable for online real-time prediction.The artificial intelligence algorithm can compensate for the defect of conventional measurement methods requiring the measuring devices and the model optimization is compared during the research process.In this article,the load current,power factor,and power factor errors available in the existing dataset are used as the input parameters for training the proposed artificial intelligence algorithms to select the optimal algorithm according to the training result,for this algorithm to have higher accuracy.The SMOGN(Synthetic Minority Over-Sampling Technique for Regression with Gaussian Noise)is selected for the research by which the data and the MFO(Moth-flame optimization algorithm)are created for the model to adjust and optimize the parameters automatically.In addition to enhancing the prediction accuracy for the excitation current,the automatic parameter adjusting method also allows the researchers not specializing in the professional algorithm to apply such application method more efficiently.The final result indicated that the prediction accuracy has reached“Mean Absolute Error(MAE)=0.0057,Root Mean Square Error(RMSE)=0.0093 andR2 score=0.9973”.Applying this method to themotor control would be much easier for the power factor adjustment in the future because it allows the motor to operate under the optimal power status to reduce energy consumption while enhancing working efficiency.
基金Supported by the Ministerial Level Advanced Research Foundation(051317030586)Ph.D.Programs Foundation of the Ministry of Education of China(20121101110018)
文摘A differential excitation probe based on eddy current testing technology was designed. Sheet specimens of Q 235 steel with prefabricated micro-cracks of different widths and of aluminum with prefabricated micro-cracks of different depths were detected through the designed detection system. The characteristics of micro-cracks can be clearly showed after signals processing through the short-time Fourier transform（ STFT）. By changing the parameter and its value in detecting process,the factors including the excitation frequency and amplitude,the lift-off effect and the scanning direction were discussed,respectively. The results showed that the differential excitation probe was insensitive to dimension and surface state of the tested specimen,while it had a high degree of recognition for micro-crack detection. Therefore,when the differential excitation detection technology was used for inspecting micro-crack of turbine blade in aero-engine,and smoothed pseudo Wigner-Ville distribution was used for signal processing,micro-cracks of 0. 3 mm depth and 0. 1 mm width could be identified. The experimental results might be useful for further research on engineering test of turbine blades of aero-engine.
文摘In deep drilling applications,such as those for geothermal energy,there are many challenges,such as those related to efficient operation of the drilling fluid(mud)pumping system.Legacy drilling rigs often use paired,parallel-connected independent-excitation direct-current(DC)motors for mud pumps,that are supplied by a single power converter.This configuration results in electrical power imbalance,thus reducing its efficiency.This paper investigates this power imbalance issue in such legacy DC mud pump drive systems and offers an innovative solution in the form of a closed-loop control system for electrical load balancing.The paper first analyzes the drilling fluid circulation and electrical drive layout to develop an analytical model that can be used for electrical load balancing and related energy efficiency improvements.Based on this analysis,a feedback control system(so-called“current mirror”control system)is designed to balance the electrical load(i.e.,armature currents)of parallel-connected DC machines by adjusting the excitation current of one of the DC machines,thus mitigating the power imbalance of the electrical drive.Theproposed control systemeffectiveness has been validated,first through simulations,followed by experimental testing on a deep drilling rig during commissioning and field tests.The results demonstrate the practical viability of the proposed“current mirror”control system that can effectively and rather quickly equalize the armature currents of both DC machines in a parallel-connected electrical drive,and thus balance both the electrical and mechanical load of individual DC machines under realistic operating conditions of the mud pump electrical drive.
文摘Large-scale synchronous condenser (LSC) has a broad application prospect in China's ultra-high voltage direct current (UHVDC) to provide dynamic reactive power. Loss of excitation (LOE) is an important grid-related fault of LSC, resulting in uncontrolled reactive power consumption. However, due to the un obvious fault feature and UHVDC's diverse reactive power demands, LSC's LOE protection faces challenges in criterion and action mode configurations. Thus, this paper proposes a complete LOE protection strategy for the LSC used in UHVDC, including effective criterion and proper action mode. First, the defect of existing reverse reactive power-based protection is presented through an in-depth analysis of the LOE LSC's reactive power behavior. Then, excitation current difference between the measured value and equivalent actual value is identified as the new fault feature. Compared with existing reverse reactive power features which also appear in healthy LSC's leading phase conditions, this current difference feature only appears in the LO E process and thus is more typical. Since actual excitation current is unmeasurable in practice, an estimation model is built and validated by experiment and simulation. Moreover, the novel LOE protection strategy including current-based criterion and improved action mode is proposed. Through comparative simulation studies in PSCADIEMTDC, the novel protection exhibits superior performances compared to existing protection in LOE detection and commutation failure immunity improvement, as well as overvoltage suppression.
基金This study was supported by National Natural Science Foundation of China （Grant No. 51275134） and the Key Program of the National Natural Science Foundation of China （Grant No. 51435004）.
文摘By applying ultrasonic-MIG welding as research object, the behaviors of welding arc were analyzed with varied ultrasonic parameters in welding using arc images recorded by high-speed camera. The influences of the current by exciting ultrasonic and the height and shape of ultrasonic radiator on welding arc were studied. Results showed that when the current was 150 mA, ultrasonic showed most distinct compressive effect on arc. The compressive volumes of arc length at different heights were calculated by adjusting the height of ultrasonic radiator continuously from 10 mm to 35 mm, there were three maximum points. The compressive degrees of them reduced successively. By utilizing different shapes of ultrasonic radiator, it revealed that ultrasonic radiator with spherical crown surface showed better compressive effect in a larger welding standard scope. When radius of radiator increased, axial compressive volume of arc enlarged, while an increasing curvature radius led to mare distinct radial compression of arc.
基金supported by the National Natural Science Foundation of China(grant no.52177206)the Joint Funds of Equipment Pre-Research and Ministry of Education of China(grant no.8091B022130).
文摘This study establishes for the first time a P2D-coupled non-ideal double-layer capacitor model(P2D-CNIC),which can be used for mechanism analysis under high-frequency periodic signal excitation.The novelty of this work is the consideration of the generally neglected electric double-layer capacitance and its dispersion effects,especially the capacitance of the solid electrolyte interface(SEI)film.The dispersion effect of the model is verified by a periodic current excitation signal and the corresponding phase change in the voltage response.Under sinusoidal alternating current(AC)excitation,a comparative analysis was conducted between the traditional P2D model,the traditional P2D model coupled with the ideal double-layer capacitor(P2D-CIC),and the proposed P2D-CNIC mechanism model.Furthermore,three models were evaluated under periodic short-circuit pulse discharge conditions to verify the accuracy and reliability of P2D-CNIC.The simulation results are used to analyze the dominant order of faradaic and non-Faraday processes under sinusoidal AC excitation,thereby providing insights into the internal mechanism analysis of lithium batteries under high-frequency cycling conditions.
基金supported by the National Natural Science Foundation of China (Grant No.:20210333).
文摘Artificial intelligence(AI)can potentially improve the reliability of transformer protection by fusing multiple features.However,owing to the data scarcity of inrush current and internal fault,the existing methods face the problem of poor generalizability.In this paper,a denoising-classification neural network(DCNN)is proposed,one which inte-grates a convolutional auto-encoder(CAE)and a convolutional neural network(CNN),and is used to develop a reli-able transformer protection scheme by identifying the exciting voltage-differential current curve(VICur).In the DCNN,CAE shares its encoder part with the CNN,where the CNN combines the encoder and a classifier.Based on the inter-action of the CAE reconstruction process and the CNN classification process,the CAE regards the saturated features of the VICur as noise and removes them accurately.Consequently,it guides CNN to focus on the unsaturated features of the VICur.The unsaturated part of the VICur approximates an ellipse,and this significantly differentiates between a healthy and faulty transformer.Therefore,the unsaturated features extracted by the CNN help to decrease the data ergodicity requirement of AI and improve the generalizability.Finally,a CNN which is trained well by the DCNN is used to develop a protection scheme.PSCAD simulations and dynamic model experiments verify its superior performance.
