41 research outputs found

    Flexible fault-tolerant topology for switched reluctance motor drives

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    Switched reluctance motor (SRM) drives are one competitive technology for traction motor drives. This paper proposes a novel and flexible SRM fault-tolerant topology with fault diagnosis, fault tolerance, and advanced control functions. The converter is composed of a single-phase bridge and a relay network, based on the traditional asymmetrical half-bridge driving topology. When the SRM-driving system is subjected to fault conditions including open-circuit and short-circuit faults, the proposed converter starts its fault-diagnosis procedure to locate the fault. Based on the relay network, the faulty part can be bypassed by the single-phase bridge arm, while the single-phase bridge arm and the healthy part of the converter can form a fault-tolerant topology to sustain the driving operation. A fault-tolerant control strategy is developed to decrease the influence of the fault. Furthermore, the proposed fault-tolerant strategy can be applied to three-phase 12/8 SRM and four-phase 8/6 SRM. Simulation results in MATLAB/Simulink and experiments on a three-phase 12/8 SRM and a four-phase 8/6 SRM validate the effectiveness of the proposed strategy, which may have significant economic implications in traction drive systems

    Landslide displacement prediction from on-site deformation data based on time series ARIMA model

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    Time series Autoregressive Integrated Moving Average (ARIMA) model is often used in landslide prediction and forecasting. However, few conditions have been suggested for the application of ARIMA models in landslide displacement prediction. This paper summarizes the distribution law of the tangential angle in different time periods and analyzes the landslide displacement data by combining wavelet transform. It proposes an applicable condition for the ARIMA model in the field of landslide prediction: when the landslide deformation is in the initial deformation to initial acceleration stage, i.e., the tangential angle of landslide displacement is less than 80°, the ARIMA model has higher prediction accuracy for 24-h landslide displacement data. The prediction results are RMSE = 4.52 mm and MAPE = 2.39%, and the prediction error increases gradually with time. Meanwhile, the ARIMA model was used to predict the 24-h displacements from initial deformation to initial acceleration deformation for the landslide in Guangna Township and the landslide in Libian Gully, and the prediction results were RMSE = 1.24 mm, MAPE = 1.34% and RMSE = 5.43 mm, MAPE = 1.67%, which still maintained high accuracy and thus verified this applicable condition. At the same time, taking the landslide of Libian Gully as an example, the ARIMA model was used to test the displacement prediction effect of the landslide in the Medium-term acceleration stage and the Imminent sliding stage (the tangential angle of landslide displacement is 80° and 85°, respectively). The relative error of displacement data prediction in the Medium-term acceleration stage is within 3%, while the relative error of the prediction value in the Imminent sliding stage is more than 3%, and the error gradually increases with time. This demonstrates that the relative error of the ARIMA model in landslide prediction and forecasting is within 3%. The relative error of the prediction value in the Imminent sliding stage is above 3%, and the error increases gradually with time. Meanwhile, the prediction results are analyzed and it is concluded that the increase in prediction time and tangential angles are the main reasons for the increase in error. The applicable conditions proposed in this study can provide a reference for the application of ARIMA model in landslide prediction and forecast

    Emergency tracheal intubation in 202 patients with COVID-19 in Wuhan, China:lessons learnt and international expert recommendations

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    Tracheal intubation in coronavirus disease 2019 (COVID-19) patients creates a risk to physiologically compromised patients and to attending healthcare providers. Clinical information on airway management and expert recommendations in these patients are urgently needed. By analysing a two-centre retrospective observational case series from Wuhan, China, a panel of international airway management experts discussed the results and formulated consensus recommendations for the management of tracheal intubation in COVID-19 patients. Of 202 COVID-19 patients undergoing emergency tracheal intubation, most were males (n=136; 67.3%) and aged 65 yr or more (n=128; 63.4%). Most patients (n=152; 75.2%) were hypoxaemic (Sao2 <90%) before intubation. Personal protective equipment was worn by all intubating healthcare workers. Rapid sequence induction (RSI) or modified RSI was used with an intubation success rate of 89.1% on the first attempt and 100% overall. Hypoxaemia (Sao2 <90%) was common during intubation (n=148; 73.3%). Hypotension (arterial pressure <90/60 mm Hg) occurred in 36 (17.8%) patients during and 45 (22.3%) after intubation with cardiac arrest in four (2.0%). Pneumothorax occurred in 12 (5.9%) patients and death within 24 h in 21 (10.4%). Up to 14 days post-procedure, there was no evidence of cross infection in the anaesthesiologists who intubated the COVID-19 patients. Based on clinical information and expert recommendation, we propose detailed planning, strategy, and methods for tracheal intubation in COVID-19 patients

    Ultrasound-guided phrenic nerve block for intraoperative persistent hiccups: a case report

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    Abstract Background Continuous hiccups during surgery not only affect the surgical procedure, they can also cause adverse effects for the patient. Apart from active investigation of the cause of the hiccups, their timely termination is also necessary. Case presentation We reported a case of a 70-year-old woman with continuous intraoperative hiccups that appeared during vaginal hysterectomy under low continuous epidural anesthesia. After the ineffectiveness CO2 repeated inhalation and intravenous administration of chlorpromazine and methoxychlorpromide, we performed unilateral phrenic nerve block under ultrasound guidance. Hiccups were terminated without any related complications. Conclusions During intraoperative continuous hiccups, ultrasound guided phrenic nerve block may be a suitable treatment option when physical methods and drug therapy are not effective. However, given the absence of a vital risk related to hiccups, this block should imply the complete absence of any respiratory contraindication and a prolonged postoperative respiratory monitoring

    Effective Viscosity in Porous Media and Applicable Limitations for Polymer Flooding of an Associative Polymer

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    Hydrophobically associating polyacrylamide (HAPAM) is considered to be a promising candidate for polymer flooding because of its excellent apparent viscosifying capability. Compared with partially hydrolyzed polyacrylamide (HPAM), the resistance factor and residual resistance factor caused by HAPAM tend to be higher. However, the effective viscosity of HAPAM is lower than that of conventional polymer at a concentration of 2 000 mg/L. The dynamic retention capacity of HAPAM is about 2.3 times that of HPAM. The oil displacement efficiency of HAPAM is lower than that of conventional polymer at a concentration of 2 000 mg/L in the homogeneous sandpack model. The oil displacement efficiency of HAPAM is higher than that of HPAM only in the heterogeneous model (permeability ratio 2.8). Neither high nor low permeability ratios are good for the oil displacement efficiency of HAPAM

    Automated Detection Method to Extract <i>Pedicularis</i> Based on UAV Images

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    Pedicularis has adverse effects on vegetation growth and ecological functions, causing serious harm to animal husbandry. In this paper, an automated detection method is proposed to extract Pedicularis and reveal the spatial distribution. Based on unmanned aerial vehicle (UAV) images, this paper adopts logistic regression, support vector machine (SVM), and random forest classifiers for multi-class classification. One-class SVM (OCSVM), isolation forest, and positive and unlabeled learning (PUL) algorithms are used for one-class classification. The results are as follows: (1) The accuracy of multi-class classifiers is better than that of one-class classifiers, but it requires all classes that occur in the image to be exhaustively assigned labels. Among the one-class classifiers that only need to label positive or positive and labeled data, the PUL has the highest F score of 0.9878. (2) PUL performs the most robustly to change features in one-class classifiers. All one-class classifiers prove that the green band is essential for extracting Pedicularis. (3) The parameters of the PUL are easy to tune, and the training time is easy to control. Therefore, PUL is a promising one-class classification method for Pedicularis extraction, which can accurately identify the distribution range of Pedicularis to promote grassland administration

    Analysis of price competition in two-tier service systems

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