高压变压器油面温度计的数字化改造

把火力发电厂220kV主变和13.8kV高厂变的BWY-803A（TH）-288型油面温度计改造为XIN-MMA型油面数控温度显示仪,提高了就地温度显示精度。通过数字化仪表输出接点代替油面温度计的微动开关接点,确保了变压器冷却系统设备控制精度,延长了仪表的校验周期。     

扩声与制作主备音频系统的同步倒换

文章就广播电视设备系统中现场扩声与制作主备音频设备发生故障的各种可能性、现场扩声与制作音频信号的应急同步倒换方式进行了分析,在分享实践的基础上为读者提供一个关于音频安全制作的应用参考和思路。     

应用于TD-SCDMA系统的高线性10W功率放大器设计

针对TD-SCDMA系统的要求,成功设计了TD-SCDMA 10W功率放大器。设计过程中比较了S参数优化设计和大信号LOAD-PULL设计的仿真结果,指出了对于功率放大器,应该按照大信号设计方法进行。最后,依据仿真结果,制作了放大器并进行了测试。     

对变压器线圈端部电场的有限元分析

文章对变压器端部的绝缘做了电场分析,依据许瓦兹的有限长度代替无限远的理论,对变压器的端部绝缘结构作出改进,并对改进后的模型作出了电场分析,通过对比优化前后的电场图得出许瓦兹理论对于改变变压器端部的畸变电场和降低电场的最大值的作用是十分明显的。     

一起35kV变压器线圈短路故障的检测过程及在生产中防范措施

本文,笔者主要结合案例,分析了变压器的线圈短路故障在生产过程中的防范措施。     

脉冲C类固态放大器中偏置馈电电路的研究

对脉冲C类固态放大器中偏置馈电电路部分作一些探讨，研究偏置馈电电路及其供电储能、滤波等，使放大器更稳定可靠地工作。     

An extract-then-abstract based method to generate disaster-news headlines using a DNN extractor followed by a transformer abstractor

Generating news headlines has been one of the predominant problems in Natural Language Processing research. Modern transformer models, if fine-tuned, can present a good headline with attention to all the parts of a disaster-news article. A disaster-news headline generally focuses on the event, its effect, and the major impacts, which a transformer model lacks when generating the headline. The extract-then-abstract based method proposed in this article improves the performance of a state-of-the-art transformer abstractor to generate a good-quality disaster-news headline. In this work, a Deep Neural Network (DNN) based sentence extractor and a transformer-based abstractive summarizer work sequentially to generate a headline. The sentence extraction task is formulated as a binary classification problem where the DNN model is trained to generate two binary labels: one corresponding to the sentence similarity with ground truth headlines and the other corresponding to the presence of disaster and its impact related information in the sentence. The transformer model generates the headline from the sentences extracted by the DNN. ROUGE scores of the headlines generated using the proposed method are found to be better than the scores of the headlines generated directly from the original documents. The highest ROUGE 1, 2, and 3 score improvements are observed in the case of the Text-To-Text Transfer Transformer (T5) model by 17.85%, 38.13%, and 21.01%, respectively. Such improvements suggest that the proposed method can have a high utility for finding effective headlines from disaster related news articles.