摘要
通过对转炉化渣噪声的功率谱进行随机分析,解释了原有音频化渣技术存在的滞后、误报等问题的原因,提出了多特征频段、功率强度-时间曲线互补等结论,确定以加权组合的综合特征函数来监测化渣状态。实验证明,新的噪声分析方法能更加准确地监测化渣状态,能更好地预警喷溅与返干。
Power spectrum of slagging noise in converter is stochastically analyzed. The reason for lagging and misreporting of the existing sonic-slagging technology is explained and some conclusions such as muhi-eigenfrequency and complementary power intensity-time curve are arrived at. It is determined that weighted combination of integrated eigenfunction is used to monitor slagging status. It is proved that the new noise analysis method is more accurate and better to alarm for slag splashing and drying.
出处
《计算机应用与软件》
CSCD
北大核心
2007年第3期184-186,共3页
Computer Applications and Software
基金
山东省优秀中青年科学家奖励基金项目(02BS009)。
关键词
化渣
噪声
功率谱
随机分析
特征频段
Slagging Noise Power spectrum Stochastic analysis Eigenfrequency
