频率域航空电磁异常的数字化识别筛选技术

Digital detection and classification technique of the frequency-domain airborne EM anomaly

频率域航空电磁法实施连续测量,形成了海量数据,航电异常识别筛选工作量大,传统人工异常识别筛选工作无法满足需要。基于HDY-402型三频航空电磁仪技术特点,参考国内、外相关技术,借鉴传统的人工异常识别筛选方法,开发了计算机软件异常识别、筛选和解释算法,并编制了应用软件。研制的软件应用在内蒙古地区开展的约42.3万测线千米航空物探综合勘查项目中,异常识别方法和效果得到了检验,提高了海量异常识别筛选的工作效率和质量。

A frequency domain airborne electromagnetic (AEM)survey collects EM data continuously and forms huge vol-ume EM anomaly.The traditional manual anomaly detection and classification technique can not meet the needs of identification of AEM anomaly.Based on the EM data character of the HDY-402 tri-frequency EM system,and referred to the traditional manual anomaly detection technique and the related technology at home and abroad,this paper introduce the digital methods to detect and classify AEM anomaly.A software was developed and applied to about 423 000 survey kilometer AEM data acquired in the Inner Mongolia using the new technique.Its anomaly detection and classification efficiency and accuracy was validated.