Taking the Ms 7.4 earthquake in Indonesia on September 28, 2018 as the background, this paper uses the sliding quartile (IQR) algorithm, sliding principal component analysis (PCA) algorithm and short-time Fourier transform (STFT) algorithm to study the space-time electromagnetic data in the epicentral area by using the X, Y and Z components of ULF magnetic field observed by Zhangheng-1 electromagnetic satellite.The results show that the three algorithms can effectively extract the anomaly before the earthquake. 1) The mean value of X, Y and Z components began to appear anomaly 7 days before the earthquake. The anomaly degree of Y and Z components increased gradually with the approaching of the earthquake occurrence time, and reached the peak value 2 days before the earthquake. The maximum anomaly degree of Y component reached 0.7 nT, and then slowly disappeared after the earthquake. 2) 5 days before the earthquake, the anomaly of the principal component began to appear, the proportion of the first principal component decreased sharply by more than 15%. The proportion of the second and third principal components increased sharply, and the anomaly lasted for 3 days. 3) 9 days before the earthquake, the proportion of 13 and 25 Hz power spectral density anomalies appeared at the same time, 13 Hz proportion increased by 35%, 25 Hz proportion decreased by more than 40%. 13 Hz proportion appeared positive anomalies and 25 Hz proportion appeared negative anomalies, of which the largest positive anomaly reached 0.1, the largest negative anomaly reached ?0.15. The anomalies disappeared after the earthquake. According to the solar geomagnetic activity in the same period of time, the comprehensive analysis shows that the above electromagnetic anomalies can be used as precursors of earthquakes in Indonesia.

以2018年9月28日印尼Ms 7.4地震为背景, 利用张衡一号电磁卫星观测的ULF磁场X, Y和Z三分量数据, 采用滑动四分位(IQR)算法、滑动主成分分析算法(PCA)和短时傅里叶变换算法(STFT), 对震中范围的时空电磁数据进行分析, 结果显示 3 种算法都能有效地提取到震前异常。1) X, Y和Z分量均值震前7天开始出现异常, 随着发震时间临近, Y和Z分量的异常程度逐渐增加, 震前2天达到峰值, Y分量最大异常达到0.7 nT, 震后异常慢慢消失; 2) 震前5天主成分出现异常, 第一主成分占比急剧下降, 下降幅度超过15%, 第二、第三主成分占比急剧上升, 异常持续3天; 3) 震前9天, 13和25 Hz功率谱密度占比同时出现大幅异常, 13 Hz占比上升35%, 25 Hz占比下降超过40%, 13 Hz占比出现正异常, 最大正异常达到0.1, 25 Hz占比出现负异常, 最大负异常达到?0.15, 震后异常消失。结合同时段的太阳地磁活动情况, 认为上述电磁异常可以作为印尼地震的前兆。