用多通道AD分级采集扩展地震数据采集器的动态范围

地震数据采集是地震信号数字化必不可少的环节,动态范围是其一个重要的性能指标.实际地震信号的动态范围在160dB以上,而目前普遍使用的24位地震数据采集器动态范围相对较小且在50 Hz采样率时最大只达到135dB,致使24位地震数据采集器在实际使用中对小信号分辨率不够,不能有效提取地震信息;在大地震时又容易使数据采集器出现饱和限幅失真的现象而失去地震监测记录功能.本文针对在地震监测和地震研究中需要具有高分辨率和高动态范围的地震数据采集器这个亟待解决的问题,提出一种采用多通道AD转换器并行分级采集的方法,讨论了通道间失配及其标定.对研制实验样机的测试表明,其动态范围在50Hz采样时可以达到157dB以上,线性度优于0.005%.

Extending dynamic range of the seismic data acquisition system by using multi-channel ADC

The seismic data acquisition system is an indispensable process of the digitalization of seismic signals. The quality of this system has a direct effect on the quality of the seismic signal recorded and the final data processing results. There is a wide dynamic range for the observed seismic signal, the total signal amplitude of which could even surpass 160 dB. So it is a dynamic range of broadband seismometers, which is more than 140 dB. However, the widely used 24-bit high-quality seismic data acquisition system in recent times, which is produced based on ΔΣAD conventional technology, has a dynamic range of only 135 dB@50SPS. As a result, seismic information cannot be extracted effectively in practical earthquake monitoring for both minor and strong signals. The loss of minor signal is due to the fact that data acquisition with low SNR (signal to noise ratio) has no high resolution to identify minor signals, and that the amplitude of the signal to record is at the same magnitude order as the resolution of the data acquisition system. The loss of large signal is caused by a saturated clipping distortion that appears in violent earthquakes. This makes local seismograph stations almost lose the ability to record data at the time that firsthand observation resources are needed for earthquake prevention and hazard reduction, and leads to lose precious opportunities to record strong seismic signals for seismic study. Therefore, to meet the application requirements, a multi-channel AD converter sample grading method for extending the dynamic range of seismic data acquisition is put forward in this paper.#br#In the multi-channel AD converter sample grading method, several ADC channels are put in parallel, and simulated input signals are sent to each channel. Synchronous sampling and digital conversion are made on the full range input signal in each channel with different input voltage ranges in each channel for conversion. Meanwhile, the ranges of measurement and the input range of AD converters are matched by modulating waveforms and electrical level displacements in simulated preprocessing circuits in the front ends of each channel. The results are put out in the format of 32-bits converted digital signals after processing and fitted by the CPU-control process unit and multi switch MUX.#br#We adopt the parallel connection of two ADCs in the experimental circuits for a two-level segmented acquisition of input signals. The 24-bit AD chip ADS1255 with fourth-order ΣΔ modulators are used as the chip of the analog-digital converter. The range of AD input signal is extended from ±5 V to ±40 V (differential) with the resistance attenuating network for the first level of signal, and the resolution of the other level of signal is improved by amplitude limiting and magnification. The ADCs in the two channels collect the input simulated signal synchronously and parallel driven by the same clock. The digital option switch selects channel data according to the magnitude of the signal, and forms a 32-bit output after a data scaling by the control processor. The test results show that the zero input noise voltage has an effective value less than 0.2 μV, the noise spectral density is less than 0.05 μV/√Hz, the full-scale input range is ±40 V, with a dynamic range of 157 dB and linearity better than 0.005% at a sampling rate of 50 Hz.#br#The method of multi-channel AD converter sample grading not only improves the resolution of seismic data acquisition for minor signals, but also enables the acquisition system to record great number of seismic information without saturation in advance to prevent from amplitude limiting. This method can help meet requirements for the large dynamic ranges for data acquisition in seismic monitoring, with low costs and easily to achieve technologically.