时分复用数字闭环电容式微加速度计接口电路

为实现电容式微加速度计的数字输出闭环,设计了一种数字输出闭环ASIC(Application Specific Integrated Circuit)接口电路,以降低电路输出噪声并提高测量量程。对已有的电容式微加速度计ASIC电路进行了改进,分时段在中间极板上加载差分电容读出信号和由脉宽调变(PWM)波控制的反馈信号,然后由控制器实现闭环,利用Sigma Delta调制器实现模数转换。通过分析差分电容读出电路和Sigma Delta调制器的原理和特性,建立了该数字输出闭环电容式微加速度计的模型,进行了系统的设计与仿真。实验结果表明,该数字输出闭环电容式微加速度计的噪声水平为9.6μg/√Hz,量程为±3g。这些结果验证了时分复用方案的可行性和本文所提出模型的正确性。     

基于高精度运算放大器的隧道式硅微加速度计信号处理电路

介绍了一种由高精度运算放大器及精密仪表放大器构成的隧道式硅微加速度计信号处理电路,通过分析信号处理电路的构成、信号输出的有效成分、放大器的性能指标及典型用法,得出高精度运算放大器OPA128LM使用在隧道电流的I-V转换部分所具有的独特优势.后级反馈放大电路采用精密仪表放大器AD620BR构成两级放大,其各项参数极大提高了信号读出电路的精密性.实验结果表明:基于以上方法的设计对信号处理电路的精度、灵敏度及线性度等性能有明显的改善.     

角加速度信号自适应小波的去噪方法

针对多扰动、大负载环境下角加速度计输出信号中含有脉冲噪声和高斯白噪声的情况,提出一种改进的离散小波阈值法与中值滤波算法相结合的角加速度计信号自适应去噪算法。首先,使用中值滤波对原始信号进行去除脉冲噪声的预处理;其次,使用分解层数的自适应确定方法与改进的阈值选取准则,通过离散小波阈值去噪法去除高斯白噪声。仿真结果表明,该算法能够有效地提高信噪比,降低最小均方误差。实验结果表明,该算法既能去除分子型液环式角加速度计信号中噪声,又能很好地保留真实信号中的高动态部分。     

紫外临边成像光谱仪CCD电路系统的设计

提出一种用于紫外临边成像光谱仪模数分离成像电路的系统设计方案,该方案避免了CCD模拟输出信号的板间传输和数字信号对模拟信号的干扰,使CCD信号处理电路的噪声水平达到了模拟前端数据手册中给出的2 LSB的性能指标.考虑CCD57-10 BI AIMO没有抗溢出结构,在饱和之前会发生电荷溢出现象,提出了临界溢出电子数的概念...     

微加速度计中Sigma Delta调制与 脉冲编码调制的对比分析

对Sigma Delta调制与脉冲编码调制进行对比,研究了Sigma Delta调制与脉冲编码调制的优缺点。建立了微加速度计中两位输出的Sigma Delta调制和两位输出的脉冲编码调制的仿真系统。然后,对比使用这两种调制方式的微加速度计的加速度信号,并分析在两种不同调制方式下的输出信号波形的差别。最后,利用周期图法得到了两种调制信号的功率谱密度图,发现在低频段脉冲编码调制信号的量化噪声比Sigma Delta调制信号大很多;而在高频段,两种调制方式信号的量化噪声一样严重。仿真结果表明,尽管Sigma Delta调制系统比脉冲编码调制系统更加复杂,但是Sigma Delta调制得到的信噪比要比脉冲编码调制得到的信噪比高出20 dB。     

基于MEMS传感器的高精度电子罗盘研究

针对电子罗盘易受到干扰和成本高等问题,对电子罗盘结构、倾角补偿、误差分析、误差校正等方面进行了研究,对电子罗盘在实际应用中的误差来源和校正算法进行了归纳,提出了基于STM32 ARM Cortex-M3内核单片机以及MEMS传感器构建电子罗盘系统,开展了电子罗盘的误差分析,提出了电子罗盘误差模型,提出用卡尔曼滤波算法对磁阻传感器和加速度计进行了数据融合与滤波,在利用加速度计计算倾角的基础上对电子罗盘进行了倾角补偿,利用Matlab处理上位机采集到的电子罗盘数据,进行了电子罗盘的输出角度和精度试验。研究结果表明,该电子罗盘可获得高精度的静态姿态角。     

温度对无驱动结构硅微机械陀螺信号相位差的影响

在旋转载体用硅微机械陀螺的信号解调中,陀螺与加速度计信号的相位差起到至关重要的作用,必须考虑温度对陀螺与加速度计信号相位差的影响,以及温度对陀螺输出的影响.通过测试加速度计温度特性及陀螺温度特性,并将二者进行比较,研究了温度对陀螺与加速度信号的相位差的影响,证实温度对陀螺输出影响很小,温度对硅微机械陀螺的信号相位差影响很小.     

IEPE加速度计电路噪声分析

研究压电集成电路加速度计的主要噪声源,利用En-In噪声模型将内部噪声源等效输入端,实现了输入噪声和输入信号的直接对比,能容易得到噪声对信号的影响。将Y-Δ变换原理引入T型网络噪声分析,降低噪声分析难度。通过对电路噪声的分析,在宽频范围内推导出可用于计算IEPE加速度计电路本底噪声的公式。将理论计算值与PSpice软件噪声分析所得值进行了对比,证明二者具有良好的相关性,同时得出了各噪声源在输入端对总噪声的贡献,提出了在不同频段内降低总噪声的方法,为IEPE加速度计电路的低噪声设计、参数选择和性能优化提供了理论依据。实验样机的实际值与理论值的对比结果表明,此法对于IEPE加速度计电路低噪声设计具有应用价值。     

流量计输出信号的智能化网络整形识别技术

流量计在使用过程中由于受到噪声、电磁脉冲等因素的干扰,在使用时常会出现仪表显示不稳、显示数字失真等现象,有时会严重影响计量精度.文中深入分析了相关信号调理模块与软件滤波方法对该类信号处理过程中所存在的缺陷,结合神经网络等方法提出了一种流量计输出信号智能化整形识别技术,并结合实际信号对该方法进行了检验.结果表明,该方法能有效克服传统方法存在的缺陷,为流量计输出信号的整形与识别分析开辟了一条有效的途径.     

基于可编程模拟器件ispPAC10低频声波声检测电路设计

提出了基于在线可编程模拟器件ispPAC10差动放大及低通滤波电路来完成低频声波信号的采集方法.该方法可有效地降低检测电路的噪声干扰,提高输出信号的信噪比.     

微隧穿式陀螺仪检测模态的线性二次高斯控制

为了将微隧穿式陀螺仪(MTG)的隧尖与检测电极之间的隧道间隙及其变动量分别维持在1nm和0.1nm并降低系统噪声和扩大带宽,本文为其检测模态设计了线性二次高斯(LQG)闭环反馈系统。在利用微小量法对呈指数规律的隧道效应进行线性化的基础上,建立了MTG检测模态的线性化模型,并将哥氏加速度和电子隧道1/f噪声分别当作主要的过程噪声和输出噪声,设计了由最优状态估计器和线性二次(LQ)状态调节器组成的LQG控制器。搭建了仿真系统和实际的LQG控制电路并进行动态测试。仿真结果显示,LQG控制在将系统的信噪比提高24dB的同时,能够将两个隧道电极之间的间隙的变动量控制在10-4 nm。实验曲线表明,隧道电流噪声的峰峰值为0.4nA,LQG反馈控制系统在动态加速度信号的激励下可维持恒定隧道间隙为1nm。     

串级时滞过程的解耦控制设计

针对化工串级过程提出了两种新颖的两自由度解耦控制结构。基于鲁棒控制H2最优性能指标设计给定值响应控制器。根据系统运行抗负载干扰要求,在中间级可测量过程的输入和输出端之间设计抑制负载干扰信号的闭环,通过提出期望闭环余灵敏度函数的方法来确定其反馈通道中的扰动观测器,同时给出了该闭环保证鲁棒稳定性的充要条件。最后通过实验显示了该方法相对于其它方法的优越性。     

SIGNAL FEATURE EXTRACTION BASED UPON INDEPENDENT COMPONENT ANALYSIS AND WAVELET TRANSFORM

It is an important precondition for machine fault diagnosis that vibration signal can be extracted effectively. Based on the characteristic of noise interfused during the course of sampling vibration signal, independent component analysis (ICA) method is combined with wavelet to de-noise. Firstly, The sampled signal can be separated with ICA, then the function of frequency band chosen with multi-resolution wavelet transform can be used to judge whether the stochastic disturbance singular signal is interfused. By these ways, the vibration signals can be extracted effectively, which provides favorable condition for subsequent feature detection of vibration signal and fault diagnosis.     

Robust integral of neural network and precision motion control of electrical–optical gyro-stabilized platform with unknown input dead-zones

Parametric uncertainty associated with unmodeled disturbance always exist in physical electrical–optical gyro-stabilized platform systems, and poses great challenges to the controller design. Moreover, the existence of actuator deadzone nonlinearity makes the situation more complicated. By constructing a smooth dead-zone inverse, the control law consisting of the robust integral of a neural network (NN) output plus sign of the tracking error feedback is proposed, in which adaptive law is synthesized to handle parametric uncertainty and RISE robust term to attenuate unmodeled disturbance. In order to reduce the measure noise, a desired compensation method is utilized in controller design, in which the model compensation term depends on the reference signal only. By mainly activating an auxiliary robust control component for pulling back the transient escaped from the neural active region, a multi-switching robust neuro adaptive controller in the neural approximation domain, which can achieve globally uniformly ultimately bounded (GUUB) tracking stability of servo systems recently. An asymptotic tracking performance in the presence of unknown dead-zone, parametric uncertainties and various disturbances, which is vital for high accuracy tracking, is achieved by the proposed robust adaptive backstepping controller. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy.     

汽车发电机高低转速电磁噪声的解决方案

针对某型汽车交流发电机高转速下的电磁异响问题和低转速区间的电磁噪声问题进行分析。综合考虑影响电磁噪声的关键因素,给出高低转速下电磁噪声的解决方案,并取得满意效果。为发电机的降噪设计提供依据。     

基于小波分析的电能质量三相不平衡度虚拟仪

介绍了一种基于小波分析的电能质量三相不平衡度检测技术,在LabVIEW虚拟仪器设计平台上采用小波分析技术检测电能信号的突变点,从原始信号中除去突变点得到稳态信号,采用巴特沃斯低通滤波器滤除谐波成份后计算工频基波的三相不平衡度。实验结果表明,利用该方法可以很好地去除信号突变,获得较高的精度。     

Auditory-model-based Feature Extraction Method for Mechanical Faults Diagnosis

It is well known that the human auditory system possesses remarkable capabilities to analyze and identify signals. Therefore, it would be significant to build an auditory model based on the mechanism of human auditory systems, which may improve the effects of mechanical signal analysis and enrich the methods of mechanical faults features extraction. However the existing methods are all based on explicit senses of mathematics or physics, and have some shortages on distinguishing different faults, stability, and suppressing the disturbance noise, etc. For the purpose of improving the performances of the work of feature extraction, an auditory model, early auditory(EA) model, is introduced for the first time. This auditory model transforms time domain signal into auditory spectrum via bandpass filtering, nonlinear compressing, and lateral inhibiting by simulating the principle of the human auditory system. The EA model is developed with the Gammatone filterbank as the basilar membrane. According to the characteristics of vibration signals, a method is proposed for determining the parameter of inner hair cells model of EA model. The performance of EA model is evaluated through experiments on four rotor faults, including misalignment, rotor-to-stator rubbing, oil film whirl, and pedestal looseness. The results show that the auditory spectrum, output of EA model, can effectively distinguish different faults with satisfactory stability and has the ability to suppress the disturbance noise. Then, it is feasible to apply auditory model, as a new method, to the feature extraction for mechanical faults diagnosis with effect.     

基于有载品质因数的低抖动时钟电路研究

抖动作为衡量时钟信号质量的重要指标,对电子系统的性能具有重要意义。数据采集系统要获得良好的信噪比,就必须要有高性能低抖动的时钟信号。本文应用相位噪声与抖动的关系,同时结合相位噪声Leeson模型,研究了时钟信号发生电路的抖动及相位噪声特性,分析了电路有载品质因数QL对抖动的影响,并给出了电路主要器件与抖动关系的显性表达式。以一种100 MHz低抖动时钟信号发生电路为例,进行了理论分析、仿真和实验验证,并将其应用到2.5 GHz采样时钟信号发生电路中进行了对比测试。结果表明,提高电路的有载品质因素QL可以明显改善其抖动及相位噪声特性。     

基于分段统计非等权处理提高寻北仪抗基座扰动的能力

为减小静基座寻北时外部基座扰动对寻北精度的影响,文章首先分析了基座扰动引起寻北仪输出数据变化的特点,根据干扰大小的时段性,提出采用分段统计非等权处理的方法对寻北仪原始输出数据进行滤波处理,将分段统计后的均方差大小作为衡量该段数据可信度的依据,并对每段数据赋予不同的权值。通过人员走动及上下车的扰动试验进行仿真,证明该方法可以较好地减小基座扰动对寻北精度的影响。     

Generalized predictor based active disturbance rejection control for non-minimum phase systems

In this paper, a generalized predictor based control scheme is proposed to improve system performance of set-point tracking and disturbance rejection for non-minimum phase (NMP) systems. By using a generalized predictor to estimate the system output without time delay, a model-based extended state observer (MESO) is designed to simultaneously estimate the system state and disturbance. Accordingly, an active disturbance rejection control design is developed which consists of a state feedback control and a feedforward control for the disturbance rejection. The MESO and feedback controllers are analytically derived by specifying the desired characteristic roots of MESO and closed-loop system poles, respectively. To improve the output tracking performance, a pre-filter is designed based on a desired closed-loop transfer function for the set-point tracking. A sufficient condition guaranteeing robust stability of the closed-loop system against time-varying uncertainties is established in terms of linear matrix inequalities (LMIs). Three illustrative examples from the literature are used to demonstrate the effectiveness and merit of the proposed control scheme.