基于经典谱估计改进方法的涡街流量计

针对涡街流量计高精度、高量程比的要求,在分析涡街信号及其噪声特点的基础上,提出一种采用自适应采样频率和Welch功率谱估计相结合的涡街信号分析处理方法。该方法首先使用经典功率谱估计的FFT算法计算出信号频率的区间范围,然后将信号通过相应截止频率的低通滤波器以防止发生混叠现象,采用信号抽取的方法降低采样频率从而减小频谱的最小频率分辨率,最后采用Welch功率谱估计的方法进行谱分析提高信噪比、减少谱失真。仿真及实验结果表明:所提出的涡街信号处理方法能有效地抑制噪声,实现高精度的功率谱计算,对于提升和改进涡街流量计的性能有良好的效果。     

Frequency measurement technique based on frequency conversion

To measure the signals with high freq u ency(>500 MHz),a sampling frequency down conversion method is introduced.This pa per analyzes the intermodulation signals and figures out the relationship betwee n the intermodulation signal and intermediate frequenc y signal.Based on the frequency conversion technology,an exclusion algorithm i s proposed a nd the actual implementation of the algorithm is given.The application resu lts show that the exclusion algorithm can identify the intermodulation signal exactly and eliminate the bad influence on the frequency measurement.     

计及负频率影响的科里奥利质量流量计信号处理方法

采用滑动Goertzel算法计算科里奥利质量流量计信号的相位差时，存在较长的收敛过程，其主要原因之一是忽略了负频率成分的贡献。基于DTFT递推算法，提出了一种计及负频率影响的科里奥利质量流量计信号处理方法。首先采用自适应格型陷波滤波器对科里奥利质量流量计的传感器输出信号进行滤波并求得其频率，然后采用计及负频率影响的DTFT递推算法计算两路信号之间的实时相位差，再通过频率和相位差计算出时间差，从而求得质量流量。仿真结果表明，该方法可极大缩短相位差和时间差计算的收敛过程，具有较高的计算精度，且当应用于实际的系统时不易发生数值溢出。     

基于压缩感知弱匹配追踪算法的信号特征提取

针对滚动轴承故障诊断中的特征提取问题,提出一种基于压缩感知弱匹配追踪算法的特征提取方法。针对轴承故障信号特征特点构建了一个由傅里叶字典和冲击时频字典组成的联合字典,作为弱匹配追踪算法中的过完备冗余原子库。进而利用改进的简化粒子群寻优算法在联合字典原子库中寻找最能匹配轴承故障信号特征的原子,实现故障信号的快速高效稀疏分解。在信号重构阶段提出了一种改进的阈值降噪策略,解决了软阈值降噪存在恒定偏差以及硬阈值降噪的不连续问题。对CWRU（Case Western Reserve University）轴承数据中心所提供的标准轴承故障信号和某钢厂滚动轴承实测信号进行了仿真,仿真结果验证了该方法的优越性。     

涡街流量计信号估计的自适应陷波方法

本文提出采用自适应陷波方法计算涡街流量计输信号的频率,并给出实验结果。流量计信号为一窄带信号,自适应陷波抑制一个特定的涡街频率,并且几乎不受位于带宽以外频率的影响。此自适应陷波器只需估计一个参数,频率计算非常简单,与以前的频率估计方法相比,它以前的频率估计方法相比,它有许多优点,是一种有效的新方法。     

Note: anti-strong-disturbance signal processing method of vortex flowmeter with two sensors

Some digital signal processing methods have been used to deal with the output signal of vortex flowmeter for extracting the flow rate frequency from the noisy output of vortex flow rate sensor and achieving the measurement of small flow rate. In applications, however, the power of noise is larger than that of flow rate sometimes. These strong disturbances are caused by pipe vibration mostly. Under this condition the previous digital signal processing methods will be unavailable. Therefore, an anti-strong-disturbance solution is studied for the vortex flowmeter with two sensors in this Note. In this solution, two piezoelectric sensors are installed in the vortex probe. One is called the flow rate sensor for measuring both the flow rate and vibration noise, and the other is called the vibration sensor for detecting the vibration noise and sensing the flow rate signal weakly at the same time. An anti-strong-disturbance signal processing method combining the frequency-domain substation algorithm with the frequency-variance calculation algorithm is proposed to identify the flow rate frequency. When the peak number of amplitude spectrum of the flow rate sensor is different from that of the vibration sensor, the frequency-domain subtraction algorithm will be adopted; when the peak number of amplitude spectrum of the flow rate sensor is the same as that of the vibration sensor, the frequency-variance calculation algorithm will be employed. The whole algorithm is implemented in real time by an ultralow power micro control unit (MCU) to meet requirements of process instrumentation. The experimental results show that this method can obtain the flow rate frequency correctly even if the power of the pipe vibration noise is larger than that of the vortex flow rate signal.     

Performance evaluation of piezoelectric and differential pressure sensor for vortex flowmeters

Piezoelectric and transient differential pressure sensors are two among the most widely employed sensors for vortex flowmeter application. The present study evaluates the performance of these two techniques under fully developed and disturbed flow conditions. Firstly, the location of the transient differential pressure sensor is optimized to obtain high amplitude signals and good linearity in Strouhal number. Empirical mode decomposition method in combination with autocorrelation decay is successfully employed at high Reynolds numbers to identify the vortex shedding frequency in presence of hydrodynamic noise. The performance of the differential pressure sensor deteriorates significantly under disturbed flow conditions at low Reynolds number due to the presence of low frequency components. This deterioration in the signal quality limits the lower operating range of the flowmeter with differential pressure sensor. The output signals of the piezoelectric sensor and differential pressure sensor under no flow condition are compared to obtain the background noise due to piping vibrations and electrical interferences. These results will help a designer to suggest robust signal processing algorithms for vortex frequency detection.     

A DSP-based signal processing method and system for CMF

A set of digital signal processing method is formed by combining a digital band-pass filter, an adaptive lattice notch filter and the DTFT algorithm considering negative frequency contribution for processing the signals of Coriolis mass flowmeter. A digital Coriolis mass flow transmitter is developed with a DSP chip to realize the signal processing approach. Some effective measures are proposed to ensure high accuracy and real time of this approach in the implementation. Simulations, electrical signal tests and water flowrate calibrations are conducted to validate the performances of the method and the system.     

基于IIR小波滤波器的涡街流量计数字信号处理系统

涡街流量计被广泛应用于过程工业,但是,由于易受由管道振动和流场扰动等因素干扰,现场测量精度无法保证,测量小流量困难。本文将小波滤波器组应用于涡街流量计信号处理中,研究基于小波滤波的涡街信号处理方法,分析了小波滤波器的幅频特性对信号分析的影响,构造了幅频特性好的IIR型小波滤波器组。本文研制了基于ADSP2181的涡街流量计数字信号处理系统,并进行了气体流量和水流量标定实验,实验结果表明,基于小波滤波的涡街流量计数字信号处理系统有良好的适配性能,性能指标优于常规的涡街流量计处理系统。     

磁悬浮高速离心式鼓风机的喘振检测

针对磁悬浮高速离心式鼓风机的喘振问题,提出了一种基于磁悬浮轴承的喘振检测方法。该方法采用通用同频陷波器滤除转子位移中的同频分量,消除了同频扰动对喘振检测的影响;通过分析不同收敛因子对喘振频率估计的作用,基于自适应估计提出了变收敛因子的喘振频率和幅值估计方法,减小了低频信号的干扰,提高了喘振信号检测的快速响应能力。最后,分析了改进检测算法的收敛性,并在100kW磁悬浮离心式鼓风机测试系统上进行了实验验证。实验结果表明,改进后的喘振检测算法可在喘振发生前检测出喘振先兆旋转失速信号,在喘振发生0.23s内检测出喘振信号,较改进前的检测结果提高了2.6s。该检测方法无需外加其它检测单元,算法简单、快速,计算量小、并可有效地反映喘振发生过程中频率与振幅的变化。     

Bearing fault diagnosis based on an improved morphological filter

The extraction of repetitive impacts from vibration signals plays an essential role in bearing fault detection. Among different signal processing algorithms, morphological filter (MF) has attracted lots of attention because it could directly extract the geometric structure of the impulsive feature and only needs little computation. However, the conventional MF and some current improvements are based on the local optima of the raw signal to de-noise the noisy signal and its faulty feature extracting capability would be greatly affected by the noise. In this paper, a new improved MF algorithm is proposed to overcome such deficiency. Firstly, morphological gradient (MG) operator is selected in this paper due to its capability of picking up both positive and negative impulses. Then, based on the relationship between the defect induced impulse and a harmonic function with the resonant frequency, the harmonic waveform in a period is adopted to instruct the construction of structuring element (SE). The improved MF can obtain the fault feature from low SNR signals. The processing results of a simulation signal and two sets of experimental signals and a set of comparisons verify the effectiveness and robustness of the proposed method.     

基于自适应陷波的直拉单晶直径跟踪

为抵消单晶生长过程中晶体直径测量信号存在的周期性干扰,提出一种适合晶体直径测量信号的自适应陷波滤波方法。该方法采用抵消低频分量、保留高频分量的思想建立滤波器优化函数,利用一种改进的粒子群优化算法优化该函数获得周期性干扰的逼近信号,并用此逼近信号抵消周期性干扰。实验结果表明,所提出的滤波方法能有效跟踪直拉单晶直径的变化,精度优于常用的滤波方法,所提出的粒子群优化算法能够使滤波器系数较快收敛。     

A dual phase-locked loop for vortex flow metering

A vortex-shedding flow meter produces an approximately sinusoidal signal whose average frequency is proportional to volumetric flow rate. The frequency of vortex shedding varies over a large range (up to 1:100), depending on the size of the flow meter. The conventional frequency estimator uses a zero-crossing algorithm (ZC), but this approach fails at low flows, where the signal-to-noise ratio is poor. An alternative is to use a phase-locked loop (PLL), but typical single PLL designs cannot cope with a wide frequency range at high noise levels. This paper describes a dual PLL structure that can be used to track the vortex shedding frequency over the flow meter’s full range of operation. This dual PLL provides improved accuracy and tracking ability compared with the conventional zero-crossing algorithm.     

气-液两相流压差波动信号中噪声的辨识

压差波动信号由于其容易测量,而且包含流动的很多信息而被广泛用于气液两相流的研究中。在测量时由于难免受到各种干扰,这些干扰会影响非线性分析的精度和结果。因此,在利用压差波动信号进行非线性分析之前,通常要对其进行滤波处理。究竟多高频率以上的压差波动信号才是噪声,并如何对其进行定量检测的研究就非常重要。这里对水平管内气液两相流压差波动信号用小波包进行分解,得到按16Hz等间隔分段的16个不同频带信号,用自相关函数研究了各频段信号的线性相关性。通过理论证实了气液两相流压差波动信号中,64Hz以上信号不存在线性相关性,可以认为其是噪声信号。研究指出通过气液两相流压差波动信号来研究流型信息时,应考虑64Hz以下信号。     

基于小波变换的涡街流量计信号处理方法

涡街流量计有许多优点,应用比较广泛。但是,涡街流量计易于受到由管道振动和流场扰动引起的噪声干扰。涡待流量计中的处理电路不能保证仪表在工业现场的测量精度。本文研究基于小波变换的涡街流量计信号处理方法。本文介绍小波变换的基本原理和快速算法,分析小波滤波器的幅频特性,研究调整滤波器中心频率的方法,给出涡街信号的处理过程,进行仿真和实验测试。仿真和实验结果表明,小波变换能有效地减小了噪声影响,使频率测量的精度高,处理实时。小波变换是涡街流量计信号处理的一种新方法。     

Response of a dual triangulate bluff body vortex flowmeter to oscillatory flow

In this paper, on an experimental facility, the measurement characteristics of a diameter 50 mm dual triangulate bluff body vortex flowmeter in steady flow and oscillatory flow were investigated. Then, the Hilbert Huang Transformation (HHT) method was used to assess the anti-interference performances and the vortex street stability in oscillatory flow for the dual triangulate bluff body vortex flowmeter and a single bluff body vortex flowmeter. Offline simulation was carried out on the anti-interference performances of the dual triangulate bluff body vortex flowmeter signal noise in oscillatory flow by the method of the EMD-scales filter. The major findings are: (a) in most case, the EMD-scales filter may be as good at de-noising effect for the dual bluff body vortex flowmeter in oscillatory flow than that for the single bluff body vortex flowmeter in oscillatory flow. The vortex street stability in oscillatory flow for the dual bluff body is similar to that for the single bluff body. (b) In some special case, the EMD-scales filter is unable to play a better de-nosing role for the dual bluff body vortex flowmeter in oscillatory flow. The invalid condition of the EMD-scales filter for the dual bluff body vortex flowmeter in oscillatory flow is different to that of the single bluff body vortex flowmeter and it was advanced in this paper. (C) The vortex street stability for the dual bluff body vortex flowmeter is better than that for the single bluff body vortex flowmeter.     

基于互相关检测的滚动轴承实时故障诊断方法

提出了一种易于用模拟电路实现的基于互相关检测的滚动轴承实时故障诊断方法,首先,用两个加速度传感器在不同测点采集轴承振动信号,将其分别送入相应通道的高Q带通滤波器来选择最优共振带;然后,将两路带通滤波器的输出信号进行互相关检测,将互相关检测得到的信号经低通滤波器,保留低频故障信号;最后,将低通滤波器输出的时域信号通过频谱分析仪显示滚动轴承故障特征频率的谱线以实现滚动轴承的实时故障诊断。用模拟电路的形式将该方法进行搭建,并在QPZZ-II实测平台完成滚动轴承的实时故障诊断。结果表明:该方法克服了单一信号源的局限性,能利用互相关函数削弱共振带内部噪声,使诊断结果具有更高的频谱辨识率,而且能够用结构简单、易于维护的模拟电路实现,对轴承实时故障诊断方法的应用与普及具有一定的参考价值。     

A joint adaptive wavelet filter and morphological signal processing method for weak mechanical impulse extraction

Periodical impulses are vital indicators of rotating machinery faults. Therefore, the extraction of weak periodical impulses from vibration signals is of great importance for incipient fault detection. However, measured signals are often severely tainted by various noises, which makes the detection of impulses rather difficult. As such, a proper signal processing technique is necessary. In this paper, a hybrid method comprised of wavelet filter and morphological signal processing (MSP) is proposed for this task. The wavelet filter is used to eliminate the noise and enhance the impulsive features. Then, the filtered signal is processed by the morphological closing operator and a local maximum algorithm to isolate periodical impulses. To select the proper parameters of the joint approach, i.e., the center frequency, the bandwidth of wavelet filter, and the length of flat structuring elements (SE), a novel optimization algorithm based on differential evolution (DE) is developed. The results of simulated experiments and bearing vibration signal analysis verify the effectiveness of the proposed method.     

基于改进经验小波变换的行星齿轮箱故障诊断

行星齿轮箱振动信号具有复杂多分量和调幅-调频的特点。幅值解调和频率解调方法能够避免传统Fourier频谱中的复杂边带分析,有效识别故障特征频率。经验小波变换通过对信号Fourier频谱的分割构造一组正交滤波器组,能提取具有紧支撑Fourier频谱的单分量成分,再对单分量成分运用Hilbert变换即可实现信号的解调分析。经验小波变换能够有效分离出调幅-调频成分,不存在模态混叠现象,具有完备的理论基础,自适应性好、算法简单、计算速度快。将改进的经验小波变换应用于行星齿轮箱振动信号的解调分析;提出了一种单分量个数的估算方法,解决了经验小波变换中的Fourier频谱划分问题;给出了对故障敏感的信号分量的选取方法,提高了分析的针对性。将改进方法应用于行星齿轮箱振动仿真信号和实验信号分析,验证了该方法的有效性。     

Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition

When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.