基于统计模型的涡街流量传感器抗强混合振动干扰信号处理方法研究

Flow measurement is the important part of industrial process monitoring. In the industrial field, vortex flowmeter is widely used due to numerous advantages. However, vibration interferences often make vortex flowmeter fail to work, which is a key problem in application and has not been effectively solved. For this reason, this project intends to study the anti-strong mixed vibration interference method based on statistical characteristic model. Firstly, based on the analysis of vibration source, signal model of vortex flow sensor under mixed vibration interference is established, and the model parameter identification method is studied. Then, using clustering and probability statistics method, the statistical model of frequency, amplitude and damping ratio of vortex flow signal, periodic vibration interference and transient shock interference is studied. According to the statistical model, parameter differences of three types of signals are explored. Transient impulse interference is eliminated by the iterative piecewise integration method. Periodic interference is identified by the corrected frequency variance method. Finally, a low-power anti-hybrid vibration interference signal processing system is developed and experimentally verified. This project research is expected to expand the theory of analyzing pipeline vibration interference, and provide a new method for the identification of vortex flow in complex conditions. It can also be applied to similar occasions to solve the problem of anti-pipeline vibration in frequency measurement, which has significant scientific value and application prospect.

流量测量是工业过程监测的重要环节，涡街流量计因众多优点在工业中得到广泛应用。但是，工业现场的振动干扰问题往往会使涡街流量计失效，是其应用中的关键问题，一直以来未得到有效解决。据此，本项目拟基于统计特征模型来研究抗强混合振动干扰方法。首先，基于振动源的分析，建立混合振动干扰下涡街流量传感器的信号模型，研究模型参数辨识方法；然后，采用聚类和概率统计方法，研究涡街流量信号、周期振动干扰和瞬态冲击干扰的频率、幅值和阻尼比的统计模型；根据统计模型，探索三类信号的参数差异，采用迭代分段积分法消除瞬态冲击干扰，利用校正频率方差法识别周期性干扰，研究抗强混合振动干扰信号处理方法；并最终研制低功耗抗混合振动干扰信号处理系统并进行实验验证。本项目研究预期可拓展分析管道振动干扰的理论，为复杂工况下涡街流量的识别提供一种新方法；亦可推广应用到类似场合解决频率测量的抗管道振动问题，具有显著的科学价值和应用前景。

涡街流量计常被用来检测工业过程中的气体和蒸汽流量，但涡街流量计的安装现场普遍存在风机、水泵、阀门等振动干扰源，振动干扰通过管道传播，被涡街传感器拾取，最终影响流量测量的准确性。. 本项目旨在从包含强混合振动干扰的信号中提取正确的涡街流量。项目研究内容包括研究混合振动干扰下涡街传感器的信号模型和参数估计、分析混合振动干扰下涡街传感器输出信号的时频统计、研究涡街传感器抗强混合振动干扰信号处理方法、研制抗强混合振动干扰信号处理系统并进行实验验证。. 项目研究采用单边衰减的复合Laplace小波实数形式建立了瞬态冲击干扰主要模态的数学模型；提出了瞬态冲击的频响估计方法和瞬态响应工频干扰的抑制方法；提出了基于目标函数最优估计的密集多模态参数识别方法；揭示了涡街流量和同频信号频率波动大，周期振动和谐波干扰的频率波动小的规律，统计了校正频率方差的分界线为0.02；揭示了涡街流量和周期类干扰的阻尼比值小，瞬态冲击主要模态的阻尼比值大，统计了阻尼比的分界线约为0.001；提出了校正频率方差和自滤波相结合的抗强混合振动干扰方法；研制了低功耗两线制涡街流量计变送器系统，并进行了水流量和气流量的抗强混合振动干扰验证实验；结果表明在同时存在强周期振动干扰和强瞬态冲击干扰时，采用本研究提出了抗强混合振动干扰方法和系统能正确的识别涡街流量，满足复杂工况下的测量需求。. 项目研究结果具有重要的理论意义和实用价值，通过进一步的锤炼和完善，有望应用到实际涡街流量计产品中以提升性能；亦可推广到类似场合解决强管道振动下的频率测量问题。

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