Improved numerical integration method for flowrate of ultrasonic flowmeter based on Gauss quadrature for non-ideal flow fields

Multipath ultrasonic flowmeters with large diameter are widely used in industry. And their measurement performances are sensitive to velocity profiles in conduits. Gauss–Jacobi and Optimized Weighted Integration for Circular Sections (OWICS) method are commonly applied in flow measurement of multipath ultrasonic flowmeters, both of which assume ideal flow in pipes. They are not proper for non-ideal flow measurement. Therefore, an improved numerical integration method for flowrate based on Gauss quadrature is proposed. With this method, optimum relative path heights and corresponding weights are determined according to specific disturbed flows. By comparison Gauss–Jacobi, OWICS with the improved method, the validity of the proposed method is verified for typical disturbed flows based on both theoretical analysis and experiments, and measurement performances of ultrasonic flowmeters are improved significantly.     

Measurement of steam flow rates using a clamp-on ultrasonic flowmeter with various wetness fractions

Most of the heat in industrial plants is supplied by steam. To minimize energy waste, measuring the steam flow rates in existing pipes is important. Clamp-on ultrasonic flowmeters are used for this purpose, for which the sensors are attached to the pipe wall. However, flow conditions that can be used are limited because the signal-to-noise ratio of the ultrasonic signal in a steam flow is low. Furthermore, the steam wetness increases with heat losses, which may affect measurement results. Therefore, flow rate measurements in wet steam flows using clamp-on ultrasonic flowmeters have not been fully established. In this study, steam flow rates with various wetness fractions and system pressures were measured using a laboratory-made clamp-on ultrasonic flowmeter. The results show that flow rates in wet steam could be determined within a 10% error under general conditions in a steam piping system, although the conversion factor from line-average to area-average velocities was calibrated in superheated conditions, and the speed of sound in saturated conditions at each pressure was used. However, the error of the flow rates tended to increase with the wetness fraction and was biased toward positive values. The speed of sound and liquid volume fraction were evaluated at different wetness fractions. The flow rate error due to the change in sound speed was less than 1%, and 1.2% of the flow rates were overestimated owing to the liquid volume fraction. The velocity distribution in wet steam was considered different from that in the superheated steam owing to the existence of the liquid phase, and the change in velocity profile may lead to an overestimation of the steam flow rates in the wet steam condition.     

Application of artificial neural networks instead of the orifice plate discharge coefficient

Differential pressure flowmeters are very often used in many industries. Therefore, the improvement of this method of flow measurement is an important task of flow measurement and instrumentation. One of the important characteristics of differential pressure flowmeters is the discharge coefficient of the flow transducers. A large number of studies and publications were devoted to modeling this coefficient. Therefore, in the framework of this research, this coefficient is simulated using artificial neural networks. The neural representation of this characteristic is made in the form of a multilayer perceptron. In this paper, we replace the traditional equation for the discharge coefficient with an artificial neural network. The advantages and disadvantages of such application of neural networks as discharge coefficients are discussed. The analysis of the results of gas flow measurement, where the neural network is used instead of the traditional equation, is presented. The estimation of flow rate measurement errors with such an approach is made; the error of calculation of the discharge coefficient is estimated.     

SOLVING INVERSE KINEMATICS OF REDUNDANT MANIPULATOR BASED ON NEURAL NETWORK

For the redundant manipulators, neural network is used to tackle the velocity inverse kinematics of robot manipulators. The neural networks utlized are multi-layered perceptions with a back-propagation training algorithm. The weight table is used to save the weights solving the inverse kinematics based on the different optimization performance criteria. Simulations verify the effectiveness of using neural network.     

Evaluation of flowmeters for heat metering

Heat flowmeters are expected to be reasonably priced, be very reliable, and have high measurement accuracy. Various types of heat flowmeters have been developed and they are widely used in large residential and industrial buildings. In this study, three types of heat flowmeters (turbine, electromagnetic and ultrasonic) were tested for accuracy, effect of installation position and vibration, durability and performance in the field for several installation positions and in the presence of vibration. We used a liquid flow standard system and a customized durability test system in accordance with the International Organization of Legal Metrology (OIML) R 75-2 heat meter testing method. The field test was conducted in eight different locations from winter to summer. All flowmeters were calibrated before and after the field test, and the measurement deviation and the relative expanded uncertainty were calculated. The mean deviations obtained were–0.21%,–0.07%, and 0.11%, with the relative expanded uncertainties 0.48%, 0.17%, and 0.40% for turbine, electromagnetic, and ultrasonic flowmeters, respectively. The results of position and rotation tests, mean deviations by rotation angles at 90°, 180°and 270°relative to 0°(horizontal position) were–1.24%,–1.07% and–0.80%, respectively. For the vibration tests at 1 m/s² and 5 m/s² vibration acceleration, the turbine flowmeter, the electromagnetic flowmeter and the ultrasonic flowmeter showed deviations that ranged from −0.2% to −0.5%, −0.6% (2.6 m³/h), and 0.0% (negligible), respectively. In the durability tests, the accuracy of all three types of heat flowmeters remained at ±1% or less, showing sufficient durability. In the field test, the deviation of the turbine flowmeter and the ultrasonic flowmeter showed ±2.5% or less deviation. However, the electromagnetic flowmeter seems to be inaccurate below 6.9% of the maximum flow rate.     

Systematic investigation of pipe flows and installation effects using laser Doppler anemometry—Part I. Profile measurements downstream of several pipe configurations and flow conditioners

The first part of this paper reports on an automated facility designed to investigate the influence of disturbed flows in pipes on the shift of the error curves of gas flowmeters in situ. This facility can be equipped with several pipe configurations (single and double bends, convergent and divergent sections, straight pipes up to 40 diameters in length etc.) as well as with various types of flow conditioners. It works with atmospheric air at flowrates of up to 5500 m³/h. A two-component semiconductor Laser Doppler Anemometer (LDA) is used to measure the spatial velocity and turbulence fields of the flow along the entire cross section in front of the flowmeter to be investigated. More than 150 velocity distributions have been determined for different pipe configurations at several flowrates and data have been collected to describe the corresponding flowmeter's behaviour. Some typical velocity profiles for the most usual pipe elements and flow conditioners are shown.

The second part of the publication, which will be presented in the following, compares the changes in the meter behaviour with the specific development of the flow characteristics downstream of the pipe configurations investigated. The model found to explain these metering effects will be described, evaluated and verified.     

Ultrasonic pulse-Doppler flow meter application for hydraulic power plants

At hydraulic power stations, Pitot tubes have commonly been used to measure flow rates in steel penstocks for performance testing of hydraulic turbines. Due to the difficulties of Pitot tube installation, transit-time ultrasonic flow meters are becoming a popular replacement, but their accuracy is sensitive to velocity profiles that depend on Reynolds numbers and pipe surface roughness. Ultrasonic pulse Doppler flow meters have recently gained favor as suitable tools to measure flow rates in steel penstocks because they can measure instantaneous velocity profiles directly. Field tests were conducted at an actual hydraulic power plant using an ultrasonic pulse Doppler flow meter, and it was found capable of measuring velocity profiles in a large steel penstock with a diameter of over one meter and Reynolds number of more than five million. Furthermore, two ultrasonic transducers were placed on the pipe surface to validate the multi-line measurement of asymmetric flow. Each transducer recorded the velocity profile simultaneously from the pipe centerline to its far wall during plant operation. Velocity profiles were obtained from three-minute measurements to improve the accuracy of flow rate measurements.     

Investigation into calibration performance of small volume prover for hydrocarbon flow

Several kinds of commercial flowmeters, namely, Coriolis flowmeters, turbine meters, ultrasonic flowmeters, and positive displacement flowmeters, have been calibrated using the primary standard for hydrocarbon flow measurement in Japan (which is based on static and gravimetric methods with a flying start and finish) and a small volume prover (SVP) at the same calibration condition in order to investigate the performance of the SVP. The differences in calibration results for the mechanical flowmeters between the primary standard and the SVP apparently depend on the flow rate, although the results show agreement within 0.04%. The computer-based flowmeters, which have a time delay in the output pulse signal, indicated larger differences due to the effect of the sudden flow rate change caused by the proving action of the SVP at larger flow damping times.     

Estimation of flow rates of individual phases in an oil-gas-water multiphase flow system using neural network approach and pressure signal analysis

Up until now, different methods, including; flow pressure signal, ultrasonic, gamma-ray and combination of them with the neural network approach have been proposed for multiphase flow measurement. More sophisticated techniques such as ultrasonic waves and electricity, as well as high-cost procedures such as gamma waves gradually, can be replaced by simple methods. In this research, only flow parameters such as temperature, viscosity, pressure signals, standard deviation and coefficients of kurtosis and skewness are used as inputs of an artificial neural network to determine the three phase flow rates. The model is validated by the field data which were obtained from separators of two oil fields and 6 wells over ten-month with 8 h interval (totally 5400 sets of data). A linear relation can be observed between the actual data and the predictions which were obtained from separators and neural network approach, respectively. Furthermore, it is shown that using feed forward neural network with Levenberg–Marquardt algorithm which has two hidden layers is sufficient to determine the flow rates. Also, it is tried to see the effect of flow regimes on the results of neural network approach by determining kurtosis and skewness coefficients for different flow regimes in a horizontal pipeline.     

Flow profile identification with multipath transducers

Accuracy of flow rate determination is very critical to an ultrasonic gas flowmeter, which is sensitive to the flow profile under measurement and cannot be obviously improved with traditional weighted integration methods for multipath transducers. Therefore, on one hand, more attentions are paid to intelligent learning algorithms (e.g. artificial neural networks) in recent studies to accurately construct the mapping relation between multipath velocities and the flow rate. However, the bottleneck that a trained network is only customized for a certain flow profile greatly restricts its application. On the other hand, many researchers turn to reconstruct the flow field but so far all flow visualization methods cost too much and are difficult to realize online. In this paper, an intelligent method of flow profile identification for multipath ultrasonic flowmeters is developed to solve the above predicament. Based on support vector machine, a multiclass identifier is constructed to automatically identify the flow profile to be measured from 65 typical flow patterns. Extremely high identification accuracy of 99.49% for test and 100% for training is achieved while the test result still reaches 88.46% even when a measurement uncertainty of ±2% is considered. A comparison with extreme leaning machine further reveals the identification performance and robustness of the proposed flow profile identifier. Different piping configurations, installation positions and angles can be therefore accurately identified, which indirectly realizes the flow visualization and can comprise an intelligent system of ultrasonic flow measurement when combined with the intelligent flow rate determination algorithms.     

电触头钎焊接头超声检测信号的集成神经网络分类

研究电触头钎焊接头超声无损检测中的缺陷分类问题,提出了一种新的集成神经网络分类方法。该方法分四步：频率不变性预处理,多分辩分析,特征量预处理,集成 Ｂ Ｐ神经网络分类。使用不同中心频率探头检测得到的缺陷信号首先通过预处理变换到一个等效的参考频率上,然后利用离散小波变换提取特征量。特征量被预处理后,输入到集成 Ｂ Ｐ神经网络分类器中分类。本文用２１３ 个超声检测信号测试了集成神经网络的性能。实验结果表明了频率不变性技术和集成 Ｂ Ｐ神经网络分类技术的有效性。     

连续波超声多普勒管道流量测量

介绍了一种采用连续波超声多普勒方法的管道流量测量系统。该系统在单片数字信号处理芯片上运用中频解调、选带傅立叶变换和加权平均频率估计等算法对连续波超声多普勒信号进行处理。解决了传统超声多普勒流量计在管道流量测量中遇到的低流速测量困难和无法判断流速方向等问题。     

Correction of flow metering coefficients by using multi-dimensional non-linear curve fitting

Flow disturbances can significantly affect flow metering because the downstream flow of flow disturbances can become unstable and asymmetric, thus resulting in measurement errors in the flow meter. A clamp-on type ultrasonic flow meter is an example of a flow meter that is susceptible to flow disturbances given its diametrical configuration of ultrasonic paths. Several flow rate correction formulas have been suggested to mitigate the effect of flow disturbance for improved flow metering. As a novel method, a multi-dimensional non-linear correction formula is suggested to overcome limitations in flow metering that are attributed to the non-linearity of flow disturbances. The non-linear correction formula comprises n-th order polynomials with multiple variables. To validate the usefulness of the non-linear correction formula, the standard error of estimate (SEE) is introduced. Four types of flow configurations, namely, downstream of a contraction pipe, an expansion pipe, a single elbow joint, and a tee joint, are used to show the effect of the non-linear correction formula. The expanded uncertainty based on the SEE indicates estimated values of 1.29%, 11.14%, 1.07%, and 6.31% for the four upstream flow configurations, respectively. Thus, the effect of the non-linear correction formula is limited according to the upstream flow conditions. In the downstream flow of the contraction pipe and of the single elbow joint, the non-linear correction formula not only harmonizes the distribution of the flow rate deviations but also removes the biases of flow rate deviations with respect to the flow velocity, the installation location, and the diameter ratio.     

Development of side wall type permanent magnet flowmeter for sodium flow measurement in large pipes of SFRs

Sodium cooled Fast Reactors (SFR) require measurement of liquid sodium flow in its primary and secondary circuits. For the primary system of the pool type concept of SFR design, flowmeters have to be immersed in sodium pool and require flow sensors which can withstand high temperatures up to 550 °C, nuclear radiation and chemically reactive sodium environment. Secondary circuits and safety grade decay heat removal (SGDHR) circuits of SFR need flow measurement in stainless steel (SS) pipes of diameter varying from 15 mm to 800 mm. For small pipes, flowmeters with permanent magnet flowmeter with ALNICO-V magnet assembly is the unanimous choice. Conventional permanent magnet flowmeters (PMFM) for large pipelines become bulky, heavy and have installation problems. For sodium flow measurement in large pipelines a few other alternate methods are considered. In the case of Prototype Fast Breeder Reactor (PFBR), which is at an advanced stage of construction at Kalpakkam, flow in the 800 mm diameter secondary main circuit is measured by means of a bypass flowmeter. Other sensors that could be deployed include eddy current flowmeters (ECFM), which are introduced into the pipe to measure flow velocity in the pipe, ultrasonic flowmeters and permanent magnet based side wall flowmeters. In permanent magnet based side wall flowmeter (SWFM), a permanent magnet block is mounted on one side of the large pipe and the magnetic field produced by the magnet penetrates through the pipe and interacts with the flowing sodium and induces an electro motive force (emf) proportional to the flow. This is a compact, cost effective and fairly accurate method for flow measurement in large pipelines of SFR circuits. SWFM is suitable for pipelines of 100 mm and above. In the present work a side wall flowmeter for 100 mm pipe is designed, manufactured, calibrated and tested in an existing sodium facility. Voltage signal developed in SWFM for different flowrates was simulated with three dimensional Finite Element Model (FEM) and validated with experimental results. Effect of asymmetric magnetic field on flowmeter voltage signal and dependence of flowmeter voltage signal on position of electrodes was also analyzed with model. The feasibility of use of this type of flowmeter for large pipelines of SFRs is demonstrated.     

Effects of water in oil and oil in water on single-phase flowmeters

The effect of two-phase flow on the performance of a range of single-phase flowmeters has been investigated experimentally using the National Standard Multiphase Flow facilities at NEL. The flowmeters tested were 2-inch and 4-inch positive displacement meters, venturi meters, helicoidal and flat-bladed turbine meters, 2-inch U-tube, 3-inch and 1.5-inch straight tube Coriolis meters and a 4-inch vortex shedding meter. The flowmeters were tested in oil flow with water and water flow with oil. The second component fractions were varied from 3% up to 15% by volume. The aim of the project was to quantify the effect of second-phase fluid components on the basic uncertainty of a range of single-phase. These tests have provided evidence of the suitability of particular flowmeters for two-component flow applications. Comparisons have been made between generic type and size of flowmeter. The oil-in-water and water-in-oil tests indicated that the uncertainty in the outputs of the flowmeters tested were generally within ±1% relative to the reference flowrates, although some errors as high as 5–10% were also observed. Most of the measurements from the turbine flowmeters and the positive displacement flowmeters were within ±0.4% of the reference flowrates.     

基于神经网络软测量的动态流量测量方法研究

文章以圆管中的粘性流体为研究对象,分析了管道中压差、温度、速度的变化对动态流量的影响,设计出了用于软测量建模的RBF神经网络结构;与此同时,还设计了动态流量测量管,并在伺服阀动态性能试验台上采集了相关数据,其间采用超声波类时差法测量了流速信息;利用采集的数据基于NeuroSolution软件对RBF网络进行了学习训练、检验和测试,最后建立了动态流量的软测量模型;通过将流量预测曲线与实测曲线相对比,结果发现该软测量模型具有很高的逼近精度,它可为动态流量的测量提供一条新的途径.     

High-frequency transducers and correlation method to enhance ultrasonic gas flow metering

Research activities carried out in past years have shown that in gas networks some constraints exist on the frequency at which ultrasonic transducers can be operated. The study of the transmission and attenuation of the signal and noise mechanisms gives us a defined suitable frequency range (K.R. Wild, A European collaboration to evaluate the application of multi-path ultrasonic gas flow meters, paper presented at 4th International Symposium on Fluid Flow Measurement, Denver, CO, 1999). A working frequency of 500 kHz proves to be the most suitable to avoid noise effects. This frequency is above the noise level detected in gas pipelines. Moreover, the signal loss due to attenuation of ultrasound in gas is still negligible.In parallel, the use of this frequency allows the application of efficient numerical techniques such as the cross-correlation method for signal processing. An initial process based on this method has been developed for gas flowmeters. It provides low uncertainty for the parameters involved in the flow measurement process.A single-path flowmeter equipped with this system has been tested on the Gaz de France test facilities. Its accuracy is better than 1.5% from 250 to 1000 m³/h without initial adjustment. An auto-calibration process also forms part of the system, using a systematic comparison between ultrasonic measurement of sound velocity and a theoretical approach. The signal-to-noise ratio remains large enough to perform the measurements correctly, even with a control valve installed close to the flowmeter.     

A hybrid signal pre-processing approach in processing ultrasonic signals with noise

Ultrasonic techniques have the potential to be used to detect sub-surface defects in aluminium castings. However, ultrasonic sensing techniques have not been successfully used to detect sub-surface defects in aluminium die castings with rough surfaces or in the ‘as-cast’ state due to the poor quality of signals. Ultrasonic signal noise caused by rough surfaces and grain size variations of the castings is difficult to eliminate. Hence, there is a need to process noisy ultrasonic signals to identify defects within the rough surface castings. This paper documents an investigation of ultrasonic signal analysis using artificial neural networks and hybrid signal pre-processing approaches for the purpose of detecting defects from noisy ultrasonic signals. In this investigation, ultrasonic signals were obtained from aluminium castings with different levels of surface roughness. The signals were first pre-processed using hybrid signal analysis techniques and then classified using an artificial neural network classifier. The hybrid pre-processing techniques utilised various combinations of fast Fourier transform (FFT), wavelet transform (WT) and principal component analysis. The best signal classification performance was generally achieved with a hybrid WT/FFT signal pre-processing technique.     

大量程柔性铰六维力传感器静态解耦的研究

为提高大量程六维力传感器的测量精度,提出了一种新型的六维力传感器非线性静态解耦方法,该方法结合混合递阶遗传算法和小波神经网络的优点,采用递阶遗传算法与最小二乘法分别对小波神经网络隐层结构参数以及输出层权值进行优化,再将优化后的小波神经网络模型用于六维力传感器非线性解耦.建立了基于混合递阶遗传算法和优化小波神经网络的六维力传感器非线性解耦模型,设计了基于混合递阶遗传算法的小波神经网络结构及参数优化算法,给出了六维力传感器非线性解耦的具体实现流程.以最新研制的6-UPUR大量程柔性铰六维力传感器为对象进行实验,结果表明,采用该方法六维力传感器的Ⅰ类误差和Ⅱ类误差分别为1.25％和2.59％,比采用BP和RBF神经网络方法的测量精度高.     

A study of ultrasonic propagation for ultrasonic flow rate measurement

For the purpose of accurate flow measurement, an automatic three-dimensional (3D) sound field measurement system has been developed, and an experimental study has been conducted on ultrasonic properties. By using this system, ultrasonic sound pressure distributions and radiation angles in water have been measured. According to Snell’s law, the ultrasonic transmission properties can be obtained on the basis of incidence angle, acoustic impedance, basic frequency of ultrasound, and material and thickness of the metallic plate. However, this law cannot be applied to certain cases where an ultrasonic incident wave passes through a metallic plate and turns into a longitudinal wave, a shear wave and a Lamb wave. Consequently, the ultrasonic propagation paths have been investigated experimentally at various angles of incidence. From the experiments, it was confirmed that the ultrasonic beam paths change with incidence angles. Hence, the most suitable incidence angle has been determined from the result of measurements. Velocity measurements using an ultrasonic velocity profiler were made at various incidence angles. The accuracy of measuring flow rates changed with the incidence angles. The optimal incidence angle determined from 3D field measurements was found to yield the most accurate flow rates.