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Ring-shaped electrostatic flow meters can provide very useful information on pneumatically transported air-solids mixture. This type of meters are popular in measuring and controlling the pulverized coal flow distribution among conveyors leading to burners in coal-fired power stations, and they have also been used for research purposes, e.g. for th...
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Experiments are performed in a dense-phase pneumatic conveying system of pulverized coal, and electrostatic signals and coal particle distribution images over cross-section of the pipeline at superficial gas velocities of 5.7 m/s, 6.9 m/s, and 8.1 m/s are obtained through use of electrostatic sensor arrays (ESA) and electrical capacitance tomograph...
Particle velocity is an important parameter of dense-phase gas-solid flow for both monitoring and control purposes. This paper presents a recent development in the noncontact measurement of solid particle velocity using an electrostatic sensor array (ESA). The electrostatic sensor array with eight electrodes is used to collect electrostatic signals...
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... Many publications relate to measurement of flow velocity via the cross-correlation technique [17][18][19][20] . Another avenue is modelling of the sensor in order to predict its output [21] with regards to flow rate, concentration etc. with consideration of effects of various parameters including velocity, with some studies utilising measured velocity to compensate its apparent effect on the measured voltage, [20] as a way to improve measurement accuracy. ...
... The focus of this paper is more relatable to the latter, though presents findings in the form of a novel calibration function and models exhibiting a higher level of accuracy to those previously described [20][21] , with a reduction in design complexity by de-necessitating determination of air-solids ratio or solids volumetric concentration. The described approach differs to other methods in the literature which often deploy complex apparatus [2][3][4][5][6][7][8] for measurement of solids volumetric concentration (e.g. via tomography, radiation/absorption, digital imaging techniques) in addition to velocity measurement (often via cross-correlation [22] ), combining both of which to obtain an indirect measurement value for mass flow rate. ...
... A model for the calibration of an electrostatic flow sensor of this type has been presented previously by Zhang [21] . This model expressed meter output voltage as a function of air-solids ratio and massflow rate, but did not incorporate particle velocity, or at least not as a distinct variable, and was of the form; ...
In this paper, modelling and machine learning with experimental data and a novel calibration function for a gas-solid flow sensor fusion are presented. Sensor fusion is the use of software that intelligently combines data from multiple sensors in order to improve overall system performance. This technique can be applied to measurement of mass flow rate of solids in a pipeline with non-intrusive electrostatic techniques. Data fusion from multiple heterogeneous/homogenous sensors can overcome the limitations of an individual sensor and measured variable. It is shown that the output voltage of a ring-shaped electrode is predominantly a function of solids mass flow rate and velocity for a flow of bulk solids in a pipeline, when particle size, properties and ambient conditions remain constant. By incorporating solids flow velocity in a proposed mathematical model (obtained via machine learning), meter output voltage could be predicted with superior accuracy, for wide range of different flow parameters from numerous experiments with a pneumatic conveying system. Transposing the model yields a new calibration function which, when deployed in signal processing software, enables accurate mass flow measurement with velocity compensation. The described method also de-necessitates determination of air solids ratio or solids volumetric concentration, thereby enabling simplification of the overall measurement system whilst yielding higher accuracy than calibration methods from previous studies. Accurate flow measurement facilitates enhanced monitoring and controllability of blast furnaces, power stations, chemical reactors, process plants etc. where there are bulk solids flows in pipelines. Optimisation of such highly materially consumptive and energy intensive processes can yield significant reductions in waste and emissions (CO2, NOx) and increased efficiencies in global production of energy and materials.
... Due to the short axial width of electrodes, it is generally consid-60 ered that the collision probability between particles and electrodes 61 is extremely low. Therefore, the signal from inner flush-mounted 62 electrostatic sensor is treated as mere induced charge signal and 63 processed by the same methods as the signal from outer surface 64 mounted electrostatic sensors [5][6][7]. However, we found that the 65 spectrum of the inner flush-mounted electrode sensor was different 66 for that of the outer surface-mounted electrode sensor in the low 67 frequency band, which mainly came from the transferred charge 68 signal [8]. ...
The measurement signal from the inner flush-mounted electrostatic sensor includes both induced charge signal and transferred charge signal. The extraction of induced charge signal from the mixed signals is of great significance to the solid phase velocity measurement. In this paper, a method of extracting induced charge signal based on the waveform characteristic in time domain is proposed. In the calibration experiment of the belt-style electrostatic velocity measurement rig, the mean absolute percentage error and the mean relative standard deviation (1.30%/1.01%) are lower than the direct cross-correlation method (4.81%/5.71%) and the Empirical Mode Decomposition (EMD-based) method (2.55%/2.38%), moreover, the average signal-to-noise ratio (SNR) of the proposed method is the greatest. In the experiment of gas-solid two-phase flow rig, the average correlation coefficient and the mean relative standard deviation are 0.77 and 2.46%, which are better than the direct cross-correlation (0.48/2.87%) and the Discrete Wavelet Transform (DWT) (0.74/2.69%).
... But due to the short axial width of electrodes, the probability of the contact between particles and electrodes is often assumed to be very small and the difference between the signals obtained from two sensor types is always neglected. As a result, the signal from inner flush-mounted electrostatic sensors is treated as mere ICS and processed by the same methods as the signal from outer surface mounted electrostatic sensors [12][13][14]. However, Wang et al. [15] found the difference of frequency characteristics between ICS and TCS. ...
The inner flush-mounted electrostatic sensors are widely used for measuring gas-solid two-phase flow in many industries. The measured signal contains induced charge signal (ICS) and transferred charge signal (TCS). According to the band characteristics of the ICS, an adaptive decomposition method based on discrete wavelet transform (DWT) is proposed to extract ICS from measured signals of the sensors. In the measurement of the cross-correlation particle velocity, the mean cross-correlation coefficient between the extracted ICS from upstream and downstream electrodes is 0.74, increased from the previous coefficient 0.48 between the overall measured signals collected from the electrodes. This significant increase shows that the ICS better serves the measurement with higher accuracy. Meanwhile, the mean relative standard deviation (RSD) of the solid velocity is reduced from 3.35% to 2.69% after decomposition, which brings better stability. In addition, the root-mean-square (RMS) of the extracted TCS shows a trend of linear increase as the solid mass flow rate and superficial air velocity rise, indicating that TCS can also serve as an effective method to predict the solid mass flow rate as an alternative to ICS.
... Xu et al. 3,4 studied the sensing characteristics and signal processing methods of ring-shaped electrostatic sensors, which were used for flow parameter monitoring. 1,19,20 However, a ringshaped one only provides the integrated signals from all the particles present in the sensing zone, thus lacking local information for some monitoring objectives, such as flow pattern and fault location. By making a tradeoff between the two types of electrostatic sensors, we proposed hemisphere-shaped electrostatic sensors. ...
... Therefore, the actual electrostatic field will be different from that under the simplified boundary condition. Consequently, the actual dynamic sensitivity will be different from that described by equation (20) to some extent. ...
... They should cover almost the whole section. Then, values of the uncalibrated analytical dynamic sensitivity are calculated by equation (20) at the points. Next, an FEM simulation model is built to emulate the actual boundary condition, by which values of the simulated dynamic sensitivity are obtained at the To ensure the accuracy of the calibrated model, first, the uncalibrated model has to be accurate under the common simplified boundary condition. ...
Electrostatic sensors are key components of electrostatic monitoring systems. Their sensitivity characteristics have a direct influence on monitoring accuracy. In previous studies, spatial sensitivity, which is called static sensitivity here, was used to describe the sensitivity characteristics. However, it only reflects a basic relationship between static charged particles and induced charges on an electrostatic sensor’s probe. Besides, as a three-dimensional defined parameter, it is difficult to build a unified model if actual boundary conditions are considered. Thus, it is not quite proper for applications that detect moving particles. To solve this problem, dynamic sensitivity is proposed in this article. As for a hemisphere-shaped electrostatic sensor, first, a more accurate model of static sensitivity is built. Based on it, dynamic sensitivity is defined and modeled analytically. Then, a calibration method is proposed to improve the model’s accuracy under actual boundary conditions. In the end, finite element method simulations are done for validations. The results demonstrate that dynamic sensitivity reflects a relationship between moving charged particles and the actual output signals of a sensor, thus it is direct and practical for moving particles. And the theoretical results are highly consistent with the simulated ones. Moreover, the dynamic sensitivity indicates localized sensing characteristics of hemisphere-shaped electrostatic sensors.
... 开发出许多方法。其中, 最有前途的方法(即达到应 用状态的方法)是静电、微波和声学技术 [21] [24] 。 英国 Teesside 大学同样建立了一套负压气固两 相流实验装置 [36][37] 2) 对于静电传感器优化, 评价传感器"几何特 性"及"空间阵列"属性的指标体系不完备, 目前优 图 9 天津大学气固两相流实验装置 Fig. 9 Gas-solid two-phase flow test rig of Tianjin University of pneumatically conveyed solids using electrodynamic sensors [J]. Measurement Science and Technology, 1995, 6 (5): 515-537. ...
The exhaust debris of gas turbines contains important information about deterioration and faults of the gas path components. Electrostatic monitoring, which has advantages of real-time, robustness and low cost, is efficient in detecting the debris, making it a promising method for gas turbine PHM. However, electrostatic monitoring systems with a single sensor have a significant shortcoming of inhomogeneous and localized special sensitivity, which would affect the monitoring accuracy. To solve this problem, an exhaust debris monitoring method by using a planar array of hemisphere-shaped electrostatic sensors is discussed in this paper. Firstly, a spatial sensitivity model of the planar array is built based on the Poisson equation. Then, as for abnormal debris, a component extraction-based algorithm is proposed to achieve fast processing of the array signals. In the end, accuracy of the models and efficiency of the algorithm are validated by FEM and numerical simulations. The results indicate that the models built in this paper are accurate. In addition, as for an electrostatic monitoring system, the array signal processing algorithm makes a significant contribution to improving the homogeneity of its sensitivity, thus the sensing accuracy is improved remarkably, especially in the central zone of the exhaust pipe.
Electrostatic sensor has been widely used in process industry in addition this sensing approach has attracted significant attention of flow measurement community because of its advantages including robustness and low costs. This paper focuses on the theoretical analysis of several electrostatic electrodes, including ring, quarter-ring, pin, and rectangular; after that, they are mathematically modelled and simulated by Mathcad software. The geometric measurements of electrodes are considered as important parameters, which affect the results of simulation. However, spatial sensitivity and statistical error are the sensing characteristics of electrodes, which play major roles in modelling these electrodes. The thickness of an electrode, as a parameter influencing spatial sensitivity, is investigated in this study. Increasing the thickness of electrode leads to increase both spatial sensitivity and statistical error while maximum spatial sensitivity and minimum statistical error are desirable parameters. Therefore, the best thickness value of an electrode must be determined to achieve the required uniform spatial sensitivity. Good verification between experimental tests and the mathematical model suggests a reasonable model of electrostatic sensor electrodes.
Gas-solid two-phase flow is complicated and random, gas-solid two-phase flow standard facility is a very important method for the study of gas-solid two-phase flow problem. As to the design requirements of standard facility, a gas-solid two-phase flow standard facility used to calibratio electrostatic sensor is designed.
