On-line Size Measurement of Pneumatically Conveyed Particles Through Acoustic Emission Sensing

Acoustic emission (AE) methods have been proposed for on-line size measurement of pneumatically conveyed particles in recent years. However, there is limited research on the fundamental mechanism of the AE-based particle sizing technique. In order to achieve more accurate measurement of particle size, the impact between particles and a waveguide should be described in a more realistic way. In this paper, an improved model based on the Stronge impact theory is presented to establish the relationship between the resulting AE signal and the particle size being measured. The improved model is validated with experiments on a single-particle test rig. A total five sets of glass beads with a mean diameter of 0.4, 0.6, 0.8, 1.0 and 1.2 mm, respectively, are used as the test particles with an impact velocity ranging from 22 m/s to 37 m/s. It is proven that the Stronge impact theory is more accurate to describe the collision process than the Hertzian impact theory and is thus more suitable for the particle size inversion, which is validated by comparing the inversion results using these two impact theories. Meanwhile, a good agreement is observed between the measured and reference particle sizes under different experimental conditions. The mean relative error between the measured and reference diameters is mostly within 12%

Electrostatic Sensors – Their Principles and Applications

Over the past three decades electrostatic sensors have been proposed, developed and utilised for the continuous monitoring and measurement of a range of industrial processes, mechanical systems and clinical environments. Electrostatic sensors enjoy simplicity in structure, cost-effectiveness and suitability for a wide range of installation conditions. They either provide unique solutions to some measurement challenges or offer more cost-effective options to the more established sensors such as those based on acoustic, capacitive, optical and electromagnetic principles. The established or potential applications of electrostatic sensors appear wide ranging, but the underlining sensing principle and resultant system characteristics are very similar. This paper presents a comprehensive review of the electrostatic sensors and sensing systems that have been developed for the measurement and monitoring of a range of process variables and conditions. These include the flow measurement of pneumatically conveyed solids, measurement of particulate emissions, monitoring of fluidised beds, on-line particle sizing, burner flame monitoring, speed and radial vibration measurement of mechanical systems, and condition monitoring of power transmission belts, mechanical wear, and human activities. The fundamental sensing principles together with the advantages and limitations of electrostatic sensors for a given area of applications are also introduced. The technology readiness level for each area of applications is identified and commented. Trends and future development of electrostatic sensors, their signal conditioning electronics, signal processing methods as well as possible new applications are also discussed

Online Measurement of the Size Distribution of Pneumatically Conveyed Particles Through Acoustic Emission Detection and Triboelectric Sensing

In a thermal power plant online measurement of the size distribution of pneumatically conveyed pulverized fuel is essential for the improvement of combustion efficiency and the reduction of pollutant emissions. In this paper, an innovative instrumentation system based on acoustic emission (AE) detection and triboelectric sensing is proposed for the on-line continuous measurement of particle size distribution. With a waveguide protruding into the flow, the AE signal is generated from the impacts of particles with the waveguide. The peak voltage of the AE signal is related to the particle size and impact velocity. For the first time, two triboelectric sensor arrays each with three arc-shaped electrodes near to the waveguide are used to measure the impact velocity. Meanwhile, a novel particle sizing algorithm with Gaussian prediction is proposed to reduce the effect of overlapping impacts and environmental noise on the peak distribution. With the known impact velocity measured from the triboelectric sensor arrays and the modified peak distribution, the measurement of particle size distribution is achieved. Experimental tests were conducted on a gas–solids two-phase flow rig to assess the performance of the developed measurement system. Silica sands in three size ranges of 116–750 μm, 61–395 μm and 10–246 μm, respectively, were used as test particles. The experimental results demonstrate that Spearman’s rank correlation coefficient between the measured and reference size distributions for all test particles is all greater than 0.8, while the discrepancy for each particle size segment is within ±4.8%

Online particle size distribution estimation of a mixture of similar sized particles with acoustic emissions

Particle processing plants regard the Particle Size Distribution (PSD) as a key quality factor as it influences the bulk and flow properties of the particles. In this work, Acoustic Emission (AE) is used to estimate the PSD of a mixture that comprise of similar sized particles. The experiments involved the use of regular sized particles (glass beads) and with the aid of a time domain based threshold analysis of the particle impacts the PSD of the mixtures could be estimated

Experimental Investigations into the Use of Piezoelectric Film Transducers to Determine Particle Size through Impact Analysis

Sensors are required to determine the particle size of granular materials in a variety of industries such as energy, chemical manufacturing and food processing. The importance of accurately monitoring the particle size is essential in quality control in these industrial sectors. This paper presents the use of a custom made piezoelectric PVDF film transducer that is capable of determining the particle size of granular material through impact analysis. Experiments were carried out using a purpose-built test rig using ball bearings of different sizes traveling at different velocities. Through power spectral analysis of the impact signal it has been determined that different components of the signal spectrum may relate to different characteristics of the particle itself such as particle impact velocity and particle size. A comparison between the experimental data and system modelling results using the known mechanical characteristics of the test particles shows close similarities

Acoustic emission enabled particle size estimation via low stress-varied axial interface shearing

Acoustic emission (AE) refers to a rapid release of localized stress energy that propagates as a transient elastic wave and is typically used in geotechnical applications to study stick-slip during shearing, and breakage and fracture of particles. This article develops a novel method of estimating the particle size, an important characteristic of granular materials, using axial interface shearing-induced AE signals. Specifically, a test setup that enables axial interface shearing between a one-dimensional compression granular deposit and a smooth shaft surface is developed. The interface sliding speed (up to 3mm/s), the compression stress (0-135kPa), and the particle size (150μm-5mm) are varied to test the acoustic response. The start and end moments of a shearing motion, between which a burst of AE data is produced, are identified through the variation of the AE count rates, before key parameters can be extracted from the bursts of interests. Linear regression models are then built to correlate the AE parameters with particle size, where a comprehensive evaluation and comparison in terms of estimation errors is performed. For granular samples with a single size, it is found that both the AE energy related parameters and AE counts, obtained using an appropriate threshold voltage, are effective in differentiating the particle size, exhibiting low fitting errors. The value of this technique lies in its potential application to field testing, for example as an add-on to cone penetration test systems and to enable in-situ characterization of geological deposits

Particle size distribution estimation of a mixture of regular and irregular sized particles using acoustic emissions

This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated

Mass Flow Rate Measurement of Pneumatically Conveyed Particles Through Acoustic Emission Detection and Electrostatic Sensing

Accurate online mass flow rate measurement of pneumatically conveyed particles is desirable to convert a conventional pulverized fuel fired power station into a smart thermal power plant. This paper presents a novel method for the online measurement of the mass flow rate of pulverized fuel through acoustic emission (AE) detection and electrostatic sensing. An integrated sensing head with an AE probe and three sets of electrostatic sensor arrays is developed. The proposed method determines the particle velocity by multi-channel cross correlation of the electrostatic signals and extracts the information about mass flow rate from the AE signal arising from impacts of particles with a waveguide protruding into the flow. An analytical model that relates the energy of the AE signals, the particle velocity and the mass flow rate is established. The sensing head was mounted on vertical and horizontal sections of a 72-mm bore laboratory-scale test rig conveying fine silica particles. Experimental tests were conducted under a range of flow conditions and installation orientations to assess the performance of the developed measurement system. The results demonstrate that the sensing head should be installed in any orientation away from the elbow on the vertical section of a pipe, while for installation on a horizontal pipe the waveguide should be in the horizontal direction. The instrumentation system is capable of measuring the mass flow rate of particles in the vertical pipe with a relative error within ±6.5% regardless of the orientation of the sensing head over the mass flow rate from 7 kg/h to 25 kg/h and the particle velocity from 12 m/s to 30 m/s. Whilst on the horizontal pipe the error is within ±5.8% when the sensing head is installed with the waveguide in the horizontal direction under the same flow conditions

Particle size distribution estimation of a powder agglomeration process using acoustic emissions

Washing powder needs to undergo quality checks before it is sold, and according to a report by the partner company, these quality checks include an offline procedure where a reference sieve analysis is used to determine the size distributions of the powder. This method is reportedly slow, and cannot be used to measure large agglomerates of powders. A solution to this problem was proposed with the implementation of real time Acoustic Emissions (AE) which would provide the sufficient information to make an assessment of the nature of the particle sizes. From the literature reviewed for this thesis, it was observed that particle sizes can be monitored online with AE but there does not appear to be a system capable of monitoring particle sizes for processes where the final powder mixture ratio varies significantly. This has been identified as a knowledge gap in existing literature and the research carried out for this thesis contributes to closing that gap. To investigate this problem, a benchtop experimental rig was designed. The rig represented limited operating conditions of the mixer but retained the critical factors. The acquired data was analysed with a designed hybrid signal processing method based on a time domain analysis of impact peaks using an amplitude threshold approach. Glass beads, polyethylene and washing powder particles were considered for the experiments, and the results showed that within the tested conditions, the designed signal processing approach was capable of estimating the PSD of various powder mixture combinations comprising particles in the range of 53-1500 microns, it was also noted that the architecture of the designed signal processing method allowed for a quicker online computation time when compared with other notable hybrid signal processing methods for particle sizing in the literature