Improvements to dust filtration through acoustic agglomeration and atomization

ABSTRACT

Based on the theories of acoustic agglomeration and dust wet removal, an experimental apparatus was constructed to study the combined effects of acoustic agglomeration and atomization humidification in the pretreatment process to analyze the filtration performance of filter material. According to the concentration of coal-fired fly ash chosen in the experiments, the proper amount of atomization humidification and the proper sound pressure level (SPL) were determined. Under the relative humidity (RH) of 69% and with SPL in the range of 100 dB to 135 dB, the removal efficiency of fly-ash, the compressibility of the fly-ash particle layer on the filter media, and the performance of pulse filter cleaning were studied. The results indicate that the combined effects of sound fields and atomization humidification can effectively remove PM₁₀ and PM_2.5, and change the interaction and movement of particles, which can improve the pore structure of the fly-ash particle layer and increase the porosity of the dust layer. The results also indicate that with the proper amount of atomization humidification and appropriate SPL, the joint acoustic-atomization pretreatment can delay the filter material blocking, which reduces the pulse filter cleaning frequency and extends the filter cleaning cycle. It can also reduce the residual resistance after filter cleaning and prolong the operating lifetime of the filter media.

© 2017 American Association for Aerosol Research

Editor:

• Jing Wang

1. Introduction

Due to the complex chemical compositions of fine particulate matter in the atmosphere, there is potential for serious harm to human bodily health from long-term exposure to haze. Tao et al. (2014) have shown that the inhalable particulate matter with diameters less than 10 μm, and especially less than 2.5 μm, may damage the respiratory system and may in particular cause cardio-cerebrovascular diseases. The coal-fired industry is an important source of fine particulate matter in the atmosphere, thus improving existing dust removal technology and reducing discharge concentrations are important steps toward controlling air pollution (García-Nieto 2006).

Acoustic agglomeration is one of the most effective preconditioning process, which makes the fine particles collide and agglomerate to shift dust distribution toward larger size and reduce the number of fine particles, and ultimately improves the dust removal efficiency of the dust collector (Volk and Moroz 1976; Reethof 1985; Xu et al. 2008; Zhang et al. 2009). Many numerical simulation and experimental works have thus been performed to study this pretreatment technology. Recently, Xu et al. (2008) developed an aerosol dynamics model of flue gas in acoustic agglomeration based on the orthokinetic and hydrodynamics interaction as main mechanisms and numerically got the particle size distribution curve that was in good agreement with experimental results: the number of fine particles decreased and the average particle size increased compared with initial particle size distribution without agglomeration. Acoustic agglomeration is sensitive to the change of frequency and under moderate-intensity acoustic fields, higher sound pressure level can yield better agglomeration effects. Zhang et al. (2009) and Yang et al. (2014) researched the hydrodynamics, orthokinetic, and Brown effect agglomeration mechanism in acoustic agglomeration, and acoustic frequency, sound field intensity, particle size, and particle spacing of the particles were calculated. The result showed that a considerable effectiveness of agglomeration could only be obtained in a narrow frequency range and beyond the range, the agglomeration efficiency would decrease. In addition, the simulation result also showed that the total number concentration of aerosol decreased exponentially with time in the acoustic agglomeration process.

Although sound condensate pretreatment can yield a good effect on dust removal, there exists the problem of high energy consumption in the process. Therefore, the researchers have studied the technology of acoustic agglomeration combined with conventional dust removal devices or other agglomeration technology that can further improve the removal efficiency and effectively decrease energy consumption (Riera et al. 2000; Moldavsky et al. 2006). Heidenreich et al. (2000), Schabe et al. (2002), and Kryukov et al. (2004) conducted the researches on the atomization humidification, which indicated that atomization humidification technology as another pretreatment technology can effectively promote particle agglomeration through the effect of supersaturated steam on the surface of fine particulate matters. The pretreatment combined acoustic agglomeration with atomization is a potential technology for dust removal and the agglomeration efficiency is substantially improved compared with that used a sound field or atomization alone. Yang et al. (2011), Wang (2012), and Yan et al. (2014) performed experimental studies on the removal effects of fine particulate matter with the combined effects of different acoustic intensities and degrees of water vapor saturation. Their results showed that the pretreatment combined acoustic agglomeration with atomization could intensify the collision among particles and promote their agglomeration under the air with different relative humidity. Ultimately, the removal efficiency is substantially improved over experiments that used a sound field alone.

In the experiments of this article, instead of water vapor the ultrasonic atomization was utilized to attempt a new way of combination. Under the combined effects of acoustic agglomeration and atomization, the particles collide and agglomerate with each other and then settle or deposit onto the filter media. This combination also helps to improve subsequent filtration performance. Due to the complexity of the whole process, it is needed to analyze the deposition behavior of particles in the joint acoustic-atomization pretreatment process. Long et al. (2007) have indicated that particle would be affected by multiple forces. After atomization humidification, the moisture content and the particle adhesion between the fly-ash particles increase. Under the effects of the van der Waals force and the sound field, the particles collide with each other to form aggregates via the “liquid bridge.” Yang et al. (2011) gave the equations of the van der Waals force and the capillary force. The result shows that for fine particles (from 0.1 μm to 10 μm), the capillary force is commonly 10⁻⁶ to 10⁻⁸ N, while the van der Waals force is commonly 10⁻¹² to 10⁻¹⁰ N. So once particles contact with each other, the capillary force exceeds the van der Waals force and becomes the dominant force. The aggregate is much stronger under capillary action. It is advantageous to form larger aggregates, which increase the removal rate, especially when the particle deposits on the surface already covered with deposited particles.

Under the effects of sound waves, a steady flow called acoustic secondary flow will be produced around the particles. Moldavsky et al. (2006) gave the calculation of the velocity of the secondary flow. The flow velocity decays rapidly with the increasing distance between acoustic secondary flow and particles. Therefore, the shorter the distance, the greater the flow velocity, which causes the deposition track of the particle to migrate.

In this article, based on the theories of acoustic agglomeration and atomization, the experiments were conducted at the relative humidity (RH) of 69% and with SPL in the range of 100 dB to 135 dB to study the filtration performance of filter material. The pre-removal efficiency of fly-ash, the compressibility of the fly-ash particle layer on the filter media and the performance of pulse filter cleaning were also investigated. It is hoped that this study will provide the reference and advice for the technical applications.

2. Experimental facility

2.1. Experimental device and methods

The experimental device was built referring to the United States American Society for Testing and Materials (ASTM) standard method D6830-02 and International Organization for Standardization (ISO) method 11057 (Pham et al. 2012). As shown in Figure 1, under the effect of a vacuum pump, the system runs under negative pressure. Water spray is produced by an ultrasonic humidifier (YC-D205, Beiking Yadu Environmental Protection Technology Co., Ltd., Beijing, China) and enters the system from the bottom of an imported flow meter. The water spray mixes with dust particles produced from the dust generator in the pipeline and then enters the agglomeration chamber, which is 70 mm in diameter and 1300 mm in length. The chamber can be opened on the end to test the sound pressure. Under the effects of the water atomization and an acoustic field in the agglomeration chamber, particles collide with each other and then enter the subsequent settle pipe, with larger particles falling into the ash hopper and the remaining fine particulate matter flowing with the air toward the fibrous filter material. At the end, the filtered airflow is exhausted by a vacuum pump. Fine particles are deposited onto filter material surface and the pressure drop across the filter material increases. When the upper pressure-drop limit is reached, the impulse valve is opened and a high-pressure gas, after purifying in the gasbag, sprays out at high speed though the impulse valve, which blows off the dust layer on the filter material, and then the next cycle of filtering begins.

Figure 1. Schematic of experimental apparatus.

In the experiments, signal generator (YB-1613, Jiangsu Green Yang Electronic Instrument Group Co., Ltd., Yangzhong, Jiangshu. China), power amplifier (AWA5870B, Hangzhou Aihua Instrument Co., Ltd., Hangzhou, Zhejiang, China), and alarm speaker (KTD-250, Taixing Ketailai Electronics Co., Ltd., Taixing, Jiangshu, China) are main equipments of sound source. Sine wave with a specific frequency generated by signal source is amplified by the power amplifier and forms a sound field with a specific frequency and SPL. The frequency and intensity of the sound field can be changed by adjusting the frequency of signal source and the amplification factor of power amplifier. SPL can be measured by sound pressure meter (HY104H-C, Hengyang Hengyi Electric Co., Ltd., Hengyang, Hunan, China) with the measurement range 50 dB–150 dB (A). A particle-grading sampler (FA-3, Qingdao Ju Chong Environmental Protection Equipment Co., Ltd., Qingdao, Shandong, China) based on the Anderson technology was used to gather aerosols from the agglomeration chamber. Particles of different sizes were sampled by a nine-stage cascade impactor and accelerated step by step by orifice plates. The larger particles hit the sample tray and the smaller particles traveled with the airflow to the next levels. After each sampling process ended, the dust quality on the sampling plates of different stages was weighed to obtain the particle size distribution (Pham et al. 2012).

A pressure meter (DP1000-III, Shanghai Green High Technology Co., Ltd., Shanghai, China) was used to automatically record the pressure drop across the fibrous filter. These data were used to construct the pressure drop curves. A laser dust mass concentration meter (LD-6S, Beijing Greenwood Innovation Digital Technology Co., Ltd., Beijing, China) was used to continuously monitor the dust concentration after the filter material. The pressure of the dust-cleaning airflow, which was kept at approximately 0.25 MPa in the experiments, was controlled by the pressure-reducing valve. A pulse valve was operated by a pulse control meter; when the pressure drop across the filter material reached 1500 Pa, the pulse valve opened and closed once with a pulse width of 200 ms.

2.2. Experimental materials

The dust used in the experiments was coal-fired fly ash from a commissary city power station in Tianjin. The true density of the dust in the experiments was 2500 kg/m³, and the packing density is about 780 kg/m³. The particle size distribution after screen filtering by 220# standard sieves was measured by a Malvern Mastersizer 2000 particle size analyzer. This distribution is shown in Figure 2, which shows that the median diameter d₅₀ of the fly-ash particles is 15.4 μm. The filter material used in experiments was the polyester needled felt with PTFE micro-porous membrane made by Fushun Tianyu Filtration Material Co., Ltd. (Fushun, Liaoning, China). The parameters of the filter material are: 507 g/m² of mass per unit area, 2 mm thickness, 2.4 m³/m²/min of air permeability, 86% porosity, 920 N of breaking strength, 1200 N/5 × 20 cm.

Figure 2. Size distribution of the initial fly ash.

2.3. Experimental conditions and design

The concentration of dust in the feed air was kept constant at 10 g/m³, and the experiments were conducted at 22°C and 0.98 atm. The pre-exploratory experiments show that the ratio of the water droplets concentration to the dust concentration (fog powder ratio) is in the range of 0.8–1.5. Therefore, to achieve a better effect of dust agglomeration, adjusting the screw of spray volume in the experiments to make the humidification about 12–15 g/m³. At this point, the relative humidity measured with a hygrometer is about 69% and there is not obvious water mist or drops on the surface of agglomeration chamber. In addition, Zhang (2001) has showed by experiments and model analysis that the small droplet diameter is better to dust agglomeration, so the ultrasonic atomization was used. The size of droplet is tested at 4–10 μm in these experiments.

Liu et al. (2011) have showed that application of low-frequency (1000–1800 Hz) sound source was proved as an advisable pretreatment with the highest agglomeration efficiency. So to achieve a better agglomeration effect, acoustic wave frequency used in the experiments was controlled at 1400 Hz and SPL was changed from 100 dB to 135 dB. This was a moderate-intensity acoustic field controlled by the wave generator. Variations in sound waves can be ignored in the agglomeration chamber because of low attenuation.

The pretreatment process combined the effects of a moderate-intensity acoustic field and atomization humidification. The pre-removal effect of acoustic coagulation and sedimentary characteristics of particles on the fibrous filter material surface were mainly studied in the investigation, which also focused on the filter performance of fibrous filter materials and dust cleaning characteristics. All experimental tests were repeated at least three times. The pre-removal efficiency and concentration parameters were averaged over multiple measurements. Because it is a continuous measurement, the pressure parameters selected a measurement representative from a number of measurements.

3. Experimental results and analysis

3.1. Experimental results and analysis of acoustic field and atomization agglomeration pre-removal

The influence of a moderate-intensity acoustic field combined with the proper amount of atomization humidification was investigated experimentally. As the dust condenses, the dust particles become larger and the gravity settling (pre-removal) occurs in the condensate chamber and the settling chamber. So the pre-removal efficiency not including the filter process was employed to analyze the dust agglomeration. Figure 3 shows that the staged pre-removal efficiency of fly ash is less than 50% without sound field or humidification, while with the improvement of SPL, the all staged pre-removal efficiency of the fly ash increases gradually. However, the pre-removal efficiency of fine particles (smaller than 3 μm), especially that of particle sizes less than 1 μm, is lower than that of larger fine particulate matter (size 3 μm—10 μm). Figure 3 also shows that under different conditions, the staged pre-removal efficiency was improved gradually with the increase of particle size. That is because under the effect of sound waves, small particles are more difficult to remove due to their short relaxation time compared with larger particles. In addition, under the effect of atomized droplets, it is difficult for the small particles to be settled due to the smaller size, which resulted in small contacting area with droplets and small capillary force. Under the combined effect of acoustic agglomeration and atomization, although the pre-removal efficiency of the fly ash in different particle sizes increased gradually, the pre-removal efficiency of small particles is still lower compared with larger particles.

Figure 3. Staged pre-removal efficiency under different conditions.

Under the effect of atomization, small size droplets collide with each other and form larger droplets, which can capture the fine particles under the effects of collision and interception and other dynamic effects. Because the coal-fired fly ash has a higher capacity for wetness, the adhesion is enhanced between fine fly-ash particles and the adhesive force is mainly the capillary force. Water molecules are adsorbed onto particle surfaces and fill the surrounding capillary space. For fine particles (from 0.1 μm to 10 μm), the capillary force is commonly 10⁻⁶ to 10⁻⁸ N, while the van der Waals force is commonly 10⁻¹² to 10⁻¹⁰ N (Yang et al. 2011). When particles collide with each other, a “liquid bridge” is formed between the particles. This allows particles to stick together to form larger particles that can be easily separated from the settle pipeline. Under moderate-intensity acoustic fields, settling and pre-removing effects increase with the increase of the sound pressure level. This is because the higher the sound pressure level, the more intense the vibration of the air medium, as well as the particles in the medium. This increases the relative velocity between particles (Hoffmann et al. 1993), which increasing the frequency of particle collisions.

3.2. Experimental results and analysis of a compressible particle layer filter under acoustic field and atomization pretreatment

3.2.1. Evolution analysis of the pressure drop as a function of mass loading and the mass loading curve

The figure in the online supplementary information (Figure S1) shows the evolution of the pressure drop as a function of mass loading and the mass loading curve under different conditions. In the blank experiment, the pressure drop measured across the filter grows rapidly over time, and its periodic transition is obvious. It is much clearer to see the transition of the pressure drop in the mass loading curve. This is because the deposition of fly-ash particles on the surface of the filter continually compresses the granular layer, which gradually compacts the structure of granular layer, leading to a sharp decrease in porosity that causes a transient increase in the pressure drop. After the atomization pretreatment or joint acoustic-atomization pretreatments, the pressure drop grows slowly and the transition is less abrupt; meanwhile, the pressure drop in the mass loading curve is relatively flat. That is because the acoustic field tends to deflect the approaching particles toward the deposited particles on the filter surface, rather than toward the empty spaces between the particles. Hence, the porosity of the filter cake will increase and the pressure drop across the filter will decrease (Moldavsky et al. 2006). Meanwhile, under the effect of atomization, adhesion between particles enhances and prevents the deposited particles from sliding, which suggests that the sudden compression of the granular layer is reduced and that the pore structure of the granular layer has changed. Kasper et al. (2010) and Xu et al. (2014) have given that dust particles on the filter material and the internal sedimentary structure can have effects on the filtration efficiency and pressure drop.

3.2.2. Estimation of filter cake porosity

Saleem et al. (2012) have given that among the influential parameters of filter cake structure (e.g., filtration velocity and dust concentration), the filtration velocity is the dominant factor, while the influence of the dust concentration is relatively small. Therefore, the filtration velocity must be strictly held constant.

It is difficult to measure the filter cake porosity in the experiment because the filter cake is fragile. Porosity and the resistance coefficient are important parameters that are closely associated with the growth of the pressure drop and the difficulty of dust removal. Porosity can be estimated from Equation (1[1] ), as proposed by Aguiar and Coury (Kasper et al. 2010). According to Equations (1[1] ) and (2[2] ), Equation (3[3] ) can be got and used to calculate the average porosity by testing the filter pressure drops on the different filter time. The resistance coefficient of the filter cake can be calculated from Equation (4[4] ). The average porosity and resistance coefficient of the filter cake are estimated in Table 1.[1] [2] [3] [4]

Here, △P is the filter pressure drops, t is the filter time, L is thickness of the filter cake layer, W is the dust mass, A is the filter area, Q is the mass flow, ρ_p is the density of dust, d_p is the diameter of the dust, replaced by d₅₀, where d₅₀ = 15.4 μm, ρ_g is the gas density, μ is the gas viscosity, ϵ is the filter cake layer porosity, v_f is the filtration velocity (ratio of the volume flow to the filter area), and κ₂ is the resistance coefficient of the filter cake in 10⁴ s⁻¹.

Table 1. Results of cake porosity.

	No acoustic field; no humidification	No acoustic field; RH = 69%	SPL = 115 dB; RH = 69%	SPL = 120 dB; RH = 69%	SPL = 126 dB; RH = 69%	SPL = 130 dB; RH = 69%
κ2(×10^4 s^−1)	11.8	9.5	10.3	7.8	7.9	7.1
Porosity	0.299	0.318	0.311	0.337	0.336	0.346

As shown in Table 1, the porosity structure of the filter cake layer changes under the effect of the sound field and atomization. The porosity is improved, and, with the improvement of sound pressure level, the porosity tends to be constantly improved and the resistance coefficient constantly decreases. This is because the migration of the deposition track of the particle increases with improving sound pressure level, which increases the porosity between the particles. In addition, with the constant improvement of the sound field intensity, the collision frequency between particles increases and the removal efficiency of the acoustic agglomeration increases, which effectively reduces the dust load of the filter material and the drag coefficient.

Under the effect of an acoustic field and atomization, the surface structure of the dust filter material layer is highly improved and the porosity is increased. The dust layer structure is relatively loose, which is conducive to dust-cleaning operations.

3.3. Results and analysis of filter cleaning experiment under acoustic field and atomization pretreatment

3.3.1. Filter cleaning cycle under acoustic field and atomization pretreatment

Figure 4 shows the trends of the pressure drop across the filter media as the cycle progress under the different conditions. Some characteristics such as the growth rate of the pressure drop, the filter cleaning frequency and cycle, the residual resistance after filter cleaning under different conditions are to be analyzed. Table 2 shows the filter cleaning cycle under the different conditions.

Figure 4. Changes in the pressure drop across the filter media under different conditions.

Table 2. Cycle of filter cleaning under different conditions.

Conditions	Filter cleaning cycle(s)
No acoustic field; No humidification	22
No acoustic field; RH = 69%	125
SPL = 120 dB; RH = 69%	500
SPL = 126 dB; RH = 69%	700

Figure 4 and Table 2 indicate that after atomization pretreatment and joint acoustic-atomization pretreatment, the filter cleaning frequency decreases and the filter cleaning cycle lengthens dramatically. It is beneficial to reduce the power consumption during dust cleaning and reduce the abrasion of the filter bag, thus extending the service life of the filter bag.

3.3.2. Analysis of parameters and result of evaluating filter cleaning characteristics of filter material

The influence of the atomization pretreatment and the joint agglomeration-atomization pretreatment on the usage of filter material will be discussed with respect to filter cleaning efficiency (Kanaoka et al. 1999), the filter resistance coefficient (Liu et al. 2002), and the blockage factor (Liu et al. 2002).

Table 3 shows that both atomization pretreatment and joint agglomeration-atomization pretreatment improve the filter cleaning efficiency. The resistance coefficient and the blocking coefficient constantly decrease, making it easier for the dust layer to fall off. Under the conditions of RH = 69%/SPL = 126 dB, the removal efficiency is 87.3%, which is the best condition in these experiments. This is because after pretreatment, when the filter reaches a given pressure drop, the dust structure is improved and the adhesion of dust onto the surface of the filter material is reduced. This makes it easier for the dust to fall off and improves the ash removal performance of the filter material. It also effectively reduces the concentration of fine dust so that fine dust inside of the filter material is reduced, delaying the blocking of dust by filter material and reducing the blocking coefficient.

Table 3. Summary of parameters.

Conditions	Filter cleaning efficiency (%)	Clean filter material resistance coefficient	Regenerated filter material resistance coefficient	Filter material blocking coefficient
No acoustic field; No humidification	58.7	25	117.9	3.72
No acoustic field; RH = 69%	60	25	115.2	3.61
SPL = 115 dB; RH = 69%	63.3	25	107.5	3.3
SPL = 120 dB; RH = 69%	80	25	69.7	1.79
SPL = 126 dB; RH = 69%	87.3	25	53.5	1.14

In addition, according to Silva et al. (1999) work on the breaking strength equation of agglomerate spherical particles, the particle spacing can be estimated as follows:[5] where σ_F* is the tension of rupture that can be regarded as the adhesive force of particles on the filter material per unit area and equal to the residual resistance after filter cleaning. H is the Hamaker constant, which averages 8 × 10⁻²⁰ m for most materials, a is the particle spacing of the dust layer in 10⁻⁹ m, d_p is the diameter of a fly-ash particle, replaced by d₅₀, where d₅₀ = 15.4 μm and ϵ is porosity.

The adhesive force between a particle and the filter material is much stronger than that between particles. The dust layer on the filter material falls off because the agglomeration between particles is broken and residual particles on the filter material become an adsorptive monolayer.

The adhesion force of dust on the filter material and the space between the particles are listed in Table 4. △P_c is the adhesion force that was estimated by testing the residual resistance after filter cleaning. The estimated space between particles is 0.89 × 10⁻⁹ m–1.28 × 10⁻⁹ m, which is consistent with actual values. Generally, the space between agglomerated particles is between 4 × 10⁻¹⁰ m and 4 × 10⁻⁸ m (Silva et al. 1999), which indicates that the estimate is reasonable. Table 4 shows that after pretreatment, with the sound pressure level increased, particle spacing on the filter material is increased and the residual dust layer structure is much looser, which helps to reduce the residual resistance (or adhesion force △P_c) and prolong the service life of the filter material.

Table 4. Results of adhesion force and space between particles.

Conditions	Porosity ϵ	Adhesion force per unit area ΔPc (N/m^2)	Space between particles a (10^−9 m)
No acoustic field; No humidification	0.299	707	0.89
No acoustic field; RH = 69%	0.318	691	0.86
SPL = 115 dB; RH = 69%	0.311	645	0.91
SPL = 120 dB; RH = 69%	0.337	418	1.06
SPL = 126 dB; RH = 69%	0.336	350	1.16
SPL = 130 dB; RH = 69%	0.346	300	1.28

3.3.3. Emission concentrations

Figure 5, which shows the dust concentrations after filter under the different conditions, suggests that the dust layer is destroyed after filter cleaning, causing fine particles to penetrate though the filter material, which reduces the filtering efficiency. Park et al. (2012) also found the same phenomena in the study. During the filtering process, the dust layer constantly recovers and filtration efficiency gradually improves. Under the effects of the acoustic field and atomization, after a certain period of time immediately following filter cleaning, the concentration behind the filter material can be kept at a lower level. In most stable filtering stages between filter cleaning, this concentration is less than 50 mg/m³, or sometimes even less than 10 mg/m³.

Figure 5. Dust concentrations after filter under the different conditions.

Table 5 shows the average dust concentrations behind the filter material under different conditions. These data clearly suggest that after atomization and joint acoustic-atomization pretreatments, the dust emission concentration is substantially lower than it is without pretreatment. Especially under the conditions SPL = 120 dB/RH = 69% and SPL = 126 dB/RH = 69%, the emission concentrations are less than 50 mg/m³, corresponding to decreases in emission concentrations of approximately 44% and 55%, respectively, from the control runs. This further enhances the filtering efficiency of the filter material and achieves the goal of the emission reduction.

Table 5. Average dust concentrations after filter under the different conditions.

Conditions	Average concentration (mg/m^3)
No acoustic field; No humidification	78.96
No acoustic field; RH = 69%	51.06
SPL = 120 dB; RH = 69%	44.16
SPL = 126 dB; RH = 69%	35.49

4. Summary

This article performs an experimental study based on the theory of acoustic agglomeration and atomization. The results of the study show that the combined effect of sound and atomization humidification can effectively improve the dust removal efficiency of coal-fired fly ash. With the appropriate levels of humidification and a moderate-intensity acoustic field, the fine dust within the scope of PM_2.5 and PM₁₀ can be effectively removed.

Under the combined effects of acoustic agglomeration and atomization, the deposition of dust onto the surface of the filter material and the force analysis of this process were studied. Under the action of the acoustic field, the deposition track of the dust particles migrates, resulting in an increase in porosity of the filter cake. Under the effect of capillary action, the adhesive force between particles is enhanced, stabilizing deposited particles and helping prevent them from sliding. It is also difficult to compress the dust layer, resulting in a reduced number of transitions of micro-scale pressure drops. Hence, the structure of the dust layer is improved in the presence of joint acoustic-atomization pretreatment.

Under the combined effects of acoustic agglomeration and atomization, the pulse filter cleaning performance has been studied. The results show that such pretreatment substantially extends the filter cleaning cycle and reduces the filter cleaning frequency. Pretreatment process also delays the blockage of filter material and reduces the residual resistance, resulting in a higher efficiency of the ash removal and a longer operating lifetime of the filter material.

Funding

The authors wish to acknowledge the project supported by the National Natural Science Foundation of China (Grant No. 51278334).