Method and system for detecting charge-to-mass ratio of particles in a fluidized bed

Abstract

This invention discloses a method and system for detecting the particle charge-to-mass ratio in a fluidized bed. By installing an electrostatic sensor on the reactor to acquire the electrostatic potential signal generated by particle motion, and through a series of data analyses, the accurate measurement of the particle charge-to-mass ratio within the reactor is achieved. The detection method and system proposed in this invention are simple, safe, and environmentally friendly, suitable for online monitoring in industrial production processes, and beneficial for ensuring the stable operation of industrial reactors. Compared with existing particle charge-to-mass ratio detection technologies, it is more sensitive, accurate, and has a wider range of applications.

Description

Technical Field

[0001] This invention relates to a method and system for detecting electrostatic parameters in a fluidized bed, and more particularly to a method and system for detecting the particle charge-to-mass ratio in a fluidized bed. Background Technology

[0002] Static electricity hazards are widespread in chemical production processes. Taking the fluidized bed production process of polyolefins as an example, polyolefin particles have poor water absorption, dry surfaces, and high resistivity. Therefore, static electricity is easily generated by friction between particles and between particles and equipment walls. Furthermore, due to the good insulation properties of polyolefin particles, static electricity is difficult to dissipate, inducing particle agglomeration. Once the agglomerates reach a certain size, it can lead to production shutdown and significant economic losses. Real-time online monitoring of the particle charge level within the reactor, and timely adjustment when the particle charge level is high, helps ensure the stable operation of the industrial production process.

[0003] Currently, commonly used methods for detecting electrostatic charge levels in fluidized beds include the Faraday cylinder method and the electrostatic probe method. The Faraday cylinder method directly obtains the intrinsic parameter representing the average charge level of particles—the average charge-to-mass ratio (AMR) (Powder Technology, 2013, 235:368-375). The AMR measured by the Faraday cylinder is the most important parameter for determining the particle charge level. However, it is an offline detection method, which suffers from problems such as long single detection time and charge dissipation caused by particle sampling, making it difficult to apply to industrial processes. Compared to the Faraday cylinder method, the electrostatic probe method can measure the charge level of particles in a fluidized bed online and output induced charge signals, electrostatic current signals, or electrostatic potential signals, and calculate the AMR of particles using a model. However, most existing models lack clear physical meaning (Powder Technology. 2016, 290:11-20), resulting in poor model universality and limited applicability.

[0004] Therefore, a method and system for detecting the particle charge-to-mass ratio in a fluidized bed has been developed, which is simple and stable in structure, convenient in operation, and has a wide range of applications, and has significant industrial application value. This invention utilizes an electrostatic sensor to collect electrostatic potential signals within the reactor, and combines signal mechanism analysis and data modeling to establish a method and system for detecting the particle charge-to-mass ratio in a fluidized bed. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for detecting the particle charge-to-mass ratio in a fluidized bed. This involves acquiring and analyzing electrostatic signals generated by particle movement within the reactor using an electrostatic sensor, and achieving online detection of the particle charge-to-mass ratio based on a mechanistic model relating the particle charge-to-mass ratio to the electrostatic signal. This invention is achieved through the following technical solutions.

[0006] A method for detecting the particle charge-to-mass ratio in a fluidized bed includes the following steps:

[0007] (1) At least one electrostatic sensor is installed on the outer wall of the fluidized bed reactor to be tested to receive the electrostatic potential signal generated by the movement of particles;

[0008] (2) The bed porosity in the reactor is obtained by measuring the pressure sensor.

[0009] (3) The collected electrostatic potential signal is preprocessed and noise is reduced, and its mean value is calculated;

[0010] (4) Calculate the particle charge-to-mass ratio in the system to be tested according to formula (1);

[0011]

[0012] In the formula, q m U represents the particle charge-to-mass ratio under the test conditions. c ε is the average electrostatic potential obtained from the electrostatic sensor. s a1 to a6 are model parameters, where a1 represents the bed porosity.

[0013] According to a preferred embodiment of the present invention, the calculation formula for the bed porosity obtained from the pressure sensor measurement in step (2) is as follows:

[0014]

[0015] In the formula, ρ s denoted as the true density of the particles, ΔP as the pressure difference between two points with a height difference of h in the fluidized bed, measured using a pressure sensor, and g as the acceleration due to gravity.

[0016] According to a preferred embodiment of the present invention, the model parameters a1 to a6 in step (4) can be obtained through electrification experiments on a laboratory-scale fluidized bed. The specific steps are as follows:

[0017] 1) Add an appropriate amount of particles to a laboratory-scale fluidized bed;

[0018] 2) The particles are fluidized using dry gas, causing them to move and become charged within the fluidized bed;

[0019] 3) Measure the electrostatic potential signal during fluidization using an electrostatic probe, measure the particle charge-to-mass ratio using a Faraday cylinder, and measure the bed porosity using a pressure sensor;

[0020] 4) Change the fluidization conditions to obtain the electrostatic potential signal, particle charge-to-mass ratio and bed porosity under different fluidization states, and then use Equation (1) to regress the above detection variables to obtain the model parameters a1 to a6.

[0021] The detection device of the present invention includes at least one invasive electrostatic sensor capable of obtaining contact electrostatic potential and a signal processing device. The invasive electrostatic sensor includes an electrostatic probe, an electrostatic transmission device, and a signal acquisition device. The diameter of the electrostatic probe is in the range of 1-5 cm, preferably in the range of 2-3 cm. The electrostatic transmission device includes a conductive system and a protection system for preventing electrostatic leakage. The conductive system consists of a stainless steel rod, and the protection system consists of a highly insulating protective tube, which can be made of insulating ceramic or polytetrafluoroethylene. The signal acquisition system is used to acquire the electrostatic potential signal and output a standard current signal.

[0022] An electrostatic sensor is installed on the outer wall of the fluidized bed reactor. The sensor probe extends into the fluidized bed to a depth of approximately 1-10 cm, preferably 2-6 cm. The electrostatic sensor is connected to a signal processing device to analyze the collected signals.

[0023] The signal processing device includes:

[0024] The feature extraction module denoises the electrostatic signal based on the changing trend of the received electrostatic potential signal and calculates the mean value of the denoised electrostatic potential signal.

[0025] The charge-to-mass ratio calculation module has built-in model parameters for different types or operating states of fluidized beds (dense phase fluidized bed, dilute phase fluidized bed, pneumatic conveying pipeline). It selects the appropriate model parameters according to the type of fluidized bed or operating state, and combines the average value of the electrostatic potential signal obtained by detection and the bed porosity obtained by external methods to obtain the particle charge-to-mass ratio of the system to be tested by equation (1).

[0026] The bed porosity can be obtained from the data measured by the pressure sensor using equation (2), or it can be obtained by other methods available in the art.

[0027] The present invention has the following advantages: the detection method and system of the present invention have a simple structure and stable operation, and are suitable for online detection in industrial production processes; the particle charge-to-mass ratio calculation model adopted is a mechanistic model, which has strong generalization performance and good universality. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the detection device of the present invention;

[0029] Figure 2 This is a comparison chart of the actual and calculated values ​​of the particle charge-to-mass ratio. Detailed Implementation

[0030] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0031] like Figure 1 As shown, the detection device in this embodiment includes a fluidized bed reactor 1, an electrostatic sensor 2, and a signal processing device 3. The electrostatic sensor 2 is mounted on the fluidized bed reactor 1, and the electrostatic sensor 2 and the signal processing device 3 are connected to analyze the collected signals. The electrostatic sensor includes an electrostatic probe 2-a, an electrostatic transmission device 2-b, and a signal acquisition device 2-c.

[0032] The signal processing device includes a feature extraction module and a charge-to-mass ratio calculation module.

[0033] The feature extraction module selects an appropriate denoising algorithm to denoise the electrostatic potential signal and calculates the mean value of the denoised electrostatic potential signal. The charge-to-mass ratio calculation module contains pre-stored charge-to-mass ratio calculation models applicable to various scenarios, used to predict the charge-to-mass ratio of the system under test.

[0034] During testing, at least one electrostatic sensor is first installed on the outer wall of the fluidized bed reactor to receive the electrostatic potential signal generated by particle movement; the bed porosity inside the reactor is obtained by measuring the pressure sensor.

[0035] Then, the collected electrostatic potential signal is preprocessed to reduce noise, and its mean is calculated.

[0036] Finally, the particle charge-to-mass ratio in the test system is calculated according to equation (1);

[0037]

[0038] In the formula, q m U represents the particle charge-to-mass ratio under the test conditions. c ε is the average electrostatic potential obtained from the electrostatic sensor. s a1 to a6 are model parameters, where a1 represents the bed porosity.

[0039] In step (3), the preprocessing and noise reduction algorithm for electrostatic signals is selected from one or more of the following: smoothing, differentiation, multivariate scattering correction, orthogonal signal correction, Fourier transform, wavelet transform, and net analysis signal.

[0040] The collected electrostatic data may contain unwanted noise. Therefore, noise removal methods are crucial and necessary. In the preprocessing methods of the detection method of this invention, smoothing can improve the signal-to-noise ratio of the analyzed signal; the most commonly used methods are moving average smoothing and Savizky-Golay polynomial smoothing. Differentiation can eliminate baseline drift, enhance spectral band characteristics, and overcome spectral band overlap; it is a commonly used spectral preprocessing method. First-order differentiation can remove drifts independent of the same wavelength, while second-order differentiation can extract drifts linearly related to the same wavelength. Fourier transform can realize the conversion between spectral domain functions and time domain functions; its essence is to decompose the original sound spectrum into a superposition of many sine waves of different frequencies. It can be used for smoothing and denoising the sound spectrum, data compression, and information extraction. Wavelet transform can decompose the signal into multiple scale components according to different frequencies and apply corresponding sampling step sizes to different scale components, thereby focusing on any part of the signal. The basic idea of ​​the net analysis signal algorithm is basically the same as that of orthogonal signal correction, both removing information irrelevant to the measured component from the sound spectrum array through orthogonal projection.

[0041] To ensure the accuracy and reliability of the model parameters as much as possible, the laboratory-scale fluidized bed material, geometry, fluidized particle material, and particle size distribution are kept similar to those of the industrial reactor, specifically as follows: The preferred material for the laboratory-scale fluidized bed is stainless steel; for the laboratory-scale bubbling fluidized bed, its inner diameter is not less than 300 mm, and the static bed height is not less than twice the inner diameter; for the laboratory-scale circulating fluidized bed, its geometry is the same as that of the industrial fluidized bed, with only dimensional differences, and the inner diameter is not less than 150 mm. Simultaneously, particles with similar particle size distribution and material to those in the industrial fluidized bed are used to conduct electrostatic experiments.

[0042] The charge-to-mass ratio calculation module of this invention pre-stores charge-to-mass ratio calculation models applicable to various scenarios. These charge-to-mass ratio calculation models can be obtained through electrification experiments in a laboratory-scale fluidized bed. One optional implementation method for constructing the model is as follows:

[0043] (1) Add an appropriate amount of particles (preferably the same type and size as the particles in the industrial system to be tested) to a laboratory-scale fluidized bed;

[0044] (2) Use dry gas to fluidize the particles, so that the particles move and become charged in the fluidized bed;

[0045] (3) Measure the electrostatic potential signal during the fluidization process using an electrostatic probe, measure the particle charge-to-mass ratio using a Faraday cylinder, and measure the bed porosity using a pressure sensor;

[0046] (4) Change the fluidization conditions to obtain the electrostatic potential signal, particle charge-to-mass ratio and bed porosity under different fluidization states, and then use Equation (1) to regress the above detection variables to obtain model parameters a1 to a6, and then construct charge-to-mass ratio calculation models for various scenarios.

[0047] In this embodiment, the particle charge-to-mass ratio is detected as follows:

[0048] Using the present invention Figure 1 The system shown involves adding an appropriate amount of polypropylene particles (average particle size approximately 2.38 mm) to a circulating fluidized bed (comprising a rising section and a falling section: the rising section is 2.0 m high with an inner diameter of 0.09 m; the falling section is 1.3 m high with an inner diameter of 0.06 m). Fluidization is performed using air with a relative humidity of less than 10% (fluidizing gas velocity range of 5.5 m / s-7.5 m / s), and the solid circulation rate is controlled to be approximately 11.0 kg / (m³). 2 After the system reaches stability, an electrostatic potential signal is acquired using an electrostatic sensor, and a bed pressure signal is acquired using a pressure sensor (for calculating the bed porosity). Samples are taken at the same locations, and the true charge-to-mass ratio of the particles in the fluidized bed is obtained using a Faraday cylinder. Subsequently, the electrostatic potential signal and the porosity obtained based on the pressure signal are substituted into the prediction model of this invention for prediction, and the results are as follows. Figure 2 As shown in the figure. Experimental results show that the detection method provided by this invention can be used for online detection of particle charge-to-mass ratio in fluidized beds, and has high accuracy, with an average prediction error of only 23.2%, meeting the online detection requirements of industrial production processes.

[0049] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for detecting the particle charge-to-mass ratio in a fluidized bed, characterized in that, Includes the following steps: (1) At least one electrostatic sensor is installed on the outer wall of the fluidized bed reactor to be tested to receive the electrostatic potential signal generated by the movement of particles; (2) The bed porosity in the reactor is obtained by measuring the pressure sensor; (3) The collected electrostatic potential signal is preprocessed and denoised, and its mean value is calculated; (4) Calculate the particle charge-to-mass ratio in the system to be tested according to formula (1); （1） In the formula, q m U represents the particle charge-to-mass ratio under the test conditions. c ε is the average electrostatic potential obtained from the electrostatic sensor. s A represents the bed porosity, and a1 to a6 are model parameters.

2. The method for detecting the particle charge-to-mass ratio in a fluidized bed according to claim 1, characterized in that: The formula for calculating the bed porosity obtained from the pressure sensor measurement in step (2) is as follows: （2） In the formula, ρ s denoted as the true density of the particles, ΔP as the pressure difference between two points with a height difference of h in the fluidized bed, measured using a pressure sensor, and g as the acceleration due to gravity.

3. The method for detecting the particle charge-to-mass ratio in a fluidized bed according to claim 1, characterized in that: The model parameters a1~a6 in step (4) were obtained through electrification experiments on a laboratory-scale fluidized bed. The specific steps are as follows: 1) Add an appropriate amount of particles to a laboratory-scale fluidized bed; 2) The particles are fluidized using dry gas, causing them to move and become charged within the fluidized bed; 3) Measure the electrostatic potential signal during fluidization using an electrostatic probe, measure the particle charge-to-mass ratio using a Faraday cylinder, and measure the bed porosity using a pressure sensor; 4) Change the fluidization conditions to obtain the electrostatic potential signal, particle charge-to-mass ratio and bed porosity under different fluidization states, and then use Equation (1) to regress the above detection variables to obtain the model parameters a1~a6.

4. The method for detecting the particle charge-to-mass ratio in a fluidized bed according to claim 3, characterized in that: The preferred material for the laboratory-scale fluidized bed is stainless steel; for the laboratory-scale bubbling fluidized bed, its inner diameter is not less than 300 mm, and the static bed height is not less than twice the inner diameter; for the laboratory-scale circulating fluidized bed, its geometry is the same as that of the industrial fluidized bed, with only dimensional differences, and its inner diameter is not less than 150 mm.

5. The method for detecting the particle charge-to-mass ratio in a fluidized bed according to claim 3, characterized in that: In the laboratory-scale fluidized bed electrification experiment, particles with similar particle size distribution and the same material as those in the industrial fluidized bed were used to conduct the electrification experiment.

6. A device for detecting the particle charge-to-mass ratio in a fluidized bed implementing the method of claim 1, characterized in that, The detection device includes at least one invasive electrostatic sensor capable of obtaining contact electrostatic potential and a signal processing device; the invasive electrostatic sensor includes an electrostatic probe, an electrostatic transmission device, and a signal acquisition device; the diameter of the electrostatic probe is in the range of 1-5 cm; the electrostatic transmission device includes a conductive system and a protection system for preventing electrostatic leakage, the conductive system is composed of a stainless steel rod, and the protection system is composed of a highly insulating protective tube, the protective tube being made of insulating ceramic or polytetrafluoroethylene; the signal acquisition system is used to acquire electrostatic potential signals and output standard current signals.

7. The device for detecting the particle charge-to-mass ratio in a fluidized bed according to claim 6, characterized in that, The electrostatic sensor is installed on the outer wall of the fluidized bed reactor. The electrostatic probe extends into the fluidized bed to a depth of 1-10 cm. The electrostatic sensor is connected to a signal processing device to analyze the collected signals. The signal processing device includes: The feature extraction module denoises the electrostatic signal based on the changing trend of the received electrostatic potential signal and calculates the mean value of the denoised electrostatic potential signal. The charge-to-mass ratio calculation module has built-in model parameters for different types or operating states of fluidized beds. The appropriate model parameters are selected according to the type or operating state of the fluidized bed. The average value of the electrostatic potential signal obtained by detection and the bed porosity obtained by external methods are combined to obtain the particle charge-to-mass ratio of the system to be tested by equation (1).

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