A method and device for measuring equivalent electrical parameters of an ion tube

Abstract

The present invention discloses a method and device for measuring equivalent electrical parameters of an ion tube, comprising the following steps: S1. Training a neural network calculation model using the voltage and current signals on the low-voltage side and the voltage signal on the high-voltage side of an ion tube transformer; S2. Obtaining the voltage and current signals on the low-voltage side of the ion tube transformer, and calculating the voltage signal on the high-voltage side based on the neural network model; S3. Calculating the equivalent electrical parameters of the ion tube from the calculated voltage signal on the high-voltage side. It has the advantages of being able to measure the equivalent electrical parameters of the ion tube without the need for a high-voltage probe and an externally connected measuring capacitor, facilitating the engineering of ion tube parameter detection, and being safe and efficient.

Description

Technical Field

[0001] The present invention relates to a method and device for measuring equivalent electrical parameters of an ion tube. Background Art

[0002] An ion tube is a dielectric barrier discharge device widely used in the field of air quality control. The operating state and parameters of the ion tube are key factors affecting the efficiency of air quality control. During the use of the ion tube, since the object to be treated is the air to be treated containing dust and fine particles, under the high-voltage environment in which the ion tube works, the aggregation of dust and fine particles will block the discharge channel of the ion tube, which will cause the discharge capacity of the continuously working ion tube to gradually decline, and ultimately affect the efficiency of air quality control. Therefore, how to monitor the working state of the ion tube in real time and accurately is the key point and difficulty in the use and maintenance of the ion tube.

[0003] As a typical dielectric barrier discharge device, the working state of the ion tube can be divided into a non-discharge state and a discharge state. The equivalent circuit of the non-discharge state is the series connection of a dielectric capacitor and an air-gap capacitor, and the equivalent circuit of the discharge state is the series connection of a dielectric capacitor and a Zener diode in the breakdown state. Therefore, the working state of the ion tube can be characterized by the parameters of the equivalent circuit of the ion tube, that is, by obtaining the parameters of the equivalent circuit of the ion tube to analyze the working state of the ion tube. The equivalent electrical parameters of the ion tube include a dielectric capacitor and an air-gap capacitor.

[0004] The existing method for measuring the equivalent electrical parameters of a dielectric barrier discharge device needs to set a measuring capacitor and a high-voltage probe in the working circuit of the discharge device, and use an oscilloscope to obtain the Lissajous figure of the device. This method is only applicable to the laboratory environment, cannot perform on-line measurement of the equivalent electrical parameters of the ion tube in actual work, and has problems such as high cost, need to contact high voltage, and inability to realize the automation of parameter measurement. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a method and device for measuring equivalent electrical parameters of an ion tube with low cost, safety and reliability, and easy to realize engineering application of parameter measurement.

[0006] The technical solution of the present invention to solve the above problems is: a method and device for measuring equivalent electrical parameters of an ion tube, including the following steps:

[0007] S1. Train a neural network calculation model using the voltage and current signals on the low-voltage side of the ion tube transformer and the voltage signal on the high-voltage side;

[0008] S2. Obtain the voltage and current signals on the low-voltage side of the ion tube transformer, and calculate the voltage signal on the high-voltage side based on the neural network model;

[0009] S3. Calculate the equivalent electrical parameters of the ion tube from the calculated high-voltage side voltage signal.

[0010] The effect of the present invention is as follows: Regarding the problem of measuring the equivalent electrical parameters of the ion tube, compared with the traditional method, the present invention provides a measurement method and device with low cost, safety and reliability, and easy to realize the engineering application of parameter measurement. The advantages of this parameter measurement method are as follows: During the actual measurement process, there is no need to change the working circuit of the ion tube, that is, there is no need to connect a measurement capacitor to the working circuit of the ion tube; there is no need to measure the high-voltage signal, that is, there is no need for a high-voltage probe or to connect a sampling capacitor in parallel to the working circuit of the ion tube; there is no need for a multi-channel oscilloscope, that is, there is no need to use an oscilloscope to draw a Lissajous figure and then calculate the slopes of both sides of the parallelogram by the method of plotting points on the figure; it is convenient for the engineering of parameter measurement. In the measurement device based on the embedded system constructed, the equivalent electrical parameters can be directly calculated based on the calculated data set. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a flowchart of the present invention

[0012] Figure 2 It is a circuit diagram for measuring the characteristics of the ion tube in the present invention

[0013] Figure 3 It is a waveform diagram of the data set for training the neural network in the present invention

[0014] Figure 4 It is a measurement scheme diagram of the present invention

[0015] Figure 5 It is a circuit diagram for measuring the equivalent electrical parameters of the ion tube in the present invention

[0016] Figure 6 It is a comparison diagram between the neural network calculated value and the actual measured value of the high-voltage side voltage signal in the present invention

[0017] Figure 7 It is a Lissajous figure of the ion tube drawn from the calculated value in the present invention

[0018] Figure 8 It is a schematic diagram of the fixed-point search strategy calculation in the present invention EMBODIMENT

[0019] The following further describes the present invention in detail with reference to the drawings and specific embodiments.

[0020] A method and device for measuring the equivalent electrical parameters of an ion tube according to the present invention, the flowchart of which is as Figure 1 shown, including the following steps:

[0021] S1. Train a neural network calculation model using the low-voltage side voltage and current signals and the high-voltage side voltage signal of the ion tube transformer;

[0022] S2. Obtain the voltage and current signals on the low-voltage side of the ion tube transformer, and calculate the voltage signal on the high-voltage side based on the neural network model;

[0023] S3. Calculate the equivalent electrical parameters of the ion tube from the calculated voltage signal on the high-voltage side.

[0024] 1. The specific process of step S1 includes:

[0025] S1.1. Construct an ion tube characteristic measurement circuit as shown in Figure 2 . This circuit includes a single-phase 220V AC power supply, an ion tube transformer, an ion tube, measurement capacitors (C M , C1, C2), a voltage sensor PT, a current sensor CT, and a 4-channel oscilloscope. The single-phase 220V AC power supply is connected to the low-voltage side of the ion tube transformer. The voltage sensor and the current sensor are respectively used to measure the voltage and current signals on the low-voltage side of the ion tube transformer. The ion tube is connected in series with the measurement capacitor C M and then connected to the high-voltage side of the ion tube transformer. The sampling capacitors C1 and C2 are connected in series and then connected to the high-voltage side of the ion tube transformer. The measurement capacitor C M is used to measure the charge during the operation of the ion tube. The sampling capacitors C1 and C2 are used to obtain the operating voltage of the ion tube, and based on the capacitance voltage division principle, a low-voltage signal available for oscilloscope measurement is obtained. In the present invention, the measurement capacitor C M has a value of 0.47uF, the capacitor C1 is 47pF, and the capacitor C2 is 47000pF. The 4-channel oscilloscope is used to record the low-voltage side voltage U and current I, as well as the high-voltage side total voltage V W and the measurement voltage V M ;

[0026] S1.2. Construct a neural network calculation model. The constructed neural network adopts a three-layer structure, where the input layer consists of 2 neurons, the hidden layer includes 5 neurons, and the output layer has 2 neurons. The neurons in the input layer correspond to the voltage and current signals on the low-voltage side of the ion tube transformer, and the neurons in the output layer correspond to the high-voltage side total voltage and measurement voltage signals;

[0027] S1.3. Train the neural network calculation model. Use the recorded low-voltage side voltage and current signals and high-voltage side total voltage and measurement voltage signals as the sample data for training the neural network. The sample data contains 4 groups of 1000 points, as shown in Figure 3 . Among them, Figure 3 (1) is the low-voltage side voltage signal U, Figure 3 (2) is the low-voltage side current signal I, Figure 3 (3) is the high-voltage side total voltage signal V W , Figure 3 (4) is the high-voltage side measurement voltage signal V M; To improve the efficiency of neural network training, the low-voltage side current signal is first integrated and then input into the neural network; finally, the neural network model is trained using the error backpropagation algorithm to obtain a trained network model.

[0028] 2. The specific process of step S2 includes:

[0029] The measurement scheme of the present invention is as Figure 4 shown. A voltage sensor and a current sensor are used to measure the voltage and current signals on the low-voltage side of the ion tube transformer respectively, and the current signal is integrated to obtain the electric charge; the low-voltage side voltage signal and the electric charge are input into the trained neural network model, and the total voltage and the measured voltage on the high-voltage side are calculated by the network model. Finally, a Lissajous figure is drawn and the equivalent electrical parameters are calculated.

[0030] S2.1. Construct an ion tube equivalent electrical parameter measurement circuit as Figure 5 shown. The circuit includes a single-phase 220V AC power supply, an ion tube transformer, an ion tube, a voltage sensor, a current sensor, and a parameter measurement device; the single-phase 220V AC power supply is connected to the low-voltage side of the ion tube transformer, and the voltage sensor and the current sensor are respectively used to measure the voltage and current signals on the low-voltage side of the ion tube transformer; the ion tube is connected to the high-voltage side of the ion tube transformer; the parameter measurement device obtains the voltage U and current I on the low-voltage side of the ion tube transformer sampled by the voltage and current sensors, the number of sampling points is 1000 points, and the sampling duration is 40ms.

[0031] S2.2. Calculate the high-voltage side voltage signal based on the neural network model. Store the trained neural network model in the parameter measurement device, and send the obtained low-voltage side voltage and current signals into the neural network. The corresponding high-voltage side voltage signal is calculated by the neural network; the calculation results are as Figure 6 shown, Figure 6 (1) is a comparison chart of the calculated value and the measured value of the total voltage on the high-voltage side, Figure 6 (2) is a comparison chart of the calculated value and the measured value of the measured voltage on the high-voltage side. It can be seen from the figure that the high-voltage side voltage signal calculated by the constructed neural network has a small calculation error.

[0032] 3. The specific process of step S3 is:

[0033] S3.1. Draw a Lissajous figure according to the calculated high-voltage side voltage signal dataset. As Figure 7 shown, it is a typical DBD discharge characteristic figure; combined with Figure 7 a fixed-point search strategy is used to calculate the slope of the parallelogram of the Lissajous figure. Its calculation principle is as Figure 8 shown. The process is as follows: ① First, search for the data points in the dataset where the absolute value of the measured voltage is less than 0.5, and record the serial numbers of these data points in the dataset. As Figure 8Points A and B as shown; ② Divide the serial numbers of the searched data points into two categories. The total voltage corresponding to the serial numbers of the first category of data points is positive, such as point B in Figure 8 ; the total voltage corresponding to the serial numbers of the second category of data points is negative, such as point A in Figure 8 ; ③ Taking each serial number of the first category of data points as the center, take the serial numbers with an interval of 15 before and after it, and calculate the slope of the corresponding line segment based on the total voltage and the measured voltage corresponding to the serial number. Finally, calculate the average value of the slopes of the line segments corresponding to all the serial numbers of the first category of data points, denoted as k1. In Figure 8 , the line segment corresponding to the serial number of point B is CD, and its calculated slope is k11; ④ Taking each data point of the second category as the reference, find the serial numbers of the data points in the dataset whose absolute value of the deviation from the total voltage corresponding to the data points of the second category is less than 0.3 and the corresponding measured voltage is less than -10, such as point E in Figure 8 . Take the serial numbers with an interval of 10 before and after it, and calculate the slope of the corresponding line segment based on the total voltage and the measured voltage corresponding to the serial number. Finally, calculate the average value of the slopes of the line segments corresponding to all the serial numbers of the second category of data points, denoted as k2. In Figure 8 , first find the point E corresponding to the serial number of point A, and then obtain the line segment corresponding to point E as FG, and calculate its slope as k21.

[0034] S3.2. Calculate the equivalent electrical parameters of the ion tube according to the calculated slope. The parameters are: dielectric capacitance C d and air-gap capacitance C g ; The calculation formula is:

[0035] C d = (k2 × C M ) / 1000

[0036] Cg = (k1 × k2 × C M ) / [(k1 - k2) × 1000]

[0037] 4. The ion tube equivalent electrical parameter measuring device includes a sensor module, an AD module, an embedded processor, a parameter display screen, and a serial port module; among them, the serial port is used to load the neural network model, the voltage and current sensors are used to obtain the voltage and current signals on the low-voltage side of the ion tube transformer, the AD module is used to convert the sampled low-voltage side voltage and current signals into digital signals, the embedded processor is used for current signal integration processing, neural network calculation, Lissajous figure slope calculation, and ion tube equivalent electrical parameter calculation, and the display screen is used to display the Lissajous figure and the ion tube equivalent electrical parameters.

Claims

1. A method for measuring equivalent electrical parameters of an ion tube, comprising the following steps: S1. Training a neural network calculation model using the voltage and current signals on the low-voltage side and the voltage signal on the high-voltage side of the ion tube transformer; S2. Obtaining the voltage and current signals on the low-voltage side of the ion tube transformer and calculating the voltage signal on the high-voltage side based on the neural network model; S3. Calculating the equivalent electrical parameters of the ion tube from the calculated voltage signal on the high-voltage side; S3.

1. Drawing a Lissajous figure according to the calculated high-voltage side voltage signal dataset and calculating the slope of the parallelogram in the Lissajous figure using a fixed-point search strategy; S3.

2. Calculate the equivalent electrical parameters of the ion tube according to the calculated slope, and the parameters are: dielectric capacitance C d and air-gap capacitance C g , and the calculation formula is: C d = (k2 × C M ) / 1000 Cg = (k1×k2×C M ) / [( k1-k2)×1000] Among them, k2 is the average value of the slopes of the line segments corresponding to all the serial numbers of the second type of data points; k1 is the average value of the slopes of the line segments corresponding to all the serial numbers of the first type of data points; C M is the measured capacitance, with a value of 0.47 uF.

2. The method for measuring the equivalent electrical parameters of an ion tube according to claim 1, wherein The specific steps of the said step S1 include: S1.

1. Constructing an ion tube characteristic measurement circuit, which includes a single-phase 220V AC power supply, an ion tube transformer, an ion tube, a measurement capacitor, a voltage sensor, a current sensor, and a 4-channel oscilloscope; the single-phase 220V AC power supply is connected to the low-voltage side of the ion tube transformer, and the voltage sensor and the current sensor are respectively used to measure the voltage and current signals on the low-voltage side of the ion tube transformer; the ion tube and the measurement capacitor are connected to the high-voltage side of the ion tube transformer, and the measurement capacitor is used to measure the working voltage and charge of the ion tube; the 4-channel oscilloscope is used to record the voltage and current signals on the low-voltage side and the voltage signal on the high-voltage side; S1.

2. Constructing a neural network calculation model, the constructed neural network adopts a three-layer structure, where the input layer consists of 2 neurons, the hidden layer includes 5 neurons, and the output layer is 2 neurons; the neurons in the input layer correspond to the voltage and current signals on the low-voltage side of the ion tube transformer, and the neurons in the output layer correspond to the voltage signal on the high-voltage side; S1.

3. Training the neural network calculation model, using the recorded voltage and current signals on the low-voltage side and the voltage signal on the high-voltage side as the sample data for training the neural network; first performing integral processing on the low-voltage side current signal and then inputting it into the neural network; training the neural network model using the error backpropagation algorithm to obtain a trained network model.

3. The method for measuring equivalent electrical parameters of an ion tube according to claim 1, characterized in that The specific steps of the said step S2 include: S2.

1. Constructing an ion tube equivalent electrical parameter measurement circuit, which includes a single-phase 220V AC power supply, an ion tube transformer, an ion tube, a voltage sensor, a current sensor, and a parameter measurement device; the single-phase 220V AC power supply is connected to the low-voltage side of the ion tube transformer, and the voltage sensor and the current sensor are respectively used to measure the voltage and current signals on the low-voltage side of the ion tube transformer; the ion tube is connected to the high-voltage side of the ion tube transformer; the parameter measurement device obtains the voltage and current signals on the low-voltage side of the ion tube transformer sampled by the voltage and current sensors; S2.

2. Calculating the voltage signal on the high-voltage side based on the neural network model, storing the trained neural network model in the parameter measurement device, and sending the obtained voltage and current signals on the low-voltage side into the neural network, and calculating the corresponding voltage signal on the high-voltage side by the neural network.

4. An ion tube equivalent electrical parameter measuring device for implementing the method according to any one of claims 1-3, characterized in that The device includes a sensor module, an AD module, an embedded processor, a parameter display screen, and a serial port module; among them, the serial port is used to load a neural network model, voltage and current sensors are used to obtain the voltage and current signals on the low-voltage side of the ion tube transformer, the AD module is used to convert the sampled low-voltage side voltage and current signals into digital signals, the embedded processor is used for current signal integration processing, neural network calculation, Lissajous figure slope calculation, and ion tube equivalent electrical parameter calculation, and the display screen is used to display the Lissajous figure and the ion tube equivalent electrical parameters.

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