Array electrostatic sensor, self-adaptive airflow velocity measuring system and self-adaptive airflow velocity measuring method

Abstract

The invention discloses an array electrostatic sensor and a self-adaptive airflow velocity measuring system and method, and the array electrostatic sensor comprises a discharge electrode which generates ions as a tracer; the linear array measuring electrode is composed of a plurality of measuring electrodes which are arranged at intervals in the airflow flowing direction; and the discharge electrode is positioned at the upstream of the linear array measuring electrode. The adaptive airflow velocity measurement system includes: an array electrostatic sensor; the high-voltage ion generation source is connected with the discharge electrode and is used for ionizing gas flowing through the high-voltage ion generation source and generating ions as tracers; the multi-channel signal processing and calculating module is used for acquiring an electrostatic signal of the linear array measuring electrode measured by the array electrostatic sensor; and obtaining the airflow velocity according to the obtained electrostatic signal. According to the invention, the problems of ion attenuation characteristic change and measurement position mismatch caused by flow velocity change are effectively overcome, and the measurement reliability and high precision in a wide flow velocity range are ensured.

Description

Technical Field

[0001] This invention relates to the field of fluid measurement, specifically a system and method for measuring the velocity of low-concentration or dust-laden airflow, which achieves accurate measurement of airflow velocity based on a flat-panel array electrostatic sensor and an adaptive channel selection algorithm. Background Technology

[0002] Gas-solid two-phase flow is widely present in industries such as energy, chemical, metallurgy, and environmental protection, including pulverized coal conveying in coal-fired boilers, catalyst circulation in petrochemical industries, and flue gas emissions from thermal power plants. Real-time and accurate measurement of parameters such as velocity and concentration of gas-solid two-phase flow in these pipelines is crucial for optimizing process control, improving combustion efficiency, and ensuring safe production. Currently, various velocity measurement methods exist, such as the Pitot tube method, hot-wire anemometer method, and optical measurement methods (e.g., LDV, PIV). However, contact methods such as Pitot tubes and hot-wire anemometers are prone to clogging and wear in dusty and high-temperature environments; while optical methods, although highly accurate, are expensive, complex, and susceptible to dust contamination leading to light path obstruction, making long-term stable operation in harsh industrial environments difficult. In contrast, electrostatic measurement methods (electrostatic sensors) have been widely used in the parameter measurement of gas-solid two-phase flow due to their advantages of simple structure, low cost, durability, non-invasive measurement, and fast response speed.

[0003] However, traditional electrostatic sensors rely heavily on the natural collisions and triboelectric charging of solid particles in fluids. In many critical industrial scenarios, such as when the particulate concentration is extremely low (e.g., secondary air) or when the flue gas is hot (with very low particle charge), electrostatic sensors cannot detect sufficient charge signals, leading to a significant decrease in measurement accuracy, or even rendering them unusable.

[0004] To overcome this limitation, an important technical approach is to combine electrostatic sensors with active gas ionization technology, known as "ion tracer method." The basic principle is that a high-voltage ionization device upstream of the sensing electrode ionizes the air through corona discharge, actively generating a large number of ions. These ions act as tracers, moving with the airflow and forming a "charged fluid." When two downstream sensing electrodes (usually in a ring shape) spaced apart along the flow direction detect this ion signal, two signals with time delays are generated. By calculating the cross-correlation function of these two signals, the transit time corresponding to the peak value is found. Combined with the known electrode spacing, the airflow velocity can then be calculated.

[0005] However, this "ion tracer + fixed dual electrode" technology still faces unresolved issues in practical industrial applications, especially in the measurement of dusty gases. On one hand, when traditional ring-shaped sensors are horizontally installed in large-space flow fields or horizontal pipes, dust particles easily accumulate at the bottom of the pipe and on the sensor due to gravity. This dust accumulation contaminates the electrode surface, causing distortion of the induced electric field, severely interfering with signal accuracy, and even leading to measurement failure. On the other hand, as the ion cloud flows downstream, it undergoes "comprehensive attenuation" due to neutralization and diffusion effects. This means that if the measurement position (i.e., the measuring electrode) is too close to the ionization source, the ions are not sufficiently mixed, resulting in poor signal correlation; if it is too far from the ionization source, the ion concentration is too low, and the signal becomes very weak. More importantly, this "optimal measurement position" dynamically drifts with changes in airflow velocity. Traditional dual-electrode sensors have a fixed spacing, which cannot guarantee measurement at the optimal position under all flow rate conditions. When changes in flow velocity cause measurement position mismatch, the cross-correlation coefficient will significantly decrease, leading to decreased measurement accuracy or failure.

[0006] Therefore, there is an urgent need for a new type of velocity measurement system that can avoid physical interference from dust accumulation and adapt to signal attenuation characteristics under different flow velocities, thereby improving the reliability and accuracy of the measurement. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to propose an array electrostatic sensor that can adapt to the signal attenuation characteristics under different flow velocities, thereby improving the reliability and accuracy of measurement, an adaptive airflow velocity measurement system based on the array electrostatic sensor, and a measurement method.

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: This invention first provides an array electrostatic sensor, comprising: A discharge electrode is used to ionize the flowing gas to generate ions as tracers. A linear array measuring electrode, wherein the linear array measuring electrode is composed of a plurality of measuring electrodes spaced apart along the airflow direction; The discharge electrode is located upstream of the linear array measurement electrode.

[0009] The linear array of measuring electrodes comprises 6-8 measuring electrodes.

[0010] The measuring electrode is a flat plate electrode.

[0011] The discharge electrodes are two needle-tip discharge electrodes.

[0012] The present invention also provides an adaptive airflow velocity measurement system based on an array of electrostatic sensors, comprising: An array electrostatic sensor includes a discharge electrode and a linear array of measuring electrodes. The discharge electrode is located upstream of the linear array of measuring electrodes, and the linear array of measuring electrodes is composed of multiple measuring electrodes spaced apart along the airflow direction. A high-voltage ion generator, connected to the discharge electrode, is used to ionize the flowing gas and generate ions as tracers. as well as The multi-channel signal processing and calculation module acquires the electrostatic signals of the linear array measuring electrodes in the array electrostatic sensor; and obtains the airflow velocity based on the acquired electrostatic signals.

[0013] The method by which the multi-channel signal processing and calculation module obtains airflow velocity is as follows: Collect electrostatic signals from each electrode in the linear array measurement electrode; Calculate the cross-correlation function between adjacent electrodes; Find the peak value of the cross-correlation coefficient of the electrostatic signals between each electrode; Select the channel corresponding to the peak value of the cross-correlation coefficient and calculate the airflow velocity.

[0014] The formula for calculating the cross-correlation coefficient function is:

[0015] in, R i,i+1 ( m ) is the first i The first electrode and the second i +1 cross-correlation function between measuring electrodes; m For delay points, k The sampling point number; x i ( k ) is the first i Discrete-time series signal of each electrode x i+1 ( k ) is the first i Discrete-time sequence signal with +1 electrode; For the first i Discrete-time sequence signal of each electrode x i ( k The average value of ) For the first i Discrete-time sequence signal with +1 electrode x i+1 ( k The average value of ).

[0016] The steps for finding the peak values ​​of the cross-correlation coefficients of electrostatic signals between each electrode include: Search n-1 set of cross-correlation functions R i,i+1 ( m Each of them has its own maximum peak value; Record the number of delay points corresponding to the maximum peak value of each channel, where the first... j Maximum peak value of each channel R max ( j The corresponding delay points are denoted as m peak ( j ).

[0017] Select the channel corresponding to the peak value of the cross-correlation coefficient, and calculate the airflow velocity. The calculated airflow velocity is:

[0018] in, v The airflow velocity; f s The sampling frequency; L This represents the center-to-center distance between adjacent electrodes.

[0019] The present invention also provides an adaptive airflow velocity measurement method, comprising: The discharge ionizes the flowing gas, generating ions that serve as tracers. Electrostatic signals are acquired through the linear array measuring electrodes in the array electrostatic sensor. The airflow velocity is obtained based on the acquired electrostatic signal.

[0020] Compared with the prior art, the beneficial effects of the present invention are: 1. The sensor of this invention comprises a linear array of multiple sensing electrodes. During measurement, it is no longer limited to fixed electrode pairs, but rather adjacent electrodes form a pair, thus creating multiple electrode pairs. The cross-correlation coefficients of all adjacent electrode pairs are calculated and compared in real time. The electrode pair with the highest cross-correlation coefficient at the current moment (i.e., the best signal quality) is selected as the "optimal measurement channel," and the flow rate is calculated using the transit time corresponding to that channel. This effectively overcomes the problems of altered ion attenuation characteristics and measurement position mismatch caused by changes in flow rate, ensuring measurement reliability and high accuracy over a wide flow rate range.

[0021] 2. The measurement method of this invention is based on a sensor with a linear array of multiple sensing electrodes. It calculates and compares the cross-correlation coefficients of all adjacent electrode pairs in real time. The electrode pair with the highest cross-correlation coefficient (i.e., the best signal quality) at the current moment is selected as the "optimal measurement channel," and the flow velocity is calculated using the transit time corresponding to that channel. By dynamically tracking the "optimal measurement position" under different flow velocities through adaptive channel selection, reliability and high accuracy in measurements over a wide flow velocity range are ensured.

[0022] 3. The electrodes on the sensor used in this invention are flat plate electrodes. During use, they can be flexibly installed vertically (i.e., the sensing plane is parallel to the direction of gravity) or upside down (i.e., the sensing plane faces downwards, installed on the upper part of the flow field). This installation method utilizes gravity to allow dust to fall off naturally, fundamentally avoiding the problem of dust accumulation in the electrode sensing area, and greatly improving the stability and applicability of the system in harsh industrial environments.

[0023] 4. Flexible system structure and easy expansion: The array design of this invention has good scalability. It can be adjusted by increasing the number of electrodes or adjusting the electrode spacing according to different measurement needs (such as a wider flow rate range or higher accuracy requirements). L Flexible configuration without the need to redesign the entire sensor body. Attached Figure Description

[0024] Figure 1 This is a structural diagram of a planar electrode array electrostatic sensor. Figure 2 This is a schematic diagram of the airflow velocity measurement system; Figure 3 This is a block diagram of the multi-channel signal processing and computing module. Figure 4 This is a flowchart of an adaptive airflow velocity measurement method. Detailed Implementation

[0025] Example 1 This embodiment provides an array electrostatic sensor, such as Figure 1 As shown, it includes: Discharge electrode 1, which is used to ionize the flowing gas to generate ions as tracers; Linear array measurement electrode, which consists of multiple measurement electrodes 2 spaced apart along the airflow direction; Discharge electrode 1 is located upstream of the linear array measurement electrodes.

[0026] In one embodiment, the number of measuring electrodes 2 in the linear array measuring electrodes is 6-8.

[0027] In one embodiment, the measuring electrode 2 is a flat plate electrode.

[0028] In one embodiment, discharge electrode 1 consists of two needle-tip discharge electrodes. The two needle-tip discharge electrodes are installed upstream of the sensor and are respectively connected to the positive and negative terminals of a high-voltage power supply to ionize the flowing gas and generate ions as tracers.

[0029] In one embodiment, the array electrostatic sensor is a planar electrode array sensor, comprising an insulating substrate 3, an insulating cover 4, and a stainless steel shield 5. Both the insulating substrate 3 and the insulating cover 4 are made of high-temperature resistant and wear-resistant insulating ceramic. Multiple (6-8) stainless steel measuring electrodes 2 are arranged in a linear array on the insulating substrate 3 along the airflow direction. A fixed center-to-center distance is maintained between the measuring electrodes 2. L . Figure 1 The repeated arrangement of multiple measuring electrodes 2 is indicated by ellipses. The stainless steel shield 5 is used to enclose the sensor and ground it to shield against external electromagnetic interference.

[0030] Example 2 This embodiment provides an airflow velocity measurement system, such as Figure 2 As shown, the system includes a planar array electrostatic sensor 10 as provided in Embodiment 1, a high-voltage ion generator 20 located upstream of the sensor, and a multi-channel signal processing and computing module 30. The high-voltage ion generator consists of two needle-tip discharge electrodes and a high-voltage power supply.

[0031] As described above, the sensor of the present invention is designed as a flat plate structure, allowing it to be installed vertically (sensing plane parallel to the direction of gravity) or upside down (sensing plane facing downwards). This installation method makes it difficult for dust particles to accumulate on the electrode surface due to gravity, thereby solving the dust accumulation interference problem mentioned in the background art.

[0032] like Figure 3 As shown, the multi-channel signal processing and computing module is the core of this invention. Each sensing electrode in the sensor is connected to the module via an independent signal cable. The module includes: n A parallel signal conditioning channel independently performs I / V conversion, amplification, and filtering on the weak induced signals from each electrode. A multi-channel digital signal acquisition module synchronously acquires... n The signal from each channel is converted into a digital sequence. A signal processing and computing module (such as a DSP or host computer) is used to execute the subsequent adaptive algorithm.

[0033] The adaptive airflow velocity measurement method of the present invention is executed by the signal processing and calculation module, and the specific algorithm flow is as follows: Figure 4 As shown, it includes the following steps: Step S1: Signal Acquisition. The system synchronously acquires all signals. nThe signals from each sensing electrode are pre-filtered, amplified, and then acquired to obtain... n A set of discrete time series signals, denoted as x i ( k ),in i =1, 2, ..., n , k This is the sampling point number.

[0034] Step S2: Calculate the cross-correlation function between adjacent electrodes. The system calculates the cross-correlation function for all adjacent electrode pairs (i.e., ... ( x 1, x 2), ( x 2, x 3), ..., ( x n-1 , x n Cross-correlation calculations are performed. To accurately compare the correlation quality between different signal pairs, a normalized cross-correlation function is used here. R i,i+1 ( m Its discrete calculation formula is as follows: (1) in, m For delay points, and These are the average values ​​of the two signals, respectively. The range of this function is [-1, 1].

[0035] Step S3: Locate the peak value of the cross-correlation coefficient of the electrostatic signals in each channel. The signal processing calculation module iterates through the channels. m Search n -1 set of cross-correlation functions R i,i+1 ( m Each of the following is its maximum peak value. For the first... j For a channel, its maximum peak value is denoted as R max ( j The number of delay points corresponding to this peak value is denoted as . m peak ( j ).

[0036] Step S4: Adaptively select the optimal channel. The system compares all... n -1 maximum peak value R max ( j ) (in j =1 to n -1), and select the global maximum value among them.R global_max Corresponding channel s This is the optimal measurement channel.

[0037] (2) By comparing signal quality in real time, the measurement range with the best correlation during ion decay is automatically found, thus dynamically adapting to the drift of the optimal measurement position caused by changes in flow rate.

[0038] Step S5: Calculate the flow rate. The system uses the number of delay points corresponding to the optimal measurement channel. m peak ( s (As the final crossing time) τ 0. The sampling frequency of the digital signal acquisition module is... f s (Sampling period) T s = 1 / f s The center-to-center distance between adjacent electrodes is L Then the airflow speed v The calculation is as follows: (3) (4) Calculated speed v This is the final measurement result.

[0039] During measurement, a high-voltage ion generator first produces ions upstream of the sensor. As the ions flow sequentially through the array of sensing electrodes with the gas flow, each electrode senses an electrostatic signal.

[0040] all n The signals from each electrode are independently sent to the signal processing and calculation module (e.g., ...). Figure 3 Inside the module, n The signals first enter their respective signal conditioning channels, and then are synchronously sampled by the multi-channel digital signal acquisition module (step S1). Figure 3 ).

[0041] Signal processing calculation module execution Figure 4 The adaptive algorithm is shown. First (step S2), for all n -1 signal sequence of adjacent electrode pairs (i.e. ( x 1, x 2), ( x 2, x 3), ..., ( x n-1 , x nThe cross-correlation coefficient function (as shown in the formula in the technical solution) is called to perform the calculation.

[0042] Subsequently (step S3), the calculated n Find the maximum peak value of each of the -1 cross-correlation function results. R max ( i ) and the corresponding delay m peak ( i ).

[0043] Next (step S4), the computing unit compares this n -1 peak R max ( i The size of ). For example, at a certain low flow rate, it is possible that ( x 2, x 3) The correlation between them is the best ( R max (2) Maximum), the system will automatically select m peak (2) as transit time; while at another high flow rate, ion decay is accelerated, possibly ( x 4, x 5) The correlation between the two is the best. R max (4) Maximum), the system will automatically switch, select m peak (4) As the time of crossing.

[0044] This step dynamically tracks the drift of the optimal measurement range caused by changes in flow velocity, ensuring that the system can always select the electrode pair with the best current signal quality for calculation, regardless of how the flow velocity changes. This overcomes the accuracy reduction problem caused by signal attenuation and position mismatch in the background technology.

[0045] Finally (step S5), the calculation unit calculates the optimal delay based on the selected optimal delay. m peak ( j ), known sampling frequency f s and electrode spacing L Calculate the final airflow velocity. v = ( L · f s ) / m peak ( j ), and output.

Claims

1. An array electrostatic sensor, characterized in that, include: A discharge electrode is used to ionize the flowing gas to generate ions as tracers. A linear array measuring electrode, wherein the linear array measuring electrode is composed of a plurality of measuring electrodes spaced apart along the airflow direction; The discharge electrode is located upstream of the linear array measurement electrode.

2. The array electrostatic sensor according to claim 1, characterized in that, The linear array of measuring electrodes comprises 6-8 measuring electrodes.

3. The array electrostatic sensor according to claim 1, characterized in that, The measuring electrode is a flat plate electrode.

4. The array electrostatic sensor according to claim 1, characterized in that, The discharge electrodes are two needle-tip discharge electrodes.

5. An adaptive airflow velocity measurement system based on an array of electrostatic sensors, comprising: An array electrostatic sensor includes a discharge electrode and a linear array of measuring electrodes. The discharge electrode is located upstream of the linear array of measuring electrodes. The linear array of measuring electrodes consists of N measuring electrodes spaced apart along the airflow direction. The N measuring electrodes form N-1 measuring channels, where N≥3. A high-voltage ion generator, connected to the discharge electrode, is used to ionize the flowing gas and generate ions as tracers. as well as The multi-channel signal processing and calculation module acquires the electrostatic signal of the linear array measuring electrode in the array electrostatic sensor measurement; and obtains the airflow velocity based on the acquired electrostatic signal.

6. The adaptive airflow velocity measurement system according to claim 5, characterized in that, The method by which the multi-channel signal processing and calculation module obtains the airflow velocity is as follows: Collect electrostatic signals from each electrode in the linear array measurement electrode; Calculate the cross-correlation function between adjacent electrodes; Find the peak value of the cross-correlation coefficient of the electrostatic signals between each electrode; Select the measurement channel corresponding to the peak value of the cross-correlation coefficient and calculate the airflow velocity.

7. The adaptive airflow velocity measurement system according to claim 6, characterized in that, The formula for calculating the cross-correlation coefficient function is: in, R i,i+1 ( m ) is the first i The first electrode and the second i +1 cross-correlation function between measuring electrodes; m For delay points, k The sampling point number; x i ( k ) is the first i Discrete-time series signal of each electrode x i+1 ( k ) is the first i Discrete-time sequence signal with +1 electrode; For the first i Discrete-time sequence signal of each electrode x i ( k The average value of ) For the first i Discrete-time sequence signal with +1 electrode x i+1 ( k The average value of ).

8. The adaptive airflow velocity measurement system according to claim 7, characterized in that, The steps for finding the peak values ​​of the cross-correlation coefficients of electrostatic signals between adjacent electrodes include: Search n -1 Cross-correlation function of electrostatic signals of adjacent electrodes R i,i+1 ( m Each of them has its own maximum peak value; Record the number of delay points corresponding to the maximum peak value of each measurement channel, where the number of delay points is... j Maximum peak value of each channel R max ( j The corresponding delay points are denoted as m peak ( j ).

9. The adaptive airflow velocity measurement system according to claim 8, characterized in that, Select the measurement channel corresponding to the peak value of the cross-correlation coefficient, and calculate the airflow velocity. The calculated airflow velocity is: in, v The airflow velocity; f s The sampling frequency; L This represents the center-to-center distance between adjacent electrodes.

10. An adaptive airflow velocity measurement method based on the adaptive airflow velocity measurement system according to any one of claims 5-9, characterized in that, include: The gas flowing through the discharge electrode is ionized to generate ions that serve as tracers. Electrostatic signals are acquired through the linear array measuring electrodes in the array electrostatic sensor. The airflow velocity is obtained based on the acquired electrostatic signal.

Images