Counting system for online detection of granularity of electronic special gas

Abstract

The invention relates to a counting system for online detection of electronic special gas granularity. The counting system comprises an optical detection module, a gas path control module, a signal processing module, a man-machine interaction module and a data output module, the optical detection module is used for enabling particulate matters in the electronic special gas to be detected to generate scattered light signals and converting the light signals into electric pulse signals; the gas path control module is in fluid communication with the detection area of the optical detection module and is used for accurately controlling the flow, pressure and flow velocity of the electronic special gas to be detected flowing through the detection area and ensuring that the gas flow is in a laminar flow state; the signal processing module is electrically connected with the optical detection module and the gas path control module and is used for receiving and processing the electric pulse signals, and screening, counting and particle size conversion are carried out on the pulse signals through a preset algorithm so as to obtain the quantity and particle size distribution information of the particulate matters; and meanwhile, a control instruction is sent to the gas path control module.

Description

Technical Field

[0001] This invention relates to the field of gas purification and detection technology, and in particular to a counting system for online detection of particle size in electronic specialty gases. Background Technology

[0002] Electronic specialty gases are indispensable key materials in the electronics and information industries, such as semiconductor manufacturing and photovoltaic cells. Their purity and cleanliness have a decisive impact on the performance, reliability, and production yield of the final products. In the semiconductor chip manufacturing process, even trace amounts of particulate contaminants can cause short circuits, circuit damage, or device failure in integrated circuits. Therefore, strict control of particle size in electronic specialty gases is of paramount importance.

[0003] Currently, particle size detection of electronic specialty gases faces multiple technical challenges. First, electronic specialty gases are diverse, with significantly different gas properties. They include inert gases such as nitrogen and argon, as well as highly corrosive, toxic, and flammable gases such as silanes and fluorine-nitrogen mixtures. These different gases place extremely stringent requirements on the material compatibility, sealing, and safety of the detection system. Second, electronic specialty gases are typically maintained at high pressures during transportation and use, making it difficult for conventional particle counting equipment to directly connect to high-pressure gas sources and perform safe and stable sampling and measurement. Furthermore, as semiconductor process nodes continue to shrink, the sensitivity to particulate contamination further increases, requiring detection systems to identify and count particles as small as micrometers. This places extremely high demands on the resolution, stability, and anti-interference capabilities of sensors.

[0004] Most existing particle counting devices are designed for atmospheric dust or general compressed air, and their material selection, gas path design, and detection sensitivity are insufficient to meet the special requirements of electronic specialty gas detection. Although some particle counters claiming to be suitable for specific electronic specialty gases have appeared on the market, they generally still have certain application limitations. For example, these devices often lack sufficient tolerance to corrosive gases, have poor sample introduction stability under high pressure conditions, have incomplete particle size channel settings, or lack data output and system integration capabilities to adapt to complex operating conditions. In addition, traditional devices usually do not consider the need for long-term online monitoring, and they still have significant shortcomings in terms of reliability, maintenance cycle, and ease of operation.

[0005] Therefore, we propose a counting system for online detection of particle size in electronic specialty gases. Summary of the Invention

[0006] This invention proposes a counting system for online detection of particle size in electronic specialty gases, aiming to solve the technical problems existing in the prior art, such as insufficient sensitivity for small particle size detection, signal overlap processing capability, insufficient utilization of particle position information, and inflexible data output interface.

[0007] To achieve the above objectives, this invention proposes a counting system for online detection of particle size in electronic specialty gases, comprising: an optical detection module, a gas path control module, a signal processing module, a human-computer interaction module, and a data output module; The optical detection module is used to generate scattered light signals from particulate matter in the electronic special gas to be tested, and to convert the light signals into electrical pulse signals. The gas path control module is in fluid communication with the detection area of ​​the optical detection module, and is used to precisely control the flow rate, pressure and velocity of the electronic special gas to be tested flowing through the detection area, and to ensure that the airflow is in a laminar state. The signal processing module is electrically connected to the optical detection module and the gas path control module, respectively, and is used to receive and process the electrical pulse signal. It uses a preset algorithm to identify, count and convert the pulse signal to obtain the number and particle size distribution information of the particles, and sends control commands to the gas path control module. The human-computer interaction module is connected to the signal processing module and is used to set detection parameters, display real-time and historical granular detection results and system status; The data output module is connected to the signal processing module and is used to output the particle size detection results and system data to the outside in a specified format and protocol.

[0008] Preferably, the signal processing module is configured as follows: The cavity wall profile within the optical detection area is fitted using the least squares algorithm to establish a reference flow channel model for optical calibration. Based on the aforementioned reference flow channel model, the optical correction coefficients, background light intensity distribution, and boundary data of the effective detection volume at each spatial location within the optical detection area are obtained, along with the real-time flow velocity and pressure information of the particles obtained from the gas path control module. A calculation matrix is ​​then constructed to map the pulse signal features into particle size and spatial location. Based on the electrical pulse signal collected by the optical detection sensor, baseline correction and noise reduction filtering are performed to extract the effective pulse with a signal-to-noise ratio higher than the preset threshold, and its peak voltage, pulse width, and pulse area characteristics are obtained. The extracted pulse feature quantities are input into the calculation matrix to calculate the equivalent particle size and its three-dimensional spatial coordinates within the optical detection area. Based on the calculated particle spatial position and timestamp, it is determined whether there is signal overlap caused by multiple electronic special gas particles being simultaneously within the effective detection volume. If signal overlap exists, the pulse signal is discarded or a signal separation algorithm is used to estimate the particle size and position of a single particle. If there is no signal overlap, the equivalent particle size and spatial position of the particle are recorded as valid data.

[0009] Preferably, the determination of the signal overlap phenomenon is configured as follows: A four-dimensional spatiotemporal discrimination model is constructed, the four dimensions of which include at least: the three-dimensional spatial coordinates of the particle within the optical detection area, and the timestamp corresponding to the three-dimensional spatial coordinates of the particle within the optical detection area; after calculating the spatial position and timestamp of the particle corresponding to a single pulse through the calculation matrix, it is defined as an independent four-dimensional spatiotemporal event point; Multiple four-dimensional spatiotemporal event points appearing in adjacent time windows within the optical detection area are combined into a continuous time stream. When at least two four-dimensional spatiotemporal events occur simultaneously in the continuous time stream, and the three-dimensional spatial distance between them is less than the preset spatial distance threshold ΔS, and the timestamp difference is less than the preset time window threshold ΔT, it is determined that there is a signal overlap phenomenon.

[0010] Preferably, the spatial distance threshold ΔS ranges from 10 μm to 50 μm; and the time window threshold ΔT ranges from 1 μs to 100 μs.

[0011] Preferably, the optical detection module includes a laser source, an optical lens group, and a photodetector. The laser source is used to generate a laser beam that irradiates the gas to be tested. The optical lens group is used to collect the scattered light generated by the particulate matter and focus it onto the photodetector. The photodetector is used to convert the optical signal into an electrical pulse signal.

[0012] Preferably, the optical detection module is configured as a forward-scattering light detection structure, wherein the angle between the optical axis of the laser source and the optical axis of the photodetector is greater than 0 degrees and less than 30 degrees.

[0013] Preferably, the optical detection module is configured as a side-scattering light detection structure, and the angle between the optical axis of the laser source and the optical axis of the photodetector is between 70 degrees and 110 degrees.

[0014] Preferably, the data output module supports multiple industry standard communication protocols, including at least one of Modbus RTU / TCP, Profinet, and EtherNet / IP.

[0015] Preferably, the data output module is also equipped with an analog output interface for real-time output of a 4-20mA current signal that is proportional to the particulate matter concentration.

[0016] Preferably, the system also includes a self-calibration module for calibrating the detection accuracy of the optical detection module by introducing a particulate suspension of standard particle size or a standard aerosol.

[0017] The beneficial effects of the technical solution of this invention are as follows: By incorporating cavity wall contour fitting within the optical detection area into the signal processing module, a reference flow channel model is established. Based on this model, a calculation matrix is ​​constructed to calculate the equivalent particle size and its three-dimensional spatial coordinates within the optical detection area. Furthermore, based on the particle's spatial position and timestamp, it can determine whether signal overlap exists. For pulses exhibiting signal overlap, they can be discarded or processed using a signal separation algorithm, significantly improving the accuracy and reliability of high-concentration particulate matter detection and effectively avoiding the inaccurate counting and particle size measurement distortion problems caused by signal overlap in traditional systems.

[0018] Meanwhile, the signal processing module underwent functional refinement and intelligent upgrades. It not only performs basic signal identification, counting, and particle size conversion, but also ensures data source quality through baseline correction, noise reduction filtering, and effective pulse extraction. By combining the calculation matrix to solve for the particle's three-dimensional spatial position, it effectively compensates for error sources such as light field inhomogeneity and differences in particle path, resulting in more accurate particle size conversion.

[0019] The gas path control module not only precisely controls the flow rate, pressure, and velocity, but also emphasizes ensuring that the airflow is in a laminar state. This is crucial for the stable and uniform passage of particulate matter through the detection area, and is a prerequisite for ensuring detection accuracy, thus avoiding the impact of airflow disturbance on the detection results.

[0020] The human-machine interface module supports setting detection parameters and displaying real-time and historical data, providing an intuitive and convenient operating interface. The data output module supports multiple industrial standard communication protocols (such as Modbus RTU / TCP, Profinet, EtherNet / IP, etc.) and analog output interfaces, enabling the system to seamlessly integrate with various industrial automation and control systems, meeting the data integration needs of different application scenarios. Furthermore, the introduced system self-calibration module calibrates the detection accuracy using standard particle size samples, ensuring the long-term stability and reliability of the system and reducing maintenance costs. Attached Figure Description

[0021] Figure 1 This is a system block diagram according to an embodiment of the present invention; Figure 2 This is a system block diagram of an optical detection sensor according to an embodiment of the present invention; Figure 3 This is a schematic diagram of gas source sample information and bottle number identification according to one embodiment of the present invention; Figure 4 The histogram for bottle number "16A030019" (gas source: "pure enriched gas") :96ppb); Figure 5The histogram for bottle number "21W356088" (gas source is "6N gas source enriched gas"). Figure 6 The histogram for bottle number "21W363079" (gas source: "6N syngas"). Figure 7 The histogram for bottle number "23W442068" (gas source: "6N syngas"). Figure 8 The histogram for bottle number "22W121146" (gas source: syngas). :105 ppb); Figure 9 This is a histogram of bottle number "16A030192" (gas source: syngas). :114 ppb"); Figure 10 The histogram for bottle number "16A031137" (gas source is "syngas (mixed gas source)"). :226ppb"); Figure 11 The histogram for bottle number "22W124140" (gas source: "6N syngas") is shown. Figure 11 The test curve shown; Figure 12 This is a schematic diagram of gas source sample information and bottle number identification according to another embodiment of the present invention; Figure 13 The histogram for bottle number "216201073"; Figure 14 The histogram for bottle number "813301087"; Figure 15 The histogram for bottle number "206101006"; Figure 16 The histogram for bottle number "203602085"; Figure 17 The histogram for bottle number "216201106"; Figure 18 The histogram for bottle number "203602065"; Figure 19 The histogram for bottle number "203602067"; Figure 20 This is a histogram of bottle number "52901146".

[0022] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] The solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0025] It should also be noted that when a component is described as "fixed to" or "set on" another component, it can be directly on the other component or there may be an intervening component present. When a component is described as "connected to" another component, it can be directly connected to the other component or there may be an intervening component present.

[0026] Furthermore, descriptions using terms such as "first" and "second" in this invention are for descriptive purposes only (e.g., to distinguish identical or similar elements) and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" and "second" may explicitly or implicitly include at least one of those features. Additionally, technical solutions from different embodiments can be combined with each other, but only if they are feasible for those skilled in the art. If a combination of technical solutions is contradictory or impossible to implement, such a combination should be considered nonexistent and not within the scope of protection claimed by this invention.

[0027] See Figure 1 This invention proposes a counting system for online detection of particle size in electronic specialty gases, comprising: an optical detection module, a gas path control module, a signal processing module, a human-computer interaction module, and a data output module.

[0028] The optical detection module is used to perform optical detection of particulate matter in the electronic specialty gas. Specifically, the optical detection module causes the particulate matter in the electronic specialty gas to generate a scattered light signal, and converts the generated scattered light signal into an electrical pulse signal. Preferably, as follows... Figure 2 As shown, the optical detection module may include a laser source, an optical lens group, and a photodetector.

[0029] The laser source generates a high-energy, highly stable laser beam to irradiate the gas to be tested as it passes through the detection area. When particles pass through the laser beam, they generate scattered light. An optical lens group precisely collects this scattered light and focuses it onto a photodetector. The photodetector then converts the received optical signal into a corresponding electrical pulse signal. By analyzing these electrical pulse signals, information about the particle size, quantity, and the area through which the particles have passed can be obtained.

[0030] The gas path control module is fluidly connected to the detection area of ​​the optical detection module. Specifically, the gas path control module precisely controls the flow rate, pressure, and velocity of the electronic special gas to be tested flowing through the detection area. Through precise valves, flow meters, and pressure sensors, the gas to be tested passes through the detection area in a stable and controllable state, ensuring that the airflow through the detection area is laminar. Laminar airflow avoids turbulent flow of particles within the detection area, thereby ensuring that particles pass through the detection optical field with a predictable trajectory, reducing detection errors and improving detection accuracy.

[0031] The signal processing module is electrically connected to the optical detection module and the gas path control module, respectively, and is used to receive and process the electrical pulse signal. The pulse signal is identified, counted and converted into particle size using a preset algorithm to obtain the number and particle size distribution information of the particles. At the same time, control commands are sent to the gas path control module. The human-machine interface module is connected to the signal processing module, providing a user-friendly interface for operation. Users can use it to set various detection parameters, such as the detection cycle and alarm thresholds. Simultaneously, it can display the current particle size detection results and system status in real time, such as current particle concentration, environmental parameters, or equipment operating status.

[0032] The data output module is connected to the signal processing module and is used to output the granularity detection results and system data to the outside world in a specified format and protocol. Furthermore, the data output module supports multiple industrial standard communication protocols, including at least one of Modbus RTU / TCP, Profinet, and EtherNet / IP, enabling the system to seamlessly integrate into existing industrial control networks and achieve interconnection with PLCs, DCSs, or other SCADA systems.

[0033] In addition, the data output module is also equipped with an analog output interface for real-time output of a 4-20mA current signal that is proportional to the particulate matter concentration. The 4-20mA current signal is a standard analog signal widely used in the industrial field, which has the advantages of long transmission distance and strong anti-interference ability. It can be easily connected to various analog input devices to provide users with intuitive concentration trend indication.

[0034] At the same time, multiple batches of phosphine ( The gas underwent online particle size testing, which fully verified its detection performance and applicability in a real electronic special gas environment.

[0035] The test was conducted at a rated flow rate of 2.83 L / min, with each gas cylinder tested continuously for 25 minutes. The gas consumption was approximately 450 g. Data was recorded in units of "cells / cubic foot @ 0.1 μm". The gas samples used covered various gas source types and impurity backgrounds. Specific sample information and labeling are as follows: Figure 3 As shown; Specifically, during the test, the system successfully connected to sample gas cylinders under different pressure conditions, achieving sealed sampling via the VCR interface. The gas path module stably maintained the required pressure and flow rate. The optical sensor accurately captured and counted the number of particles in the 0.1μm channel, and the signal processing system completed data recording and output in real time. Specific sample test results, such as... Figures 4-12 As shown; in, Figure 4 The test results are for bottle number "16A030019" (the gas source is "pure enriched gas"). :96ppb), and Figure 4 The test curve shown initially shows a downward trend due to gas path switching, then quickly enters a stable detection range, and a small peak of 5,000,000 ± 200,000 samples / cubic foot appears at 11:01:27, indicating that the instrument has good repeatability and stability.

[0036] Figure 5 The test results are for bottle number "21W356088" (the gas source is "6N gas source enriched gas"), and Figure 5 The test curve shown initially showed a brief downward trend due to the gas path switching, followed by a step-like recovery and gradually stabilization.

[0037] Figure 6 The test results are for bottle number "21W363079" (gas source: "6N syngas"), and Figure 5 The test curve shown initially shows a downward trend due to the gas path switching, followed by a slow upward trend.

[0038] Figure 7 The test results are for bottle number "23W442068" (gas source: "6N syngas"), and Figure 7 The test curves shown generally exhibit a downward trend, with a slight peak occurring at 13:48:59. Throughout the 25-minute test period, the average particle count in the 0.1μmx channel remained stable at 400,000 ± 200,000 particles / cubic foot.

[0039] Figure 8The test results are for bottle number "22W121146" (the gas source is syngas). :105 ppb), and Figure 8 The test curve shown initially dropped sharply due to the gas path switching, then entered a gradual recovery phase, and finally reached dynamic equilibrium at 9:11:57 during the test.

[0040] Figure 9 The test results are for bottle number "16A030192" (the gas source is syngas). :114 ppb").

[0041] Figure 10 The test results are for bottle number "16A031137" (the gas source is "syngas (mixed gas source)"). :226ppb").

[0042] Figure 11 The test results are for bottle number "22W124140" (gas source: "6N syngas"), and Figure 11 The test curve is shown.

[0043] Furthermore, multiple batches of arsine ( The gas underwent online particle size testing, which fully verified its detection performance and applicability in a real electronic special gas environment.

[0044] The test was conducted at a rated flow rate of 2.83 L / min, with each gas cylinder tested continuously for 25 minutes. The gas consumption was approximately 450 g. Data was recorded in units of "cells / cubic foot @ 0.1 μm". The gas samples used covered various gas source types and impurity backgrounds. Specific sample information and labeling are as follows: Figure 12 As shown; Specifically, during the test, the system successfully connected to sample gas cylinders under different pressure conditions, achieving sealed sampling via the VCR interface. The gas path module stably maintained the required pressure and flow rate. The optical sensor accurately captured and counted the number of particles in the 0.1μm channel, and the signal processing system completed data recording and output in real time. Specific sample test results, such as... Figures 13-20 As shown; in, Figure 13 The test results are for bottle number "216201073" (the gas source is "crude enrichment gas"). The test curve (187ppb) showed that the count value rapidly climbed to its peak value and then gradually dropped back down in the initial stage due to the gas path switching.

[0045] Figure 14 The test results are for bottle number "813301087". Figure 16The test results are for bottle number "203602085" (the gas source is "passivation exhaust gas"). :123ppb").

[0046] Figure 15 The test results are for bottle number "206101006" (the gas source is syngas). :144ppb").

[0047] Figure 16 The test results are for bottle number "203602085" (the gas source is "passivation exhaust gas"). :123ppb").

[0048] Figure 17 The test results are for bottle number "216201106" (the gas source is "crude enrichment gas"). : 270ppb).

[0049] Figure 18 The test results are for bottle number "203602065" (the gas source is "6N syngas (sampling gas)").

[0050] Figure 19 The test results are for bottle number "203602067" (the gas source is "pure enriched gas"). : 202ppb").

[0051] Figure 20 The test results are for bottle number "52901146" (the gas source is syngas). :180ppb).

[0052] In summary, the system in this embodiment demonstrates excellent anti-interference capabilities and measurement repeatability when facing syngas and enriched gases with various impurities, including moisture, nitrogen, hydrogen, and ethane. It can be reliably applied to particle size monitoring of various electronic specialty gases such as phosphine and arsine, adapting to gases from different sources, from "pure enriched gas" to "industrial syngas," and meeting the diverse needs of the semiconductor industry for high-pressure, high-risk, and high-purity gas particle contamination control.

[0053] In one embodiment, the signal processing module is configured to: The cavity wall profile within the optical detection area is fitted using the least squares algorithm to establish a reference flow channel model for optical calibration. Based on the aforementioned reference flow channel model, the optical correction coefficients, background light intensity distribution, and boundary data of the effective detection volume at each spatial location within the optical detection area are obtained, along with the real-time flow velocity and pressure information of the particles obtained from the gas path control module. A calculation matrix is ​​then constructed to map the pulse signal features into particle size and spatial location. Based on the electrical pulse signal collected by the optical detection sensor, baseline correction and noise reduction filtering are performed to extract the effective pulse with a signal-to-noise ratio higher than the preset threshold, and its peak voltage, pulse width, and pulse area characteristics are obtained. The extracted pulse feature quantities are input into the calculation matrix to calculate the equivalent particle size and its three-dimensional spatial coordinates within the optical detection area. Based on the calculated particle spatial position and timestamp, it is determined whether there is signal overlap caused by multiple electronic special gas particles being simultaneously within the effective detection volume. If signal overlap exists, the pulse signal is discarded or a signal separation algorithm is used to estimate the particle size and position of a single particle. If there is no signal overlap, the equivalent particle size and spatial position of the particle are recorded as valid data.

[0054] Specifically, if signal overlap exists, the pulse signal is discarded, or a signal separation algorithm is used to estimate the particle size and position of individual particles. Discarding the signal is a direct but effective method to avoid false counting, suitable for high concentrations and situations with extremely high signal overlap rates. A better strategy is to use signal separation algorithms, such as those based on blind source separation, independent component analysis, or deep learning, to attempt to decompose overlapping pulse signals, thereby estimating the particle size and position of individual particles as accurately as possible and reducing data loss. If no signal overlap exists, the equivalent particle size and spatial position are recorded as valid data for subsequent statistical analysis.

[0055] In this embodiment, a baseline flow channel model is established by fitting the cavity wall profile within the optical detection area through the signal processing module. Based on this model, a calculation matrix is ​​constructed to calculate the equivalent particle size and its three-dimensional spatial coordinates within the optical detection area. Furthermore, based on the particle's spatial position and timestamp, it can determine whether signal overlap exists. Pulses exhibiting signal overlap can be discarded or processed using a signal separation algorithm, significantly improving the accuracy and reliability of high-concentration particulate matter detection and effectively avoiding the inaccurate counting and particle size measurement distortion problems caused by signal overlap in traditional systems.

[0056] Meanwhile, the signal processing module underwent functional refinement and intelligent upgrades. It not only performs basic signal identification, counting, and particle size conversion, but also ensures data source quality through baseline correction, noise reduction filtering, and effective pulse extraction. By combining the calculation matrix to solve for the particle's three-dimensional spatial position, it effectively compensates for error sources such as light field inhomogeneity and differences in particle path, resulting in more accurate particle size conversion.

[0057] In one embodiment, the determination of the signal overlap phenomenon is configured as follows: A four-dimensional spatiotemporal discrimination model is constructed, the four dimensions of which include at least: the three-dimensional spatial coordinates of the particle within the optical detection area, and the timestamp corresponding to the three-dimensional spatial coordinates of the particle within the optical detection area; after calculating the spatial position and timestamp of the particle corresponding to a single pulse through the calculation matrix, it is defined as an independent four-dimensional spatiotemporal event point; Multiple four-dimensional spatiotemporal event points appearing in adjacent time windows within the optical detection area are combined into a continuous time stream. When at least two four-dimensional spatiotemporal events occur simultaneously in the continuous time stream, and the three-dimensional spatial distance between them is less than the preset spatial distance threshold ΔS, and the timestamp difference is less than the preset time window threshold ΔT, it is determined that there is a signal overlap phenomenon.

[0058] In this embodiment, a baseline flow channel model is established by fitting the cavity wall contour within the optical detection area through the signal processing module. Based on this model, a calculation matrix is ​​constructed to calculate the equivalent particle size and its three-dimensional spatial coordinates within the optical detection area. More importantly, this invention can determine whether signal overlap exists based on the spatial position and timestamp of the particle. For pulses with signal overlap, they can be discarded or processed using a signal separation algorithm, significantly improving the accuracy and reliability of high-concentration particulate matter detection and effectively avoiding the inaccurate counting and particle size measurement distortion problems caused by signal overlap in traditional systems.

[0059] Specifically, the physical spatial location (X, Y, Z) of a particle and its occurrence time (T) are combined to form a four-dimensional event description. After calculating the particle spatial location and timestamp corresponding to a single pulse using the aforementioned calculation matrix, it is defined as an independent four-dimensional spatiotemporal event point.

[0060] Then, multiple four-dimensional spatiotemporal event points appearing within adjacent time windows in the optical detection area are combined into a continuous time stream. This allows the system to continuously monitor all identified particle events within the detection area and organize them in chronological order.

[0061] If, within a continuous time stream, at least two four-dimensional spatiotemporal event points exist simultaneously, and the three-dimensional spatial distance between them is less than a preset spatial distance threshold ΔS, and the timestamp difference is less than a preset time window threshold ΔT, then signal overlap is determined to exist. This judgment logic combines both spatial and temporal dimensions.

[0062] The spatial distance threshold ΔS defines the minimum physical distance at which two particles can be effectively distinguished in an optical field. If two particles are too close in space, their scattered signals may superimpose even if they are slightly offset in time.

[0063] Preferably, the spatial distance threshold ΔS is in the range of 10μm to 50μm. This range takes into account the current limit resolution of optical detection technology and the typical particle size, and can effectively distinguish the spacing between tiny particles.

[0064] On the other hand, the time window threshold ΔT defines the possibility of overlap if multiple particle events occur within a very short time period. Even if the particles are spatially separated, if they pass through the detection area consecutively within a very short time, it may cause signal waveform overlap.

[0065] Preferably, the time window threshold ΔT ranges from 1 μs to 100 μs. This range takes into account both the typical flow rate of particles and the response speed of the photodetector, ensuring that overlapping events that are close in time can be captured. By simultaneously satisfying these two conditions, the system can more accurately and reliably identify signal overlap phenomena, avoiding false positives and false negatives.

[0066] In one embodiment, the optical detection module is configured as a forward-scattering light detection structure, wherein the angle between the optical axis of the laser source and the optical axis of the photodetector is greater than 0 degrees and less than 30 degrees.

[0067] In one embodiment, the optical detection module is configured as a side-scattering light detection structure, wherein the angle between the optical axis of the laser source and the optical axis of the photodetector is between 70 degrees and 110 degrees.

[0068] In one embodiment, a system self-calibration module is also included, which is used to calibrate the detection accuracy of the optical detection module by introducing a particulate suspension or standard aerosol of standard particle size. Thus, at a preset calibration cycle or according to user instructions, the system self-calibration module will automatically introduce standard particulate matter of known particle size and concentration into the detection area, and then correct and optimize parameters such as the photoelectric conversion coefficient and particle size conversion algorithm of the system by analyzing the deviation between the detection results and the standard values, so as to ensure that the system can maintain high accuracy and high reliability even after long-term operation.

[0069] The above description is only a part or preferred embodiment of the present invention. Neither the text nor the drawings should limit the scope of protection of the present invention. All equivalent structural transformations made using the content of the present invention specification and drawings under the overall concept of the present invention, or direct / indirect applications in other related technical fields, are included within the scope of protection of the present invention.

Claims

1. A counting system for online detection of particle size in electronic specialty gases, comprising: The optical detection module, the pneumatic path control module, the signal processing module, the human-machine interaction module, and the data output module are characterized in that; The optical detection module is used to generate scattered light signals from particulate matter in the electronic special gas to be tested, and to convert the light signals into electrical pulse signals. The gas path control module is in fluid communication with the detection area of ​​the optical detection module, and is used to precisely control the flow rate, pressure and velocity of the electronic special gas to be tested flowing through the detection area, and to ensure that the airflow is in a laminar state. The signal processing module is electrically connected to the optical detection module and the gas path control module, respectively, and is used to receive and process the electrical pulse signal. It uses a preset algorithm to identify, count and convert the pulse signal to obtain the number and particle size distribution information of the particles, and sends control commands to the gas path control module. The human-computer interaction module is connected to the signal processing module and is used to set detection parameters, display real-time and historical granular detection results and system status; The data output module is connected to the signal processing module and is used to output the particle size detection results and system data to the outside in a specified format and protocol.

2. The counting system for online detection of particle size of electronic special gases according to claim 1, characterized in that, The signal processing module is configured as follows: The cavity wall profile within the optical detection area is fitted using the least squares algorithm to establish a reference flow channel model for optical calibration. Based on the aforementioned reference flow channel model, the optical correction coefficients, background light intensity distribution, and boundary data of the effective detection volume at each spatial location within the optical detection area are obtained, along with the real-time flow velocity and pressure information of the particles obtained from the gas path control module. A calculation matrix is ​​then constructed to map the pulse signal features into particle size and spatial location. Based on the electrical pulse signal collected by the optical detection sensor, baseline correction and noise reduction filtering are performed to extract the effective pulse with a signal-to-noise ratio higher than the preset threshold, and its peak voltage, pulse width, and pulse area characteristics are obtained. The extracted pulse feature quantities are input into the calculation matrix to calculate the equivalent particle size and its three-dimensional spatial coordinates within the optical detection area. Based on the calculated particle spatial position and timestamp, it is determined whether there is signal overlap caused by multiple electronic special gas particles being simultaneously within the effective detection volume. If signal overlap exists, the pulse signal is discarded or a signal separation algorithm is used to estimate the particle size and position of a single particle. If there is no signal overlap, the equivalent particle size and spatial position of the particle are recorded as valid data.

3. A counting system for online detection of particle size in electronic specialty gases according to claim 2, characterized in that, The determination of the signal overlap phenomenon is configured as follows: A four-dimensional spatiotemporal discrimination model is constructed, the four dimensions of which include at least: the three-dimensional spatial coordinates of the particle within the optical detection area, and the timestamp corresponding to the three-dimensional spatial coordinates of the particle within the optical detection area; after calculating the spatial position and timestamp of the particle corresponding to a single pulse through the calculation matrix, it is defined as an independent four-dimensional spatiotemporal event point; Multiple four-dimensional spatiotemporal event points appearing in adjacent time windows within the optical detection area are combined into a continuous time stream. When at least two four-dimensional spatiotemporal events occur simultaneously in the continuous time stream, and the three-dimensional spatial distance between them is less than the preset spatial distance threshold ΔS, and the timestamp difference is less than the preset time window threshold ΔT, it is determined that there is a signal overlap phenomenon.

4. A counting system for online detection of particle size in electronic specialty gases according to claim 4, characterized in that, The spatial distance threshold ΔS ranges from 10 μm to 50 μm; the time window threshold ΔT ranges from 1 μs to 100 μs.

5. A counting system for online detection of particle size in electronic specialty gases according to claim 1, characterized in that, The optical detection module includes a laser source, an optical lens group, and a photodetector. The laser source is used to generate a laser beam that irradiates the gas to be tested. The optical lens group is used to collect the scattered light generated by the particulate matter and focus it onto the photodetector. The photodetector is used to convert the optical signal into an electrical pulse signal.

6. A counting system for online detection of particle size in electronic specialty gases according to claim 5, characterized in that, The optical detection module is configured as a forward-scattering light detection structure, and the angle between the optical axis of the laser source and the optical axis of the photodetector is greater than 0 degrees and less than 30 degrees.

7. A counting system for online detection of particle size in electronic specialty gases according to claim 5, characterized in that, The optical detection module is configured as a side-scattering light detection structure, and the angle between the optical axis of the laser source and the optical axis of the photodetector is between 70 degrees and 110 degrees.

8. A counting system for online detection of particle size in electronic specialty gases according to claim 1, characterized in that, The data output module supports multiple industry standard communication protocols, including at least one of Modbus RTU / TCP, Profinet, and EtherNet / IP.

9. A counting system for online detection of particle size in electronic specialty gases according to claim 8, characterized in that, The data output module is also equipped with an analog output interface for real-time output of a 4-20mA current signal that is proportional to the particulate matter concentration.

10. A counting system for online detection of particle size in electronic specialty gases according to claim 1, characterized in that, It also includes a system self-calibration module, which is used to calibrate the detection accuracy of the optical detection module by introducing a particulate suspension or standard aerosol of standard particle size.

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