An online coal dust measurement system suitable for high-concentration coal dust

Abstract

This invention belongs to the field of high-concentration pulverized coal air-powder concentration measurement technology, and discloses an online pulverized coal air-powder measurement system suitable for high-concentration pulverized coal. This invention employs a dual-channel pulverized coal concentration measurement method using both capacitance and acoustic methods. Based on the measurement results, it identifies anomalies and outputs a comprehensive pulverized coal concentration. The two methods are cross-validated, and anomalies are identified by comparing deviations in the measurement results, avoiding errors from a single method. Combining the advantages of both methods improves measurement accuracy and enhances the system's anti-interference capability and long-term operational stability. This invention also incorporates a dynamic cleaning mechanism for the surface material adhering to the device. A CCD imaging device monitors the thickness of the material adhering to the surface of the capacitance sensor and ultrasonic detection device in real time. The cleaning operation is dynamically executed based on the average material adhering thickness and the percentage of monitoring points exceeding the threshold. This reduces measurement errors, ensures long-term stable operation of the equipment, and improves system reliability.

Description

Technical Field

[0001] This invention belongs to the field of high-concentration pulverized coal air-powder concentration measurement technology, and relates to an online air-powder measurement system suitable for high-concentration pulverized coal. Background Technology

[0002] The transportation and combustion of high-concentration pulverized coal are common in industries such as power generation, metallurgy, and chemicals. Accurate monitoring of the pulverized coal concentration in the air-coal mixture is crucial for optimizing combustion efficiency, reducing energy consumption, minimizing pollutant emissions, and ensuring the safe and stable operation of the system. With the expansion of industrial production scale and increasing environmental protection requirements, higher demands are being placed on the accuracy, reliability, and real-time performance of online measurement of high-concentration pulverized coal.

[0003] Traditional technical solutions for measuring the concentration of high-concentration pulverized coal in air typically employ one of the following methods: capacitance method, acoustic method, or other methods. This measurement method is easily affected by environmental factors when measuring the concentration of high-concentration pulverized coal in air, resulting in low measurement accuracy. At the same time, single methods lack anomaly identification mechanisms, making it difficult to detect and handle errors in a timely manner.

[0004] Traditional technical solutions lack dynamic cleaning operations for material buildup on equipment surfaces based on actual abnormal conditions. This approach cannot monitor changes in material thickness in real time. When material accumulates on the sensor surface, it alters the electric field distribution of the capacitive sensor, affecting the performance of the ultrasonic testing device probe and leading to a continuous increase in measurement errors. Furthermore, due to the lack of a dynamic cleaning mechanism, automatic cleaning is not possible even when the material thickness exceeds a threshold. Over long-term operation, the equipment may fail due to material buildup issues, making it difficult to guarantee measurement accuracy and resulting in poor system stability and reliability. Summary of the Invention

[0005] In view of this, in order to solve the problems mentioned in the background art, an online coal dust measurement system suitable for high-concentration coal dust is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: an online coal dust measurement system suitable for high-concentration coal dust, comprising: a capacitance measurement module, which uses a capacitance sensor to monitor capacitance changes, outputs the coal dust concentration measured by capacitance based on a pre-built capacitance change-coal dust concentration relationship model, and collects ambient temperature, humidity, and sensor material thickness to correct the coal dust concentration measured by capacitance.

[0007] The acoustic wave measurement module uses an ultrasonic detection device to monitor the acoustic wave attenuation. Based on a pre-built model of the relationship between acoustic wave attenuation and coal powder concentration, it outputs the acoustic wave measurement of coal powder concentration. It also collects ambient temperature and coal powder particle size to correct the acoustic wave measurement of coal powder concentration.

[0008] The fusion analysis module compares the corrected capacitance measurement coal powder concentration with the acoustic measurement coal powder concentration to determine if there is a measurement anomaly. If no anomaly is found, the module outputs the comprehensive coal powder concentration. If an anomaly is found, the measurement operation is repeated to identify the abnormal measurement method and output the comprehensive coal powder concentration.

[0009] The device cleaning module uses a CCD imaging device to collect the thickness of the material adhering to the surface of the capacitive sensor and ultrasonic detection device in real time, and uses the cleaning device to dynamically perform the device cleaning operation.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention sets up a dual-channel coal powder concentration measurement method using capacitance method and acoustic method, identifies abnormal situations and outputs comprehensive coal powder concentration based on the measurement results, verifies the two methods against each other, identifies abnormalities based on the deviation of the measurement results, and avoids errors of a single method; when there is an abnormality, the method of repeatedly measuring and calculating the fluctuation index to locate the problem ensures the reliability of the data; when there is no abnormality, the comprehensive concentration is output according to the historical weight, combining the advantages of the two methods to improve the measurement accuracy, enhance the system's anti-interference ability and long-term operational stability.

[0011] (2) The present invention sets up a dynamic cleaning mechanism for the surface of the device. The thickness of the surface of the capacitive sensor and the ultrasonic detection device is monitored in real time by a CCD imaging device. The cleaning operation is dynamically executed based on the average thickness of the surface and the percentage of monitoring points exceeding the threshold. This can remove the surface of the device that affects the measurement in a timely manner, prevent the surface of the device from changing the working characteristics of the sensor, maintain the distribution of the capacitive electric field and the accuracy of the acoustic wave detection, reduce measurement errors, ensure the long-term stable operation of the equipment, and improve the reliability of the system. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a schematic diagram showing the connections of the various modules in the system of the present invention.

[0014] Figure 2 A schematic diagram illustrating the process of constructing a model for the relationship between capacitance change and pulverized coal concentration, corresponding to one embodiment of the present invention.

[0015] Figure 3 A schematic diagram illustrating the construction process of the acoustic attenuation-coal powder concentration relationship model corresponding to one embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of 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 some embodiments of the present invention, and not all embodiments. 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.

[0017] Please see Figure 1 As shown, the present invention provides an online coal dust measurement system suitable for high-concentration coal dust, including a capacitance measurement module, an acoustic measurement module, a fusion analysis module, and a device cleaning module, wherein the capacitance measurement module and the acoustic measurement module are both connected to the fusion analysis module, and the device cleaning module is connected to the capacitance measurement module.

[0018] The capacitance measurement module uses a capacitance sensor to monitor the change in capacitance. Based on a pre-built model of the relationship between capacitance change and coal powder concentration, it outputs the coal powder concentration measured by capacitance. It also collects ambient temperature, humidity, and the thickness of the material attached to the sensor to correct the coal powder concentration measured by capacitance.

[0019] For a preferred embodiment of the present invention, please refer to Figure 2 As shown, the specific construction method of the capacitance change-coal powder concentration relationship model is as follows: A1. Clarify that the capacitance change is the input variable and the coal powder concentration measured by capacitance is the output variable.

[0020] A2. Construct an experimental environment to simulate the transportation of high-concentration pulverized coal, set up multiple sets of working conditions with different pulverized coal concentrations, and collect a large amount of capacitance change data under each working condition using a high-precision capacitive sensor. At the same time, use the weighing method to accurately obtain the corresponding true value of pulverized coal concentration and construct the original dataset.

[0021] A3. Classify the operating conditions corresponding to the same capacitance change and extract the coal powder concentration for each operating condition.

[0022] A4. The average value of the coal powder concentration corresponding to each change in capacitance under different operating conditions is calculated to obtain the coal powder concentration corresponding to each change in capacitance.

[0023] A5. Construct a model of the relationship between capacitance change and coal powder concentration by mapping each capacitance change to its corresponding coal powder concentration.

[0024] It should be noted that when constructing the model relating capacitance change to pulverized coal concentration, a simulated high-concentration pulverized coal conveying experimental environment was built. Multiple sets of capacitance change data and weighing method true values ​​under different concentration conditions were collected to ensure the original dataset has broad coverage and high accuracy. Classifying the operating conditions corresponding to the same capacitance change and calculating the average pulverized coal concentration effectively eliminates random errors from single operating conditions, making the model output more reliable. By establishing a strict mapping relationship between capacitance change and pulverized coal concentration, this model accurately reflects concentration changes during actual conveying, providing a scientific basis for the capacitance measurement module. Compared to traditional single measurement methods, it significantly improves the accuracy and environmental adaptability of high-concentration pulverized coal measurement.

[0025] In a preferred embodiment of the present invention, the specific analysis method of the thickness of the material attached to the sensor is as follows: the surface image of the capacitance sensor is acquired in real time using a CCD imaging device, the time corresponding to the change in capacitance monitored by the capacitance sensor is obtained, and the surface image of the capacitance sensor corresponding to that time is extracted as the surface image of the monitoring capacitance sensor.

[0026] The electric field distribution of the capacitive sensor is simulated using electric field distribution simulation software to obtain the maximum electric field strength of the capacitive sensor. The electric field strength discrimination value is obtained by multiplying the preset ratio with the maximum electric field strength. The spatial area with electric field strength greater than the electric field strength discrimination value is defined as the key monitoring spatial area.

[0027] It should be noted that the higher the electric field strength of the capacitive sensor, the stronger its attraction to coal dust particles. Therefore, coal dust is more likely to accumulate in areas with high electric field strength, forming deposits. For example, the electric field strength at the edges and corners of the sensor electrodes is usually greater than that in planar areas. Deposits accumulate faster in these locations and have a more significant impact on capacitance measurements.

[0028] It should be noted that the preset ratio is based on the correlation experiment between electric field strength and the amount of coal powder adsorbed. For example, when the electric field strength is greater than 30% of the maximum value, the amount of coal powder adsorbed exceeds 70% of the total amount of coal powder adsorbed. In this case, using this intensity as the distinguishing threshold can accurately locate the area that has the greatest impact on the measurement.

[0029] The key monitoring area is mapped onto the inner surface of the capacitive sensor to obtain the monitoring plane area.

[0030] It should be noted that the reason for analyzing only the inner surface of the capacitive sensor when performing the material coating thickness analysis in this invention is as follows: The capacitive sensor measures the coal powder concentration by detecting the change in dielectric constant between the electrodes. Its electric field is mainly distributed on the inner side of the sensor, that is, the surface in direct contact with the coal powder flow. When coal powder adheres to the inner surface of the sensor, it directly changes the dielectric distribution between the electrodes, thus affecting the measurement result of the capacitance change. The outer surface, however, does not contact the coal powder flow, and the amount of material accumulation is minimal, so its impact on the capacitance measurement is negligible.

[0031] Several material thickness monitoring points are obtained by uniformly distributing points on the inner surface of the capacitive sensor. The distance between the real-time spatial position and the initial spatial position of each material thickness monitoring point is recorded as the material thickness of each monitoring point.

[0032] Specifically, the uniform distribution of dots can be a grid pattern, and the specific density can be determined based on the sensor size and measurement accuracy requirements.

[0033] The material thickness monitoring points are divided according to their distribution location to obtain the material thickness monitoring points corresponding to the key monitoring areas and the material thickness monitoring points corresponding to other areas.

[0034] The average thickness of the material at each monitoring point in the key monitoring area is used to calculate the thickness of the material in the key area. The average thickness of the material at each monitoring point in other areas is used to calculate the thickness of the material in other areas.

[0035] The thickness of the capacitive sensor is calculated by merging the thickness of the material in the key area with the thickness of the material in other areas according to a preset weight.

[0036] Specifically, the weight fusion calculation method can be weight summation.

[0037] It should be noted that the weighting is based on the quantitative relationship between the electric field distribution and the impact of the coal powder adsorbed. For example, electric field simulation shows that key areas with an electric field strength greater than 30% of the maximum value adsorb more than 70% of the total coal powder adsorbed, contributing 70% to the capacitance measurement error. For every 1mm increase in the coal powder thickness in these areas, the error increases by 5%, while the coal powder and error contribution in other areas only account for 30%. Therefore, based on the proportion of coal powder adsorbed and the degree of error impact, the weights for key areas are set to 0.7-0.8, and for other areas to 0.2-0.3. These weights can be adjusted according to the coal powder particle size, humidity, and other operating conditions to ensure that the weighting accurately matches the dominant role of high-electric-field areas in the measurement error.

[0038] It's important to note the advantages of differentiating between key areas and other regions for coating thickness analysis: It avoids uniform monitoring of the entire sensor surface, instead focusing on key areas with high electric field strength, thus improving the efficiency and relevance of coating thickness monitoring. Coating thickness is a crucial parameter for capacitance measurement correction; by accurately delineating key areas, the impact of coating on capacitance changes can be calculated more precisely. Electric field distribution simulation can be adjusted based on sensor model, installation method, and other parameters to adapt to different operating conditions and electric field distribution characteristics, ensuring that the delineation of key monitoring areas always conforms to actual coating patterns.

[0039] In a preferred embodiment of the present invention, the specific analytical method for correcting the pulverized coal concentration by capacitance measurement is as follows: extract the ambient temperature, humidity and sensor coating thickness, and compare the deviation with the pre-calibrated first reference temperature, reference humidity and reference sensor coating thickness.

[0040] It should be noted that the reasons for correcting the capacitance measurement of pulverized coal concentration by considering ambient temperature, humidity, and sensor coating thickness are as follows: Increased temperature causes thermal expansion and contraction of the sensor electrode material, altering the electrode spacing; simultaneously, the dielectric constant of air changes with temperature. Increased humidity causes pulverized coal particles to absorb moisture, increasing the dielectric constant and thus affecting the capacitance change. Accumulation of coating material on the sensor surface alters the electric field distribution.

[0041] It should be added that the settings for the first reference temperature, reference humidity, and reference sensor coating thickness are based on the following: These settings are based on standard operating conditions, such as a temperature of 25℃, humidity of 50%RH, and coating thickness of 0mm. Under these conditions, the capacitive sensor is in its ideal working state, with minimal measurement error. This setting is based on extensive experimental data. By calibrating the baseline values ​​under conditions of no environmental interference and coating thickness, a unified standard is provided for subsequent deviation comparisons, ensuring that the correction coefficient calculation accurately reflects the impact of environmental factors and coating thickness on the measurement.

[0042] It should be noted that the specific calculation method for the deviation comparison is as follows: the relative deviation of each parameter is obtained by calculating the difference between the ambient temperature, humidity and sensor coating thickness and the pre-calibrated first reference temperature, reference humidity and reference sensor coating thickness.

[0043] Based on the deviation comparison results, the first temperature correction coefficient, humidity correction coefficient, and material thickness correction coefficient are obtained. The comprehensive correction coefficient for capacitance measurement is obtained by multiplying the correction coefficients together.

[0044] It should be noted that the relative deviation directly determines the magnitude of the correction coefficient, and the specific value is obtained through a pre-constructed relative deviation-correction coefficient mapping table.

[0045] Furthermore, when constructing the relative deviation-correction coefficient mapping table, the capacitive sensor output reference value is first calibrated under standard operating conditions. Then, operating conditions with different ambient temperatures, humidity, and material thicknesses are simulated, and the deviation between the measured capacitance value and the reference value under each condition is collected. Simultaneously, the true value of the actual pulverized coal concentration is obtained using the weighing method. The correction coefficient corresponding to each deviation is calculated, i.e., the ratio of the actual concentration to the measured concentration. A one-to-one mapping relationship is established between the deviation and the correction coefficient. After fitting multiple sets of experimental data, the data is stored in the mapping table to ensure that the matching correction coefficient can be directly queried through the real-time deviation, thereby achieving accurate correction of the measured capacitance concentration.

[0046] The corrected pulverized coal concentration is obtained by multiplying the capacitance measurement pulverized coal concentration by the capacitance measurement comprehensive correction coefficient, and then summing the correction with the capacitance measurement pulverized coal concentration.

[0047] The acoustic wave measurement module uses an ultrasonic detection device to monitor the acoustic wave attenuation. Based on a pre-built model of the relationship between acoustic wave attenuation and coal powder concentration, it outputs the acoustic wave measurement of coal powder concentration. It also collects ambient temperature and coal powder particle size to correct the acoustic wave measurement of coal powder concentration.

[0048] It should be noted that the acoustic attenuation-coal powder concentration relationship model collects multi-condition data by simulating a high-concentration coal powder transportation environment and obtains the true value by combining it with the weighing method, ensuring that the original data has a wide coverage and high accuracy. A functional relationship is established through regression analysis of multiple sets of data. After verification and optimization, the coal powder concentration can be accurately calculated based on the real-time acoustic attenuation. Its advantages lie in its strong data reliability and high model accuracy, accurately reflecting the concentration changes during actual transportation, providing a scientific calculation basis for the acoustic measurement module, and improving the accuracy and environmental adaptability of high-concentration coal powder measurement.

[0049] For a preferred embodiment of the present invention, please refer to Figure 3 As shown, the specific construction method of the sound wave attenuation-coal powder concentration relationship model is as follows: B1. In a closed coal powder conveying experimental pipeline, the ambient temperature and the standard value of coal powder particle size are fixed.

[0050] B2. By adjusting the coal feed rate, a coal powder concentration distribution with uniform distribution from low to high is generated.

[0051] B3. After each operating condition stabilizes, the sound wave attenuation data measured by the ultrasonic device and the true value of coal powder concentration obtained by the high-precision reference method are collected synchronously to form the original dataset.

[0052] B4. Classify and group the sound wave attenuation according to the numerical range, take the arithmetic mean of the true concentration values ​​under different working conditions within the same sound wave attenuation range, and establish a strict mapping relationship table between the sound wave attenuation range and the average coal powder concentration.

[0053] B5. Based on this mapping table, a basic relationship model is generated that corresponds one-to-one between the input value of acoustic attenuation and the output value of pulverized coal concentration.

[0054] In a preferred embodiment of the present invention, the specific method for correcting the coal powder concentration measured by acoustic wave is as follows: extract the ambient temperature and coal powder particle size, and compare the deviation with the pre-calibrated second reference temperature and reference coal powder particle size, respectively.

[0055] It should be noted that the relative temperature deviation refers to the result of the calculation of the difference between the actual temperature and the second reference temperature. Temperature changes will change the propagation speed of sound waves in the medium, thus affecting the measurement of attenuation. The relative particle size deviation refers to the result of the calculation of the difference between the actual particle size and the reference particle size. The larger the coal powder particle size, the stronger the scattering and absorption of sound waves.

[0056] Based on the deviation comparison results, a second temperature correction coefficient and a coal powder particle size correction coefficient are obtained. Multiplying the correction coefficients together yields a comprehensive correction coefficient for acoustic wave measurement.

[0057] It should be noted that by comparing the relative deviation and combining it with the pre-constructed relative deviation-correction coefficient mapping table, the correction coefficients corresponding to temperature and particle size can be directly obtained, providing accurate input for subsequent comprehensive correction and ensuring that the concentration error of acoustic wave measurement is reduced to within a controllable range.

[0058] The corrected coal powder concentration is obtained by multiplying the coal powder concentration measured by acoustic wave by the comprehensive correction coefficient of acoustic wave measurement, and then summing it with the coal powder concentration measured by acoustic wave to obtain the corrected coal powder concentration measured by acoustic wave.

[0059] The fusion analysis module compares the corrected capacitance measurement coal powder concentration with the acoustic measurement coal powder concentration to determine if there is a measurement anomaly. If no anomaly is found, the module outputs the comprehensive coal powder concentration. If an anomaly is found, the measurement operation is repeated to identify the abnormal measurement method and output the comprehensive coal powder concentration.

[0060] In a preferred embodiment of the present invention, the specific method for determining whether there is a measurement anomaly is as follows: the difference between the corrected capacitance measurement of coal powder concentration and the acoustic measurement of coal powder concentration is calculated to obtain the coal powder concentration deviation between the two measurement methods.

[0061] The relative deviation of coal powder concentration is calculated by comparing the deviation with the corrected capacitance measurement coal powder concentration and the corrected acoustic measurement coal powder concentration.

[0062] The deviation of the relative capacitance measurement of coal powder concentration and the deviation of the relative acoustic measurement of coal powder concentration are compared with the preset allowable deviation thresholds. If any parameter exceeds the allowable deviation threshold, it is determined that there is a measurement abnormality; otherwise, it is determined that there is no measurement abnormality.

[0063] It should be noted that this anomaly detection logic achieves rapid identification of measurement anomalies by quantifying the relative deviation between the two measurement methods and comparing it with a threshold. Specifically, it first calculates the relative deviation between the concentration measured by the capacitance method and the concentration measured by the acoustic method, and then compares each with a pre-set allowable deviation threshold. If the relative deviation of either method exceeds the threshold, it indicates insufficient consistency between the two measurement results, which may be due to sensor failure, material buildup interference, or abnormal environmental parameters, and is therefore judged as a measurement anomaly. If neither exceeds the threshold, it indicates that the measurement results of the two methods are consistent, and the system is in normal working condition. This method, through dual measurement cross-validation, can effectively eliminate measurement errors from a single method.

[0064] It should be noted that the allowable deviation threshold is set based on the consistency requirement of the dual measurement principle. Extensive experiments have determined that when the relative deviation between the capacitance and acoustic wave concentration measurements is within the preset threshold, the measurement results show good consistency, and the system operates normally. Deviations exceeding this range may be due to sensor malfunction, material buildup, or environmental interference. This threshold, taking into account measurement method errors and operating condition fluctuations, was determined after verification under multiple operating conditions to ensure a high accuracy rate in anomaly detection.

[0065] In a preferred embodiment of the present invention, the specific method for outputting the comprehensive coal powder concentration if it does not exist is as follows: extract the corrected capacitance measurement coal powder concentration and the corrected acoustic measurement coal powder concentration, and then calculate the comprehensive coal powder concentration by summing the weights of the weighting factors obtained by fitting historical data.

[0066] It should be noted that the weights mentioned above are set as follows: First, based on the sensor's principle characteristics and actual operating conditions, the weights for the capacitance method and the acoustic method are calculated separately. For the capacitance method weights, real-time temperature, humidity, and material thickness are input, and a formula containing calibration coefficients fitted from historical data is used for calculation. For the acoustic method weights, coal powder particle size and ambient temperature are input, and a formula containing calibration coefficients and a reference temperature is used for calculation. Second, the calculated capacitance and acoustic method weights are normalized and converted into proportional coefficients. The two are then added together to equal 1 to obtain the final weights used for comprehensive calculation.

[0067] In a preferred embodiment of the present invention, the specific method for identifying abnormal measurement methods and outputting the comprehensive coal powder concentration is as follows: when it is determined that there is a measurement abnormality, a number of capacitance measurement operations and acoustic wave measurement operations are performed continuously.

[0068] It should be noted that when an anomaly is initially detected, the system will not directly accept the current result. Instead, it will repeatedly perform capacitance and acoustic wave measurements. This serves two purposes: first, multiple sampling eliminates occasional interference; if the interference is sporadic, the data will return to normal after multiple measurements; second, it verifies whether the sensor is truly faulty. If the deviation from multiple measurements consistently exceeds the threshold, it can be generally determined that there is a hardware problem with the sensor. Subsequent steps can then trigger a fault alarm or calibration process, thereby improving the reliability of the measurement results and preventing a single misjudgment from affecting the system's accurate monitoring of pulverized coal concentration.

[0069] The variance of the coal powder concentration measured by capacitance measurement corresponding to each capacitance measurement operation is calculated to obtain the fluctuation index of capacitance measurement. Similarly, the variance of the coal powder concentration measured by acoustic wave measurement corresponding to each acoustic wave measurement operation is calculated to obtain the fluctuation index of acoustic wave measurement.

[0070] The fluctuation index measured by the capacitance method and the fluctuation index measured by the acoustic method are compared with a preset fluctuation index threshold. If the fluctuation index measured by the capacitance method is greater than the fluctuation index threshold, the abnormal measurement method is identified as the capacitance method. If the fluctuation index measured by the acoustic method is greater than the fluctuation index threshold, the abnormal measurement method is identified as the acoustic method.

[0071] It should be noted that by collecting data from capacitance and acoustic methods under normal operating conditions, such as when the coal powder concentration is stable and the sensors are fault-free, the statistical distribution of the fluctuation index is calculated. The threshold is usually set as the upper limit of the normal fluctuation range, such as the mean of the normal fluctuation index plus twice the standard deviation, to ensure that data fluctuations under normal operating conditions will not trigger abnormal identification.

[0072] If an anomaly is identified in one measurement method, the average coal powder concentration corresponding to each measurement operation of the other measurement method will be used as the output of the comprehensive coal powder concentration.

[0073] If both measurement methods are determined to be abnormal, an alert will be issued and sent to the administrator for handling of the abnormal situation.

[0074] It should be noted that this invention uses a dual-channel coal powder concentration measurement method, employing both capacitance and acoustic methods. Based on the measurement results, it identifies anomalies and outputs a comprehensive coal powder concentration. The two methods are cross-validated, and anomalies are identified by comparing deviations in the measurement results, avoiding errors from a single method. In case of anomalies, repeated measurements are performed and fluctuation indices are calculated to pinpoint the problem, ensuring data reliability. When no anomalies are found, the comprehensive concentration is output based on historical weights. By combining the advantages of both methods, the measurement accuracy is improved, and the system's anti-interference capability and long-term operational stability are enhanced.

[0075] The device cleaning module uses a CCD imaging device to collect the thickness of the material adhering to the surface of the capacitive sensor and ultrasonic detection device in real time, and uses the cleaning device to dynamically perform the device cleaning operation.

[0076] In a preferred embodiment of the present invention, the specific method of the cleaning operation of the dynamic execution device is as follows: a number of cleaning judgment monitoring points are obtained by uniformly distributing points on the inner surface of the capacitive sensor and the probe of the ultrasonic detection device.

[0077] The thickness of the material adhering to each cleaning judgment monitoring point is acquired in real time, and the average value of each cleaning judgment monitoring point is calculated as the average thickness of the material adhering to each device. The device includes a capacitive sensor and an ultrasonic detection device.

[0078] The average material thickness of each device is compared with the preset cleaning threshold, and the material thickness at each cleaning judgment monitoring point of each device is also compared with the preset cleaning threshold.

[0079] It should be noted that the cleaning threshold is set based on sensor characteristics and operating conditions. Based on experiments on the impact of coal dust accumulation on measurement accuracy using capacitors and acoustic wave devices, and combined with historical data on accumulation rates under different humidity levels and coal dust particle sizes, basic thresholds such as material thickness and acoustic wave attenuation are set. These are then dynamically adjusted according to production load and optimized through machine learning to ensure that cleaning after the threshold is triggered minimizes measurement error, while balancing cleaning energy consumption and equipment lifespan.

[0080] If the average thickness of the material deposited on a device exceeds the cleaning threshold, then a device cleaning operation will be performed on that device.

[0081] It should be noted that the cleaning threshold is the key trigger condition for the dynamic actuator to start the automatic cleaning operation. It is a quantitative indicator set based on equipment characteristics, operating conditions, and measurement accuracy requirements. Essentially, by setting a reasonable critical value, it automates the decision-making process regarding the risk of material buildup and the cleaning action, preventing measurement failures or equipment malfunctions due to material accumulation.

[0082] If a device has more than a preset percentage of cleaning judgment monitoring points where the thickness of the material adhering to the material exceeds the cleaning threshold, then a device cleaning operation will be performed on that device.

[0083] It should be added that the cleaning operation of the device can use one or more cleaning methods. For example, for cleaning a capacitive sensor, the built-in pulse blowing device is activated to blow along the electrode surface in a directional manner for 5-10 seconds to remove the adhering material; if the adhering material is stubborn, a mechanical vibration module is used to assist in peeling it off, avoiding damage to the electrode. For cleaning an acoustic device, a combination of air knife and brush is used to clean the acoustic emitting and receiving probes: the air knife sprays compressed air to remove surface powder, and then the electric brush rotates to wipe the probe, ensuring that the acoustic path is unobstructed.

[0084] It should be noted that this invention incorporates a dynamic cleaning mechanism for surface-mounted materials. This mechanism uses a CCD imaging device to monitor the thickness of the material buildup on the surfaces of the capacitance sensor and ultrasonic testing device in real time. The cleaning operation is dynamically executed based on the average material thickness and the percentage of monitoring points exceeding the threshold. This timely removal of material buildup that could affect measurements prevents it from altering the sensor's operating characteristics, maintains the capacitance field distribution and acoustic detection accuracy, reduces measurement errors, ensures long-term stable operation of the equipment, and improves system reliability.

[0085] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A wind powder online measurement system suitable for high concentration of coal powder, characterized in that, The application relates to a coal powder concentration measuring device and method. The device comprises: a capacitance measuring module which monitors a capacitance change amount by using a capacitance sensor, outputs a capacitance-measured coal powder concentration based on a pre-constructed capacitance change amount-coal powder concentration relationship model, collects environmental temperature, humidity and sensor hanging material thickness, and corrects the capacitance-measured coal powder concentration; a sound wave measuring module which monitors a sound wave attenuation amount by using an ultrasonic detection device, outputs a sound wave-measured coal powder concentration based on a pre-constructed sound wave attenuation amount-coal powder concentration relationship model, collects environmental temperature and coal powder granularity, and corrects the sound wave-measured coal powder concentration; a fusion analysis module which compares the corrected capacitance-measured coal powder concentration and the sound wave-measured coal powder concentration to determine whether measurement abnormality exists, outputs a comprehensive coal powder concentration if no measurement abnormality exists, and repeatedly measures if measurement abnormality exists, identifies an abnormal measurement mode and outputs the comprehensive coal powder concentration. The specific way of determining whether measurement abnormality exists is as follows: a coal powder concentration deviation amount of the two measurement results is obtained by difference calculation of the corrected capacitance-measured coal powder concentration and the sound wave-measured coal powder concentration; a relative capacitance-measured coal powder concentration deviation degree and a relative sound wave-measured coal powder concentration deviation degree are obtained by ratio calculation of the coal powder concentration deviation amount and the corrected capacitance-measured coal powder concentration and the corrected sound wave-measured coal powder concentration respectively; the relative capacitance-measured coal powder concentration deviation degree and the relative sound wave-measured coal powder concentration deviation degree are compared with a pre-set allowable deviation degree threshold value respectively, if any parameter exceeds the allowable deviation degree threshold value, it is determined that measurement abnormality exists, otherwise, it is determined that no measurement abnormality exists; 2. The system according to claim 1, wherein the system is suitable for high concentration of coal powder. a device cleaning module which uses a CCD imaging device to collect the hanging material thickness of the capacitance sensor and the ultrasonic detection device surface in real time, and uses a cleaning device to dynamically execute device cleaning operation. The specific construction way of the capacitance change amount-coal powder concentration relationship model is as follows: A1, the capacitance change amount is defined as an input variable, and the capacitance-measured coal powder concentration is defined as an output variable; A2, an experimental environment simulating high-concentration coal powder conveying is built, a plurality of different coal powder concentration conditions are set, under each condition, a large amount of capacitance change data is collected by using a high-precision capacitance sensor, and a corresponding coal powder concentration true value is accurately obtained by using a weighing method, and an original data set is constructed; A3, the conditions corresponding to the same capacitance change amount are classified, and the coal powder concentration corresponding to each condition is extracted; A4, the coal powder concentration under different conditions corresponding to the same capacitance change amount is subjected to mean value calculation to obtain the coal powder concentration corresponding to each capacitance change amount; 3. The system for on-line measurement of the concentration of coal powder in the air according to claim 1, wherein: A5, the capacitance change amount and the corresponding coal powder concentration are one-to-one corresponding to construct the capacitance change amount-coal powder concentration relationship model. The specific analysis way of the sensor hanging material thickness is as follows: a CCD imaging device is used to collect the capacitance sensor surface image in real time, the time corresponding to the capacitance change amount monitored by the capacitance sensor is obtained, and the capacitance sensor surface image corresponding to the time is extracted as a monitoring capacitance sensor surface image. The electric field distribution of the capacitive sensor is simulated by using an electric field distribution simulation software, a maximum electric field intensity of the capacitive sensor is obtained, a preset ratio is multiplied by the maximum electric field intensity to obtain an electric field intensity division value, and a space region with an electric field intensity greater than the electric field intensity division value is defined as a monitoring key space region; The monitoring key space region is mapped to an inner side surface of the capacitive sensor to obtain a monitoring plane region; A plurality of hanging material thickness monitoring points are obtained by uniformly distributing points on the inner side surface of the capacitive sensor, and a distance between a real-time space position and an initial space position of each hanging material thickness monitoring point is recorded as a hanging material thickness of the hanging material thickness monitoring point; The hanging material thickness monitoring points are divided according to the distribution positions to obtain hanging material thickness monitoring points corresponding to the monitoring key space region and hanging material thickness monitoring points corresponding to other regions; The hanging material thicknesses of the hanging material thickness monitoring points in the monitoring key space region are subjected to mean value calculation to obtain a key region hanging material thickness, and the hanging material thicknesses of the hanging material thickness monitoring points in other regions are subjected to mean value calculation to obtain other region hanging material thicknesses; The key region hanging material thickness and the other region hanging material thickness are fused according to a preset weight to obtain a capacitive sensor hanging material thickness.

4. The system according to claim 3, wherein the system is suitable for high concentration of coal powder. The specific analysis method for correcting the capacitive measurement of the coal powder concentration is as follows: The ambient temperature, humidity and sensor hanging material thickness are extracted, and deviation comparison is respectively performed with the first reference temperature, reference humidity and reference sensor hanging material thickness which are pre-calibrated; A first temperature correction coefficient, a humidity correction coefficient and a hanging material thickness correction coefficient are obtained based on the results of the deviation comparison, and the correction coefficients are multiplied to obtain a capacitive measurement comprehensive correction coefficient; The capacitive measurement coal powder concentration is multiplied by the capacitive measurement comprehensive correction coefficient to obtain a corresponding correction amount, and then the capacitive measurement coal powder concentration is summed to obtain a corrected capacitive measurement coal powder concentration.

5. The system for on-line measurement of the concentration of coal powder in the flue gas according to claim 1, wherein: the system is adapted for use in a high concentration of coal powder. The specific construction method of the sound wave attenuation amount-coal powder concentration relationship model is as follows: B1. In a closed coal powder conveying experimental pipeline, the ambient temperature and the standard value of the coal powder particle size are fixed; B2. By adjusting the powder amount, a uniform distribution of coal powder concentration working condition groups from low to high is generated; B3. After each working condition is stabilized, the sound wave attenuation amount data measured by the ultrasonic device and the true value of the coal powder concentration obtained by the high-precision reference method are synchronously collected to form an original data set; B4. The sound wave attenuation amount is classified and grouped according to the numerical interval, the true values of the concentration in the same sound wave attenuation amount interval under different working conditions are taken as the arithmetic mean values, and a strict mapping relationship table of the sound wave attenuation amount interval and the average value of the coal powder concentration is established; B5. Based on the mapping relationship table, a basic relationship model of one-to-one correspondence between the sound wave attenuation amount input value and the coal powder concentration output value is generated.

6. The on-line measurement system for high concentration coal powder according to claim 4, characterized in that: The specific method for correcting the sound wave measurement of the coal powder concentration is as follows: The ambient temperature and the coal powder particle size are extracted, and deviation comparison is respectively performed with the second reference temperature and the reference coal powder particle size which are pre-calibrated; Based on the results of the deviation comparison, a second temperature correction coefficient and a coal powder particle size correction coefficient are obtained, and the correction coefficients are multiplied to obtain a sound wave measurement comprehensive correction coefficient; The coal dust concentration measured by the sound wave is multiplied by the comprehensive correction coefficient measured by the sound wave to obtain a corresponding correction amount, and then summed with the coal dust concentration measured by the sound wave to obtain a corrected coal dust concentration measured by the sound wave.

7. The system for on-line measurement of the concentration of coal powder in the air according to claim 1, wherein: the system is adapted for use in high concentration of coal powder. The specific manner of outputting the comprehensive coal dust concentration if there is none is as follows: The corrected coal dust concentration measured by the capacitance and the corrected coal dust concentration measured by the sound wave are extracted, and then the comprehensive coal dust concentration is calculated by weighted summation based on the weight factor fitted according to the historical data.

8. The system for on-line measurement of the concentration of coal powder in the air according to claim 1, wherein: the system is adapted for use in high concentration of coal powder. The specific manner of identifying the abnormal measurement method and outputting the comprehensive coal dust concentration is as follows: When it is determined that there is a measurement abnormality, the capacitance measurement operation and the sound wave measurement operation are continuously performed for several times; The capacitance measurement coal dust concentration corresponding to each capacitance measurement operation is calculated to obtain a capacitance method measurement fluctuation index, and the sound wave measurement coal dust concentration corresponding to each sound wave measurement operation is calculated to obtain a sound wave method measurement fluctuation index; The capacitance method measurement fluctuation index and the sound wave method measurement fluctuation index are compared with the pre-set fluctuation index threshold value, if the capacitance method measurement fluctuation index is greater than the fluctuation index threshold value, the abnormal measurement method is identified as the capacitance method, if the sound wave method measurement fluctuation index is greater than the fluctuation index threshold value, the abnormal measurement method is identified as the sound wave method; If it is identified that one of the measurement methods is abnormal, the average coal dust concentration corresponding to each measurement operation of the other measurement method is output as the comprehensive coal dust concentration; If both measurement methods are determined to be abnormal measurement methods, a warning is given and pushed to the administrator for abnormal situation handling.

9. The online coal dust measurement system for high-concentration pulverized coal as described in claim 1, characterized in that: The specific manner of the cleaning operation of the device is as follows: Uniformly distribute points on the inner surface of the capacitance sensor and the probe of the ultrasonic detection device to obtain a plurality of cleaning judgment monitoring points; Real-time acquisition of the hanging material thickness of each cleaning judgment monitoring point, calculation of the average value of each cleaning judgment monitoring point as the average hanging material thickness of the corresponding device, the device including the capacitance sensor and the ultrasonic detection device; Compare the average hanging material thickness of each device with the pre-set cleaning threshold value, and compare the hanging material thickness of each cleaning judgment monitoring point of each device with the pre-set cleaning threshold value; If the average hanging material thickness of a device is greater than the cleaning threshold value, the device cleaning operation is performed on the device; If there is a cleaning judgment monitoring point of a device whose hanging material thickness is greater than the cleaning threshold value, the device cleaning operation is performed on the device.

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