An on-line measuring system and method for air preheater leakage rate based on multi-point oxygen detection

Abstract

The application discloses a kind of based on multiple point oxygen quantity detection's air preheater air leakage rate online measurement system and method, belong to power plant boiler energy-saving optimization technical field.System includes 4 sets of multiple point oxygen quantity measuring device arranged at the inlet and outlet of flue on the two sides of air preheater A, B, and intelligent control and calculation center;Multiple point oxygen quantity measuring device contains high-precision zirconium oxide sensor array, electric purging mechanism and sealing device, signal acquisition and processing unit, and sensor point is determined based on CFD numerical simulation.Method is by synchronously collecting each measuring point oxygen quantity value, obtains cross-sectional representative oxygen quantity value by weighted and arithmetic average comprehensive algorithm, then adopts oxygen quantity balance method to calculate one-side air leakage rate in combination with rotary air preheater empirical correction coefficient, finally weighted average obtains overall air leakage rate and uploads to power plant DCS / SIS system.The application solves the problem that the calculation error of air leakage rate is large and cannot be monitored online in real time due to uneven flow field caused by traditional single-point measurement, with the advantages of high measurement accuracy, strong real-time, high reliability, strong maintenance guidance, can provide accurate data support for air preheater air leakage treatment and boiler operation optimization.

Description

Technical Field

[0001] This invention relates to the field of energy-saving optimization technology for power plant boilers, specifically to an online real-time detection system for the air leakage rate of a rotary air preheater and a corresponding measurement method. Background Technology

[0002] Rotary air preheaters are one of the core auxiliary machines in large coal-fired power plant boilers. Their main function is to preheat the air entering the furnace using the heat from the boiler flue gas, thereby improving boiler combustion efficiency and reducing flue gas heat loss. However, rotary air preheaters commonly suffer from air leakage during operation. Air leakage is a key factor affecting boiler thermal efficiency and operational economy: on the one hand, air leakage directly increases the power consumption of induced draft fans and forced draft fans, leading to an increase in plant power consumption; on the other hand, air leakage increases the excess air coefficient in the flue gas, significantly increasing flue gas heat loss, and in severe cases, it can even limit boiler output due to insufficient air distribution in the furnace. According to industry estimates, for every 1% reduction in air preheater leakage rate, the unit's coal consumption for power generation can be reduced by approximately 0.16 g / kW·h, demonstrating the significant energy-saving benefits of air leakage control.

[0003] Currently, the actual air leakage rate of rotary air preheaters in large thermal power generating units of 300MW and above in China is generally around 10%, with some units even reaching 15%, far exceeding the 5%-8% level abroad. The core bottleneck restricting the refined management of air preheater leakage is the lack of reliable and accurate online leakage rate measurement methods. In existing technologies, air preheater leakage rate measurement mostly adopts single-point or small-point oxygen measurement methods, combined with the traditional oxygen balance method to calculate the leakage rate. However, this method has obvious defects: the flow field distribution inside the flue is uneven, and the location representativeness of single-point or small-point measurement is poor, resulting in the collected oxygen signal not being able to truly reflect the average oxygen concentration of the flue section, ultimately causing a large error in the leakage rate calculation. At the same time, traditional measurements are mostly offline manual tests, which cannot achieve real-time continuous monitoring. The test results are lagging and cannot provide real-time guidance for boiler operation adjustment and air preheater leakage maintenance.

[0004] Furthermore, existing oxygen measurement sensors are prone to probe blockage due to dust and impurities in the flue gas, leading to measurement errors and high maintenance costs. Traditional measurement methods can only output the overall air preheater leakage rate, failing to distinguish between leakage differences on sides A and B, making it difficult to accurately locate specific areas with excessive leakage and resulting in poor targeted maintenance. Therefore, developing an online system and method that can measure air preheater leakage rate in real time, accurately, and reliably has become an urgent need in the field of energy-saving optimization for power plant boilers. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing air preheater leakage rate measurement technologies, such as large measurement errors, lack of online real-time monitoring, low sensor reliability, and poor maintenance guidance. It provides an online air preheater leakage rate measurement system and method based on multi-point gridded oxygen detection and CFD flow field modeling, which can achieve continuous and accurate measurement of air preheater leakage rate at the second level, and can distinguish between single-sided leakage. This provides a reliable and accurate real-time data foundation for leakage control and boiler operation optimization.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: I. Online Measurement System for Air Preheater Leakage Rate Based on Multi-Point Oxygen Detection The measurement system of this invention includes four sets of multi-point oxygen measurement devices and an intelligent control and computing center. The structure and function of each component are as follows: 1. Multi-point oxygen measurement device: A total of 4 sets, arranged one-to-one at the flue gas inlet and outlet positions of the flue gas ducts on both sides of air preheater A and B, to achieve oxygen signal acquisition at 4 key measurement sections. Each set of devices contains three core units: - High-precision zirconia sensor array: Composed of 5-6 independent zirconia sensors, the installation position of the sensors on the flue section is determined based on the results of computational fluid dynamics (CFD) numerical simulation. A uniform and representative measurement grid is formed according to the flue size and flow field distribution to ensure that the measurement points can reflect the average oxygen concentration and flow field characteristics of the section to the greatest extent. The weight coefficient of the sensor is determined by the velocity distribution of the flue section in the CFD flow field simulation. The sensor weight is higher in areas with high flow velocity, which improves the representativeness of signal acquisition. - Electric purging mechanism and sealing device: Composed of solenoid valve, controller, purging device and sealing component. The system can automatically start the purging program according to preset control command or manual command to clean the dust and impurities on the sensor probe in time and prevent probe blockage. At the same time, the sealing component can reduce the corrosion of the sensor by flue gas impurities and improve the measurement reliability. - Signal Acquisition and Processing Unit: Integrated into the field controller, it is responsible for acquiring the original oxygen quantity analog signals from each zirconia sensor in real time, converting them into digital signals, and then transmitting them to the intelligent control and computing center through industrial communication protocols to complete the initial processing and transmission of the signals. 2. Intelligent Control and Computing Center: Located in the intelligent control cabinet within the power plant control room, this is the core control and computing unit of the entire system. It includes a comprehensive controller, a signal processing unit, and a signal remote transmission module. Its built-in dedicated software platform integrates an operating system, a control logic configuration platform, a real-time database, a signal analysis module, and a leakage rate calculation engine, achieving three main functions: First, receiving and storing oxygen signals from various measuring points, and performing signal filtering, noise reduction, and other analysis and processing; second, using the built-in leakage rate calculation engine, performing real-time calculations of representative oxygen values ​​at cross-sections, single-sided leakage rate, and overall leakage rate according to preset algorithms; and third, uploading leakage rate data and measuring point oxygen data to the power plant's DCS (Distributed Control System) or SIS (System-in-Service) via the signal remote transmission module, while also supporting real-time display on-site.

[0007] II. Online Measurement Method for Air Preheater Leakage Rate Based on the Above System The measurement method of this invention is based on the above-mentioned multi-point oxygen detection system. It completes the online real-time measurement of the air preheater leakage rate through four steps: synchronous acquisition, cross-sectional oxygen calculation, single-sided air leakage rate calculation, and overall air leakage rate output. The specific steps are as follows: 1. Step S1: Data Synchronization Acquisition The intelligent control and computing center sends a synchronous acquisition command to control four sets of multi-point oxygen measurement devices to start working simultaneously. The devices synchronously acquire real-time oxygen values ​​from all zirconium oxide sensor measuring points in four measuring sections at the inlet and outlet of the flue on both sides of the air preheater (A and B), ensuring the time consistency of data from each measuring point and eliminating calculation errors caused by asynchronous acquisition. The acquired raw oxygen values ​​are transmitted in real time to the real-time database of the intelligent control and computing center for storage.

[0008] 2. Step S2: Calculation of representative oxygen content of the cross section The four measurement sections were processed separately. For the oxygen content values ​​at 5-6 measurement points in each section, a combined algorithm of weighted average and arithmetic average was used to calculate the final output oxygen content value Op that truly reflects the average oxygen concentration for that section. The calculation formula is as follows: Op = Oj + k * Os in: - Oj is the weighted average of oxygen values ​​at all measuring points on this cross section. The weighting coefficients are strictly determined based on the velocity distribution of the flue section obtained from the CFD flow field simulation. The weighting coefficients are higher for measuring points in areas with high flow velocity to ensure that the weighted average matches the actual flow field. - Os is the arithmetic mean of the oxygen content values ​​at all measuring points on this cross section, used as an auxiliary correction value to compensate for the insufficient adaptability of the weighted average to sudden changes in the local flow field; -k is a comprehensive correction coefficient, the value of which is determined based on CFD flow field simulation results and manual test calibration data using the field grid method, and is continuously optimized in combination with actual power plant operation data. It is used to compensate for the deviation between the numerical simulation model and the actual flue flow field, and to ensure that the Op value can accurately represent the true average oxygen concentration of the cross section.

[0009] 3. Step S3: Calculation of air leakage rate in a single flue Based on the Op values ​​of each section obtained in step S2, the classical oxygen balance method is used, and an empirical correction coefficient is introduced in combination with the operating characteristics of the rotary air preheater. The single-sided air leakage rates LA and LB of the flues on both sides of air preheater A and B are calculated respectively. The calculation formula is as follows: Lx = (O2_out' - O2_in') / (21 - O2_in') * 90% in: - Lx represents the single-sided air leakage rate, indicating LA (side A) or LB (side B), in percentage terms. - O2_out' represents the oxygen content Op_out at the flue gas outlet section of the corresponding side air preheater, expressed as a volume percentage (%). - O2_in' represents the oxygen content Op_in at the air inlet section of the corresponding side air preheater, expressed as a volume percentage (%). - 21 represents the standard oxygen content in ambient air, expressed as a percentage (%). - 90% is an empirical correction factor for rotary air preheaters, used to compensate for indirect air leakage factors such as carry-over leakage during the operation of rotary air preheaters, and to improve the accuracy of air leakage rate calculation.

[0010] 4. Step S4: Overall air leakage rate calculation and output The intelligent control and computing center selects an appropriate calculation method to obtain the overall air leakage rate L of the air preheater based on the actual operating conditions of both sides A and B: when the flue gas flow rates on both sides are basically the same, the arithmetic average of LA and LB is performed; when there is a significant difference in the flue gas flow rates on both sides, a weighted average is performed with the flue gas flow rates on both sides as the weights, and the side with the larger flow rate is given a higher weight, so as to ensure that the overall air leakage rate matches the actual operating state of the air preheater.

[0011] After the calculation is completed, the system will display the comprehensive air leakage rate L, the single-sided air leakage rate LA and LB, and the real-time oxygen data of each key measuring point on the on-site intelligent control cabinet in real time. At the same time, all data will be uploaded to the power plant's DCS or SIS system through the signal transmission module to realize remote monitoring and data retrieval in the power plant's central control room.

[0012] Compared with the prior art, the advantages and positive effects of the present invention are as follows: High measurement accuracy: The oxygen content measurement adopts a multi-point gridded system consisting of 5-6 sensors, and the sensor layout and weighting coefficients are determined by CFD numerical simulation, which avoids the problem of poor positional representativeness of single-point measurement. At the same time, the cross-sectional oxygen content value is calculated by the Oj+kOs comprehensive algorithm, and the correction coefficient is optimized by on-site calibration, which greatly reduces the measurement error caused by the uneven flow field in the flue, making the air leakage rate calculation result closer to the true value.

[0013] Real-time online monitoring: The system achieves fully automatic operation, and can complete the synchronous acquisition of oxygen signals within seconds and the real-time calculation of air leakage rate. It completely changes the lag of traditional offline manual testing and provides real-time data support for boiler operation adjustment and handling of sudden air preheater leakage problems.

[0014] The equipment is highly reliable and has low maintenance costs: The sensor is equipped with an electric purging mechanism and a sealing device, which can automatically purge to prevent probe blockage, reduce the corrosion of the sensor by flue gas impurities, reduce the failure rate of the sensor and the frequency of manual maintenance, and significantly save maintenance costs.

[0015] Highly instructive for maintenance: The system can not only output the overall leakage rate of the air preheater, but also calculate and display the single-sided leakage rates LA and LB on both sides A and B respectively. It can accurately locate the specific side with excessive leakage, and can even combine the oxygen data of the measuring points to further locate the leakage area in the flue. This provides a direct and accurate basis for targeted maintenance such as fan-shaped plate sealing and radial sealing, improving the efficiency and effectiveness of leakage control.

[0016] Highly compatible and easy to promote: The system's signal transmission module can be directly connected to the existing DCS or SIS system of the power plant without the need for large-scale modification of the original control system of the power plant. The installation and commissioning are easy and suitable for rotary air preheaters of various large coal-fired power plants of 300MW and above in China. It has broad engineering promotion value. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the overall structure of the online air preheater leakage rate measurement system based on multi-point oxygen detection of the present invention, showing the arrangement of four sets of multi-point oxygen measurement devices in the flues on both sides of the air preheater A and B, as well as their connection with the intelligent control and computing center and the power plant DCS / SIS system. In the above figures, 1-Air preheater A-side flue inlet; 2-Air preheater A-side flue outlet; 3-Air preheater B-side flue inlet; 4-Air preheater B-side flue outlet; 5-Multi-point oxygen measurement device; 6-High-precision zirconia sensor array; 7-Electric purging mechanism and sealing device; 8-Signal acquisition and processing unit; 9-Intelligent control and computing center; 10-Power plant DCS / SIS system. Detailed Implementation

[0020] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0021] Numerous specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways than those described herein, and therefore the invention is not limited to the specific embodiments disclosed in the following specification.

[0022] Example 1: The online air preheater leakage rate measurement system and method based on multi-point oxygen detection of the present invention is applicable to the online accurate monitoring of the leakage rate of rotary air preheaters in large coal-fired power plant boilers. The following detailed description, using a field implementation case of a 600MW subcritical coal-fired unit boiler (equipped with two rotary air preheaters of model Rong-32000 / 31500 / 17500, with independent operation on sides A and B), further illustrates the invention.

[0023] In this embodiment, the boiler has a rated evaporation capacity of 2000t / h, an air preheater flue gas inlet temperature of 380℃ and an outlet temperature of 130℃, an air side inlet temperature of 20℃ and an outlet temperature of 310℃, a single air preheater flue gas flow rate of approximately 1800000Nm³ / h, and a design air leakage rate of ≤8%.

[0024] I. System Hardware Deployment and Installation (a) On-site installation of multi-point oxygen measurement device Strictly following the layout requirements of the four sets of multi-point oxygen measurement devices in claim 1, precise installation is carried out at the inlet and outlet positions of the flue gas ducts on both sides of the air preheater A and B, as detailed below: 1. Determine the installation location ◦ The first set of equipment is located in the flue gas inlet duct on side A of the air preheater (cross-sectional dimensions 8m×6m, with the central axis 3.5m from the air preheater shell) and 1.5m from the upstream bend to ensure a stable flow field; ◦ The second unit is located in the air inlet flue on side A of the air preheater (cross-sectional dimensions 6m×5m), and is installed using a flange type for easy maintenance. ◦ The third set of equipment: is arranged in the flue gas inlet duct on the B side of the air preheater, symmetrically arranged with the A side; ◦ The fourth unit is located in the air inlet flue on the B side of the air preheater, and its parameters are consistent with those of the air inlet unit on the A side.

[0025] 2. Equipment assembly and fixing Each multi-point oxygen measurement device 5 integrates a high-precision zirconia sensor array 6, an electric purging mechanism and sealing device 7, and a signal acquisition and processing unit 8. Integrated debugging is completed before installation. ◦ Sensor array installation: Based on the CFD numerical simulation results in the background technology, six high-precision zirconia sensors (model: ZY-OD600, range 0-25%O2, accuracy ±0.1%, temperature resistance ≤600℃) are arranged in each measurement section, using a 3×2 matrix layout. The weighting coefficient of the four sensors (high flow velocity) in the central area of ​​the flue is set to 0.25, and the weighting coefficient of the two sensors (low flow velocity) in the edge area is set to 0.15. The sensor probes are inserted into the flue to a depth of 1.2m to ensure coverage of the main flow area. ◦Purge mechanism installation: The electric purging mechanism 7 is equipped with a solenoid valve (pressure rating 1.0MPa), compressed air pipeline and sealing components. The purging pressure is set to 0.6MPa, and the purging cycle is 30min / cycle by default. It can be adjusted according to the dust concentration on site through the intelligent control center. The sealing components are made of high temperature resistant fluororubber material (temperature resistance ≤450℃) to prevent air leakage from the flue from affecting the measurement. • Signal processing unit installation: It integrates an analog acquisition module (AI) and a digital output module (DO), supports the Modbus-RTU industrial communication protocol, and is installed in an explosion-proof junction box near the sensor to reduce signal transmission attenuation.

[0026] (II) Construction of Intelligent Control and Computing Center Based on the functional requirements of the intelligent control and computing center in claim 1, an intelligent control cabinet (dimensions: 800mm×600mm×2200mm) is independently built in the power plant boiler control room, with the following specific configuration: 3. Core Hardware Configuration ◦ Integrated controller: adopts Siemens S7-1500 PLC (model: 1511-1 PN), with a processing speed of ≥100ms / 1000 points, supports multi-task parallel processing, and meets the requirements of synchronous data acquisition and real-time calculation of air leakage rate of 4 sets of measuring devices; ◦ Signal processing unit: Equipped with an ARM Cortex-A72 processor and built-in filtering algorithm (low-pass filtering + singular value removal), which can effectively eliminate signal noise caused by flue vibration and electromagnetic interference; ◦ Remote transmission module: The 4G industrial remote transmission module (model: USR-G806) is selected, which supports TCP / IP and MQTT protocols to achieve seamless integration with the power plant DCS system (model: Simens S7-400).

[0027] 4. Software platform deployment Built-in dedicated software platform, integrating four major functional modules: Operating system: Windows Embedded Standard 2019, ensuring system stability; ◦ Real-time database: Using WinCC 7.5, data storage frequency ≥1Hz, capable of storing more than 1 year of historical operation data; ◦ Leakage rate calculation engine: Built-in cross-sectional oxygen content calculation algorithm (Op=Oj+k×Os) and leakage rate calculation formula as defined in claims 2 and 3, supporting real-time parameter configuration; ◦ Human-computer interaction interface: Equipped with a 15.6-inch touch screen, supporting real-time data display, historical curve query, parameter modification and fault alarm.

[0028] II. System Calibration and Correction Coefficient Optimization In light of the problem of "uniform flow field leading to measurement error" in the background art, the requirements for optimizing the correction coefficient in claims 2 and 4 are strictly implemented, and the specific steps are as follows: 5. Initial calibration data acquisition After the system was installed, the four measurement sections were manually calibrated using the grid method: 10 temporary measuring points were set up at each section, and the oxygen values ​​at each point were collected using a portable oxygen analyzer (accuracy ±0.05%). The actual average oxygen concentration of the section was calculated and used as the baseline data.

[0029] 6. Initial setting of correction coefficient Based on the CFD flow field simulation results and industry experience, the initial comprehensive correction coefficient k=0.3 was set, and the weight coefficients were allocated according to the principle of "high velocity areas have high weight" in the background technology.

[0030] 7. Long-term optimization and adjustment The system underwent a 72-hour trial run, continuously collecting real-time operational data and comparing the real-time calculated cross-sectional oxygen content (Op) with the measured values ​​obtained using the mesh method. ◦ When the error is greater than 0.3%, gradually adjust the value of k by 0.02 each time until the error is less than or equal to 0.2%; In this embodiment, after 72 hours of trial operation, the k value was finally optimized to 0.28. At this time, the calculation error of the entrance section Op on side A was 0.12%, and the error of the entrance section on side B was 0.15%, which meets the industry's high-precision measurement requirements.

[0031] 8. Periodic calibration mechanism Manual calibration is performed every 3 months, and the weighting coefficients are adjusted according to the on-site operating conditions to ensure the long-term measurement accuracy of the system.

[0032] III. Implementation Process of Online Air Leakage Rate Measurement Strictly following the measurement steps S1-S4 in claim 3, and considering the actual operating conditions of the 600MW unit in this embodiment, the real-time measurement of the air preheater leakage rate was completed. The specific operation is as follows: (a) Step S1: Data Synchronization Acquisition The intelligent control and computing center 9 sends a synchronous acquisition command, controlling four sets of multi-point oxygen measurement devices 5 to start working simultaneously via the Profibus-DP protocol, with the acquisition frequency set to 1 time / second. 9. Taking side A as an example, the real-time oxygen content values ​​of 6 sensors at the flue gas inlet on side A are collected simultaneously. In this embodiment, the data collected at a certain moment are: 5.2%, 5.3%, 5.5%, 5.2%, 5.1%, and 5.3%. 10. Simultaneously collect oxygen levels from six sensors at the air inlet on side A: 20.8%, 20.9%, 21.0%, 20.7%, 20.8%, and 20.9%. 11. Simultaneously collect 6 sets of oxygen values ​​from the flue gas inlet and air inlet on side B to ensure that all data timestamps are consistent and to eliminate calculation errors caused by time deviations; 12. The collected raw data is transmitted in real time to the real-time database of the intelligent control center for storage and preliminary filtering.

[0033] (II) Step S2: Calculation of representative oxygen content of cross section For the four measurement sections, the Op value is calculated using the comprehensive algorithm of Oj+k×Os in claim 2, taking the flue gas inlet section on side A as an example: 13. Calculate the weighted average value Oj: Oj = (5.2 × 0.25 + 5.3 × 0.25 + 5.5 × 0.25 + 5.2 × 0.25 + 5.1 × 0.15 + 5.3 × 0.15) = 6.86%; 14. Calculate the arithmetic mean Os: Os = (5.2 + 5.3 + 5.5 + 5.2 + 5.1 + 5.3) / 6 = 5.27%; 15. Substituting the optimized k=0.28, calculate Op_in: Op_in=Oj+k×Os=6.86 + 0.28×5.27=8.34%; 16. Similarly, the calculated values ​​are: Op_out = 32.94% for air inlet on side A, Op_in = 8.49% for flue gas inlet on side B, and Op_out = 33.10% for air inlet on side B.

[0034] (III) Step S3: Calculation of air leakage rate of one side flue Using the formula in claim 3 (oxygen balance method + 90% empirical correction factor), calculate the air leakage rates on both sides A and B respectively: 17. Calculation of air leakage rate LA on side A: LA = (Op_out - Op_in) / (21 - Op_in) × 90% = (32.94 - 8.34) / (21 -8.34) × 90% = 1.75%; 18. Calculation of air leakage rate (LB) on side B: LB = (33.10 - 8.49) / (21 - 8.49) × 90% = 1.77%.

[0035] (iv) Step S4: Calculation and output of overall air leakage rate In accordance with the principle of "flow matching weighting" in claim 5, the flow deviation of flue gas on both sides A and B in this embodiment is ≤3%, and the arithmetic mean is used to calculate the overall air leakage rate: 19. Calculation of overall air leakage rate L: L = (LA + LB) / 2 = (1.75% + 1.77%) / 2 = 1.76%; 20. Data Output: The intelligent control center uploads real-time oxygen data from L, LA, LB, and each measuring point to the power plant's DCS system via a remote transmission module. Simultaneously, the data is displayed in real-time on a touchscreen at the site. The display interface includes: ◦ Real-time air leakage rate (rounded to two decimal places); ◦Oxygen trend curves at 4 cross sections (last hour); ◦ Sensor operating status (normal / fault) and purge countdown; ◦ Historical data query entry (supports filtering by time and side).

[0036] IV. System Operation Performance Verification (a) Accuracy Verification The results of simultaneous measurement using both traditional single-point measurement methods and the method of this invention are compared below: (ii) Reliability verification The system operated continuously for 30 days, during which the sensor purging mechanism worked automatically without any probe blockage. The data acquisition success rate was ≥99.9%, and there was no packet loss during signal transmission, meeting the long-term stable operation requirements of the power station.

[0037] (III) Inspection and maintenance guidance verification During operation, the system detected that the air leakage rate on side B suddenly rose to 2.5%, which was 0.7 percentage points higher than that on side A. Based on the data, the maintenance personnel located the wear of the radial sealing sheet on side B. After targeted repairs, the air leakage rate on side B dropped to 1.78%, and the overall air leakage rate was optimized to 1.75%, achieving the goal of "accurately locating the air leakage location and improving maintenance efficiency" in the background technology.

[0038] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An online measurement system for air preheater leakage rate based on multi-point oxygen detection, characterized in that, include: Four sets of multi-point oxygen measurement devices and an intelligent control and computing center; The four sets of multi-point oxygen measurement devices are respectively arranged at the flue gas inlet and outlet positions of the flue gas ducts on both sides of air preheater A and B; each set of multi-point oxygen measurement devices includes a high-precision zirconia sensor array, an electric purging mechanism and sealing device, and a signal acquisition and processing unit. The high-precision zirconia sensor array contains 5-6 independent zirconia sensors. The sensor placement on the flue section is determined based on computational fluid dynamics (CFD) numerical simulation results, forming a measurement grid. The electric purging mechanism and sealing device include a solenoid valve, a controller, a purging device and a sealing assembly, which can automatically purge according to control commands to prevent the sensor probe from becoming clogged; The signal acquisition and processing unit is installed in the field controller and is used to acquire the raw oxygen signals of each zirconium oxide sensor in real time and transmit them to the intelligent control and computing center. The intelligent control and computing center is located in the intelligent control cabinet and includes an integrated controller, a signal processing unit, and a signal transmission module. Its built-in software platform integrates an operating system, a control logic configuration platform, a real-time database, a signal analysis module, and a leakage rate calculation engine to complete oxygen signal analysis, leakage rate calculation, and data uploading.

2. The system according to claim 1, characterized in that, The weighting coefficients of the high-precision zirconia sensor array are determined based on the velocity distribution of the flue section obtained from CFD flow field simulation, with higher sensor weighting coefficients in areas with higher flow velocities.

3. A method for online measurement of air preheater leakage rate based on the system described in any one of claims 1-2, characterized in that, Includes the following steps: S1. Data Synchronous Acquisition: Controls 4 sets of multi-point oxygen measurement devices to work synchronously, collecting real-time oxygen values ​​at all measuring points of the 4 measuring sections at the inlet and outlet of the flue on both sides of the air preheater A and B. S2. Calculation of representative oxygen content at a cross section: The oxygen content values ​​at 5-6 measuring points of each measuring cross section are comprehensively calculated to obtain the final output oxygen content value Op for that cross section. The calculation formula is: Op = Oj + k * Os; where Oj is the weighted average of the oxygen content values ​​at all measuring points of that cross section, and the weighting coefficient is determined by the velocity distribution simulated by the CFD flow field; Os is the arithmetic mean of the oxygen content values ​​at all measuring points of that cross section; k is the comprehensive correction coefficient, which is determined and optimized based on the flow field simulation results and the manual test calibration data of the field grid method. S3. Calculation of single-sided flue gas leakage rate: The leakage rates LA and LB of flues A and B are calculated separately using the oxygen balance method. The calculation formula is: Lx = (O2_out' - O2_in') / (21 - O2_in') * 90%; where Lx is LA or LB, i.e., single-sided leakage rate, in %; O2_out' is the oxygen content Op_out at the flue gas outlet section of the air preheater, in volume percentage; O2_in' is the oxygen content Op_in at the air inlet section of the air preheater, in volume percentage; 21 is the oxygen content in the ambient air, in %; and 90% is an empirical correction coefficient for rotary air preheaters. S4. Overall air leakage rate calculation and output: The air leakage rates LA and LB on both sides A and B are arithmetically averaged, or weighted averaged according to the flue gas flow rates on both sides, to obtain the overall air leakage rate L of the entire air preheater; The overall air leakage rate L, the single-sided air leakage rates LA and LB, and the oxygen data of each key measuring point are displayed in real time and uploaded to the power plant DCS or SIS system through the signal remote transmission module.

4. The method according to claim 3, characterized in that, The optimization process of the comprehensive correction coefficient k in step S2 involves combining actual on-site operating data to continuously correct the deviation between the model and the actual flue gas flow field, ensuring that the Op value matches the true average oxygen concentration of the cross section.

5. The method according to claim 3, characterized in that, In step S4, when there is a significant difference in flue gas flow rate between sides A and B, the flue gas flow rate is used as the weight to calculate the comprehensive air leakage rate L by weighted average. The side with larger flow rate has a higher weight coefficient.

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