A water vapor quality monitoring and early warning device and method based on multi-parameter fusion

Abstract

The application provides a water vapor quality monitoring and early warning device and method based on multi-parameter fusion, comprising a data acquisition unit, a data processing unit, a fusion analysis unit and an early warning output unit; the data acquisition unit comprises an online acquisition mechanism and an offline detection mechanism; the data processing unit comprises a data preprocessing module and a data verification module, the data preprocessing module is used for filtering and denoising and outlier rejection processing of the multi-dimensional parameter data, and the data verification module is used for validity verification and sensor state diagnosis of the processed data; the fusion analysis unit comprises a dynamic weight distribution algorithm-based weighted fusion processing of the multi-dimensional parameter data to generate a water vapor quality comprehensive index CQI. It can generate a comprehensive quality index by dynamically weighting and fusing multiple water vapor indexes, realize global evaluation and accurate grading early warning of water vapor working conditions.

Description

Technical Field

[0001] This invention relates to a multi-source collaborative control device and method, and in particular to a water vapor quality monitoring and early warning device and method based on multi-parameter fusion. Background Technology

[0002] In industrial sites such as thermal power plants, nuclear power plants, and chemical plants, the quality of the steam-water system directly affects the safe and economical operation of core equipment such as boilers and turbines. Excessive impurities in the steam-water system can lead to corrosion, scaling, and salt buildup in thermal equipment, potentially causing serious accidents such as pipe ruptures. Traditional online monitoring systems only set independent alarm thresholds for single chemical indicators (such as pH, conductivity, silicate, sodium ions, etc.). This single-parameter alarm method is highly susceptible to false alarms due to instantaneous sensor disturbances or fluctuations in local operating conditions. More importantly, it ignores the synergistic effect of multiple impurities on the equipment, failing to characterize the overall trend of steam-water quality deterioration. Therefore, there is an urgent need for a device that can integrate multi-source parameters, provide comprehensive diagnosis, and offer tiered early warning systems to improve the accuracy and foresight of early warnings. Summary of the Invention

[0003] The purpose of this invention is to provide a water vapor quality monitoring and early warning device and method based on multi-parameter fusion. It can generate a comprehensive quality index by dynamically weighting and fusing multiple water vapor indicators, thereby achieving a global assessment and precise graded early warning of water vapor conditions.

[0004] The technical solution of the present invention: a water vapor quality monitoring and early warning device based on multi-parameter fusion, comprising a data acquisition unit, a data processing unit, a fusion analysis unit, and an early warning output unit;

[0005] The data acquisition unit includes an online acquisition mechanism and an offline detection mechanism;

[0006] The data processing unit includes a data preprocessing module and a data verification module. The data preprocessing module is used to filter and denoise the multidimensional parameter data and remove outliers. The data verification module is used to verify the validity of the processed data and diagnose the sensor status.

[0007] The fusion analysis unit includes weighted fusion processing of the multidimensional parameter data based on a dynamic weight allocation algorithm to generate a comprehensive water vapor quality index (CQI).

[0008] The early warning output unit includes a graded early warning module and an early warning output module. The graded early warning module is used to determine the early warning level based on the comprehensive water vapor quality index and the preset multi-level early warning threshold. The early warning output module is used to output early warning signals and corresponding handling suggestions.

[0009] In the aforementioned water and steam quality monitoring and early warning device based on multi-parameter fusion, the online acquisition mechanism includes an online silicon meter installed at the mixed bed outlet, an online sodium meter installed at the main steam header of the boiler, and pH meters, conductivity meters, and dissolved oxygen analyzers distributed at various points in the water and steam system. These instruments can capture key chemical parameters affecting water and steam quality in real time.

[0010] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, the offline detection mechanism includes a laboratory benchtop silicon dioxide meter, a laboratory benchtop sodium dioxide meter, as well as a pH meter, conductivity meter, and dissolved oxygen analyzer, used to detect sampled water and to periodically calibrate and verify online monitoring data for anomalies. Through regular comparison of offline data, drift of online sensors can be effectively corrected, ensuring the long-term reliability of the basic data source.

[0011] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, the data processing unit includes: a filtering and denoising subunit, which uses a wavelet threshold denoising algorithm to filter the original monitoring signal and remove high-frequency noise interference; and a dimensional normalization subunit, which uses the Min-Max normalization method to convert monitoring data of different dimensions to a unified dimensional range, laying a mathematical foundation for subsequent fusion calculations.

[0012] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, the graded early warning module includes an attention threshold. Abnormal threshold and danger threshold ,and < < And compare the comprehensive water vapor quality index with the multi-level threshold: when CQI < When, it is judged as a normal state; when ≤ CQI < When this occurs, a warning level alert is generated, prompting operators to strengthen monitoring; when ≤ CQI < When an anomaly level warning is generated, immediate adjustment measures must be taken; when CQI ≥ When this occurs, a hazard level warning is generated, indicating that the equipment safety is seriously threatened and an emergency shutdown or the highest level of response measures are required.

[0013] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, the early warning output module is used to output the generated early warning information through at least one of the following methods: audible and visual alarm, SMS push, email notification, and system interface pop-up window, and simultaneously record the early warning log for easy post-event traceability and analysis.

[0014] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, to ensure the stability and accuracy of instrument measurements, the online acquisition mechanism includes a pretreatment device located in front of the online silicon meter, online sodium meter, pH meter, conductivity meter, and dissolved oxygen analyzer. The pretreatment device includes a sampling tube with a control valve. Behind the sampling tube, a coarse filter, a heat exchanger, a fine filter, and a collection box are sequentially arranged. A detection port is located on one side of the collection box. The cold water inlet of the heat exchanger is connected to an external water source, and a multi-way valve is located at the cold water outlet of the heat exchanger, connecting to the external water source, the coarse filter, and the fine filter, respectively. This design enables constant temperature, constant flow, and purification of the sample water, and also has a backwashing function.

[0015] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, the coarse filter includes a housing, within which a coarse filter plate is disposed. The coarse filter plate is a conical filter plate with its pointed corners pointing upwards. A rotating shaft is disposed on the upper side of the coarse filter plate, passing through the housing and connected to a motor fixed to the upper side of the housing by a bracket. A scraper is disposed at the lower end of the rotating shaft, which is in contact with the coarse filter plate. A first drain port is disposed on the upper side wall of the housing, and a first water inlet is disposed on the lower side wall of the housing, which is connected to a multi-way valve. The conical filter plate increases the filtration area, and the rotating scraper can automatically clean and trap impurities, preventing clogging.

[0016] In the aforementioned water vapor quality monitoring and early warning device based on multi-parameter fusion, the fine filter includes a body, a fine filter plate inside the body, an ultrasonic vibrating rod on one side of the fine filter plate, a pressure piston on one side of the ultrasonic vibrating rod, a second drain port on the lower side wall of the body, and a second water inlet connected to a multi-way valve on the lower side wall of the body. The ultrasonic vibrating rod can effectively peel off and remove tiny impurities on the fine filter plate through high-frequency vibration, achieving deep self-cleaning.

[0017] This invention also provides a water vapor quality monitoring and early warning method based on multi-parameter fusion, comprising the following steps:

[0018] S1. Acquire multi-dimensional parameter data of the water vapor system in real time through online acquisition agencies, and regularly verify the data through offline testing agencies to ensure data accuracy;

[0019] S2. Preprocess and validate the multidimensional parameter data to generate a standardized valid dataset;

[0020] S3. Based on the dynamic weight allocation algorithm, the parameters in the effective dataset are weighted and fused to generate a comprehensive water vapor quality index for comprehensively characterizing water vapor quality.

[0021] S4. Compare the comprehensive water vapor quality index with the preset multi-level early warning threshold, determine the early warning level, and output the corresponding early warning signal and handling suggestions accordingly.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] 1. This application overcomes the one-sidedness of single-parameter alarms by integrating multiple parameters for comprehensive evaluation. By constructing a comprehensive water vapor quality index (CQI), it integrates multiple parameters into a comprehensive index, evaluates the degree of water vapor quality degradation from the perspective of the whole system, greatly improves the scientificity and accuracy of the assessment, and offline testing agencies can verify the data collected by online agencies, resulting in better reliability.

[0024] 2. This application introduces a dynamic weight compensation mechanism. When a certain indicator deviates sharply, its weight automatically increases, enabling the CQI to reflect the abnormal change in a timely and significant manner. Compared with a simple weighting method with fixed weights, this algorithm has a faster response speed and higher sensitivity to sudden water quality deterioration, which is conducive to the early detection of potential hazards and provides valuable response time for operators.

[0025] 3. This application incorporates a pretreatment device with automatic cleaning function at the front end of the online instrument. The coarse filter uses a conical filter plate in conjunction with a rotating scraper to automatically remove large particles of impurities; the fine filter uses an ultrasonic vibrating rod to remove tiny deposits through high-frequency vibration. Furthermore, backwashing of the filter can be achieved by switching the water path using a multi-way valve. These designs effectively prevent clogging of the sampling pipeline and filtration device, ensuring a continuous and stable supply of sample water, and significantly reducing the frequency of manual maintenance and instrument failure rate. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the present invention;

[0027] Figure 2 This is a schematic diagram of the pretreatment device of the present invention;

[0028] Figure 3 This is a schematic diagram of the structure of the coarse filter of the present invention;

[0029] Figure 4 This is a schematic diagram of the structure of the fine filter of the present invention.

[0030] The labels in the attached diagram are as follows: 1-Control valve, 2-Sampling tube, 3-Coarse filter, 4-Heat exchanger, 5-Fine filter, 6-Collection box, 7-Detection port, 8-Multi-way valve, 9-Shell, 10-Coarse filter plate, 11-Rotating shaft, 12-Support, 13-Motor, 14-Scraper, 15-First drain outlet, 16-First inlet, 17-First inlet, 18-Fine filter plate, 19-Ultrasonic vibrator, 20-Second drain outlet, 21-Second inlet, 22-Pressure piston. Detailed Implementation

[0031] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0032] Example. A water vapor quality monitoring and early warning device and method based on multi-parameter fusion, comprising as follows: Figure 1-4 As shown, it includes a data acquisition unit, a data processing unit, a fusion analysis unit, and an early warning output unit;

[0033] The data acquisition unit includes an online acquisition mechanism and an offline detection mechanism. The online acquisition mechanism includes an online silicon meter installed at the mixed bed outlet, an online sodium meter installed at the main steam header of the boiler, and pH meters, conductivity meters, and dissolved oxygen analyzers distributed at various points in the water-steam system.

[0034] The offline testing equipment includes a laboratory benchtop silicon water meter, a laboratory benchtop sodium water meter, as well as a pH meter, conductivity meter and dissolved oxygen analyzer, used to test the sampled water and to perform periodic calibration and anomaly verification of the online monitoring data;

[0035] The data processing unit includes a data preprocessing module and a data verification module. The data preprocessing module is used to filter and denoise the multidimensional parameter data and remove outliers. The data verification module is used to verify the validity of the processed data and diagnose the sensor status. The data processing unit includes:

[0036] The filtering and denoising subunit uses a wavelet threshold denoising algorithm to filter the original monitoring signal and remove high-frequency noise interference.

[0037] The dimensional normalization sub-unit uses the Min-Max normalization method to convert monitoring data of different dimensions to a unified dimensional range;

[0038] The fusion analysis unit includes weighted fusion processing of the multidimensional parameter data based on a dynamic weight allocation algorithm to generate a comprehensive water vapor quality index (CQI). This invention employs a dynamic weight allocation algorithm, dynamically adjusting the contribution weight of each indicator to the comprehensive index based on its real-time deviation, thereby more sensitively capturing signs of water quality deterioration. Let the normalized effective dataset of the key parameters participating in the evaluation be... This includes normalized pH, conductivity, silicate ions, sodium ions, dissolved oxygen, etc. Each parameter has an ideal target value. The formula for calculating CQI is:

[0039]

[0040] in: Let be the static base weight of the i-th parameter, and satisfy . , This refers to the dynamic weight compensation amount. When a certain indicator deteriorates sharply, its dynamic weight compensation amount... By setting corresponding adjustment coefficients, the overall CQI index will be significantly increased, thereby achieving a rapid response. Let be the single-item quality function for the i-th parameter, used to map the parameter value to a degradation score within the interval [0,1]. The closer the parameter is to the ideal value... The closer its value is to 0, the closer it is to 1; the further it deviates from the limit, the closer its value is to 1.

[0041] The early warning output unit includes a tiered early warning module and an early warning output module. The tiered early warning module determines the early warning level based on the comprehensive water vapor quality index and preset multi-level early warning thresholds. The early warning output module outputs an early warning signal and corresponding handling suggestions. The tiered early warning module includes attention thresholds. Abnormal threshold and danger threshold ,and < < And compare the comprehensive water vapor quality index with the multi-level threshold: when CQI < When, it is judged as a normal state; when ≤ CQI < When, generate a warning at the attention level; when ≤ CQI < When CQI ≥ 0, an anomaly level warning is generated; when CQI ≥ 0, an anomaly When a hazard level warning is generated, the warning output module is used to output the generated warning information through at least one of the following methods: audible and visual alarm, SMS push, email notification, and system interface pop-up window, and simultaneously record the warning log.

[0042] The online data acquisition mechanism includes a pretreatment device located in front of the online silicon meter, online sodium meter, pH meter, conductivity meter, and dissolved oxygen analyzer. The pretreatment device includes a sampling tube 2 with a control valve 1. A coarse filter 3, a heat exchanger 4, a fine filter 5, and a collection box 6 are sequentially arranged behind the sampling tube 2. A detection port 7 is provided on one side of the collection box 6. The cold water inlet of the heat exchanger 4 is connected to an external water source. A multi-way valve 8 is provided at the cold water outlet of the heat exchanger 4, which is connected to the external water source, the coarse filter 3, and the fine filter 5, respectively.

[0043] The coarse filter 3 includes a housing 9, inside which is a coarse filter plate 10. The coarse filter plate 10 is a conical filter plate with the pointed corners pointing upwards. A rotating shaft 11 is provided on the upper side of the coarse filter plate 10. The rotating shaft 11 passes through the housing 9 and is connected to a motor 13 fixed to the upper side of the housing 9 by a bracket 12. A scraper 14 that fits against the coarse filter plate 10 is provided at the lower end of the rotating shaft 11. A first drain port 15 is provided on the side wall of the housing 9 on the upper side of the coarse filter plate 10. A first inlet port 16 that is connected to a multi-way valve 8 is provided on the side wall of the housing 9 on the lower side of the coarse filter plate 10.

[0044] The fine filter 5 includes a body 17, a fine filter plate 18 inside the body 17, an ultrasonic vibrating rod 19 on one side of the fine filter plate 18, a pressure piston 22 on one side of the ultrasonic vibrating rod 19, a second drain port 20 on the side wall of the body 17 below the fine filter plate 18, and a second water inlet 21 connected to the multi-way valve 8 on the side wall of the body 17 below the fine filter plate 18.

[0045] A method for a water vapor quality monitoring and early warning device based on multi-parameter fusion includes the following steps:

[0046] S1. Acquire multi-dimensional parameter data of the water vapor system in real time through online acquisition agencies, and regularly verify the data through offline testing agencies to ensure data accuracy;

[0047] S2. Preprocess and validate the multidimensional parameter data to generate a standardized valid dataset;

[0048] S3. Based on the dynamic weight allocation algorithm, the parameters in the effective dataset are weighted and fused to generate a comprehensive water vapor quality index for comprehensively characterizing water vapor quality.

[0049] S4. Compare the comprehensive water vapor quality index with the preset multi-level early warning threshold, determine the early warning level, and output the corresponding early warning signal and handling suggestions accordingly.

[0050] This invention integrates a pretreatment device at the front end of online silicon meters, online sodium meters, pH meters, conductivity meters, and dissolved oxygen analyzers. Its core function is to cool, filter, and stabilize the pressure of high-temperature, impurity-laden water vapor samples, ensuring that the water samples entering the analyzers meet the instruments' stringent requirements for temperature, cleanliness, and flow rate. It also features automatic self-cleaning to guarantee long-term stable operation. The high-temperature, high-pressure water vapor sample is drawn from the main pipeline through a sampling pipe equipped with a control valve. The control valve regulates the sampling flow rate and shuts off the sample water during maintenance. The sample water first enters a coarse filter to remove large particulate impurities before flowing into the heat exchanger.

[0051] The heat exchanger employs a water-to-water indirect cooling method. External cooling water enters the heat exchanger through the cold water inlet and undergoes counter-current heat exchange with the high-temperature sample water flowing through the internal coils or jacket. The sample water temperature is effectively reduced to the instrument's allowable operating temperature range, while the heated cooling water is discharged from the cold water outlet. A multi-way valve at the cooling water outlet can switch the water flow direction according to system commands, enabling the recycling of cooling water or its distribution to the backwash circuit. The cooled sample water then sequentially enters the coarse filter and the fine filter, forming a two-stage series filtration. As operating time increases, impurities gradually accumulate on the surface of the coarse filter plate, leading to an increase in the pressure difference across the filter plate. At this point, the motor drives the shaft to rotate, causing the scraper, which is in close contact with the surface of the coarse filter plate, to perform a circular motion. The scraper removes dirt, rust, and other impurities adhering to the filter plate surface and pushes them towards the side wall of the casing. Accumulated impurities settle under gravity and are periodically discharged through the first drain outlet, enabling uninterrupted online sewage discharge and ensuring the continuous and efficient filtration capacity of the coarse filter. The water sample after coarse filtration enters the interior of the fine filter body through the second inlet, passing through the fine filter plate with finer pores to further remove tiny suspended solids and colloidal particles, ensuring that the sample water entering the analytical instrument meets the high cleanliness requirements.

[0052] To address the issue of fine filter plates having small pore sizes and being more easily clogged by colloidal substances, this invention incorporates an ultrasonic vibrator on one side of the fine filter plate. When the system detects a pressure difference exceeding a set value (or according to a timed program), the ultrasonic vibrator activates, generating high-frequency mechanical vibrations that are transmitted to the fine filter plate and the surrounding water. These high-frequency vibrations create a strong cavitation effect and microjets in the water, effectively stripping away tiny impurity particles adhering to the filter plate surface and pores, causing them to detach and disperse into the water. The detached impurities are discharged through a second drain port during wastewater discharge, thus quickly restoring the filtration performance of the fine filter plate.

Claims

1. A water vapor quality monitoring and early warning device based on multi-parameter fusion, characterized in that, It includes a data acquisition unit, a data processing unit, a fusion analysis unit, and an early warning output unit; The data acquisition unit includes an online acquisition mechanism and an offline detection mechanism; The data processing unit includes a data preprocessing module and a data verification module. The data preprocessing module is used to filter and denoise the multidimensional parameter data and remove outliers. The data verification module is used to verify the validity of the processed data and diagnose the sensor status. The fusion analysis unit includes weighted fusion processing of the multidimensional parameter data based on a dynamic weight allocation algorithm to generate a comprehensive water vapor quality index (CQI). The early warning output unit includes a graded early warning module and an early warning output module. The graded early warning module is used to determine the early warning level based on the comprehensive water vapor quality index and the preset multi-level early warning threshold. The early warning output module is used to output early warning signals and corresponding handling suggestions.

2. The water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that: The online data acquisition system includes an online silicon meter located at the mixed bed outlet, an online sodium meter located at the main steam header of the boiler, and pH meters, conductivity meters, and dissolved oxygen analyzers distributed at various points in the water-steam system.

3. The water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that: The offline testing equipment includes a benchtop silicon water meter, a benchtop sodium water meter, a pH meter, a conductivity meter, and a dissolved oxygen analyzer, used to test sampled water and to perform periodic calibration and anomaly verification of online monitoring data.

4. The water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that, The data processing unit includes: The filtering and denoising subunit uses a wavelet threshold denoising algorithm to filter the original monitoring signal and remove high-frequency noise interference. The dimensional normalization sub-unit uses the Min-Max normalization method to convert monitoring data of different dimensions to a unified dimensional range.

5. A water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that: The tiered early warning module includes attention thresholds. Abnormal threshold and danger threshold ,and < < ; and compare the comprehensive water vapor quality index with the multi-level threshold: when < When, it is judged as a normal state; when ≤ CQI < When, generate a warning at the attention level; when ≤ CQI < When CQI ≥ 0, an anomaly level warning is generated; when CQI ≥ 0, an anomaly At that time, a danger level warning will be generated.

6. The water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that: The aforementioned warning output module is used to output the generated warning information through at least one of the following methods: audible and visual alarm, SMS push, email notification, and system interface pop-up window, and to record the warning log simultaneously.

7. A water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that: The online acquisition mechanism includes a pretreatment device located in front of the online silicon meter, online sodium meter, pH meter, conductivity meter and dissolved oxygen analyzer. The pretreatment device includes a sampling tube (2) with a control valve (1). A coarse filter (3), a heat exchanger (4), a fine filter (5) and a collection box (6) are arranged in sequence behind the sampling tube (2). A detection port (7) is provided on one side of the collection box (6). The cold water inlet of the heat exchanger (4) is connected to the external water source. A multi-way valve (8) is provided at the cold water outlet of the heat exchanger (4) and is connected to the external water source, the coarse filter (3) and the fine filter (5) respectively.

8. A water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 7, characterized in that: The coarse filter (3) includes a housing (9), and a coarse filter plate (10) is provided inside the housing (9). The coarse filter plate (10) is a conical filter plate with the pointed corners pointing upwards. A rotating shaft (11) is provided on the upper side of the coarse filter plate (10). The rotating shaft (11) passes through the housing (9) and is connected to a motor (13) fixed on the upper side of the housing (9) by a bracket (12). A scraper (14) that fits against the coarse filter plate (10) is provided at the lower end of the rotating shaft (11). A first drain port (15) is provided on the side wall of the housing (9) on the upper side of the coarse filter plate (10). A first inlet (16) that is connected to a multi-way valve (8) is provided on the side wall of the housing (9) on the lower side of the coarse filter plate (10).

9. A water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 7, characterized in that: The fine filter (5) includes a body (17), a fine filter plate (18) is provided inside the body (17), an ultrasonic vibrating rod (19) is provided on one side of the fine filter plate (18), a pressure piston (22) is provided on one side of the ultrasonic vibrating rod (19), a second drain port (20) is provided on the side wall of the body (17) below the fine filter plate (18), and a second water inlet (21) is provided on the side wall of the body (17) below the fine filter plate (18) and connected to the multi-way valve (8).

10. The method for a water vapor quality monitoring and early warning device based on multi-parameter fusion according to claim 1, characterized in that, Includes the following steps: S1. Acquire multi-dimensional parameter data of the water vapor system in real time through online acquisition agencies, and regularly verify the data through offline testing agencies to ensure data accuracy; S2. Preprocess and validate the multidimensional parameter data to generate a standardized valid dataset; S3. Based on the dynamic weight allocation algorithm, the parameters in the effective dataset are weighted and fused to generate a comprehensive water vapor quality index for comprehensively characterizing water vapor quality. S4. Compare the comprehensive water vapor quality index with the preset multi-level early warning threshold, determine the early warning level, and output the corresponding early warning signal and handling suggestions accordingly.

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