Multi-dimensional detection method and system for steam-water pollution

Abstract

The embodiment of the invention provides a multi-dimensional detection method and system for steam-water pollution, and the method comprises the steps: setting sampling points at target positions of condensed water, feed water, boiler water and a steam system, and detecting sampling parameters at the sampling points; identifying a water quality abnormal signal based on the sampling parameter and a preset threshold value of the water quality index; associating the water quality abnormal signal with target equipment and carrying out chemical analysis so as to position a pollution source; monitoring the thermotechnical state of the target equipment in real time, collecting thermotechnical parameters, and establishing a linkage model of the thermotechnical parameters and the water quality indexes to identify the influence of abnormal working conditions on the water quality; according to the influence result of the abnormal working condition on the water quality, the water delivery module, the shaft seal module and the dosing module are subjected to sealing performance test and purity detection so as to identify hidden source abnormal signals; and performing multi-dimensional analysis on the water quality abnormal signal, the pollution source, the abnormal working condition and the hidden source abnormal signal, and building a fault tree to generate a pollution source priority list and dynamically adjust a pollution discharge strategy.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of operation and maintenance of thermal power generating units, and particularly relates to a multi-dimensional detection method and system for steam-water pollution. BACKGROUND

[0002] Steam-water quality of a thermal power generating unit directly affects safety and efficiency of the unit, and deterioration of the steam-water quality can cause problems such as boiler fouling, corrosion and salt accumulation in a steam turbine.

[0003] Existing inspection methods mainly rely on conventional water quality monitoring and equipment appearance inspection, and have the following deficiencies: 1) limitation in locating pollution sources: it is difficult to quickly lock hidden pollution sources (such as cross-pollution of a chemical dosing system and damage of a drain expansion vessel partition) only through changes in water quality indexes; 2) lack of dynamic correlation: there is a lack of deep linkage analysis of water quality data and operating parameters (such as load and water level); 3) lack of application of advanced technologies: advanced detection means such as isotope tracing and online particle counting are not fully utilized; and 4) low system integration: traditional methods rely on manual operation, and the level of automation and intelligence is insufficient, which cannot meet the requirements of real-time monitoring of relevant policies and standards. SUMMARY

[0004] The application provides a multi-dimensional detection method and system for steam-water pollution, which is used to solve the above-mentioned deficiencies of the prior art.

[0005] According to a first aspect of an embodiment of the application, a multi-dimensional detection method for steam-water pollution is provided, which comprises:

[0006] Setting a sampling point at a target position of a condensate water, feed water, boiler water and steam system, and detecting a sampling parameter at the sampling point;

[0007] Identifying a water quality abnormal signal based on the sampling parameter and a preset threshold of a water quality index;

[0008] Associating the water quality abnormal signal with a target device and performing chemical analysis to locate a pollution source;

[0009] Real-time monitoring of a thermal state of the target device and collection of a thermal parameter, establishment of a linkage model of the thermal parameter and the water quality index, and identification of an influence of an abnormal working condition on water quality;

[0010] According to an influence result of the abnormal working condition on water quality, performing sealing property testing and purity detection on a water delivery module, a shaft seal module and a dosing module to identify a hidden source abnormal signal;

[0011] Performing multi-dimensional analysis on the water quality abnormal signal, the pollution source, the abnormal working condition and the hidden source abnormal signal, and building a fault tree to generate a pollution source priority list and dynamically adjust a blowdown strategy.

[0012] In some embodiments, the sampling parameters include routine indexes, trace elements, organic parameters and isotope parameters, wherein the routine indexes include conductivity, pH value and cation and anion concentration, the trace elements include aluminum, zinc, lead and nickel, the organic parameters include total organic carbon, volatile organic compounds and oil content, and the isotope parameters include hydrogen and oxygen isotopes and dissolved gas isotopes.

[0013] In some embodiments, identifying the water quality abnormal signal based on the sampling parameters and preset thresholds of water quality indexes includes: identifying trace element abnormal signals, isotope difference abnormal signals and organic parameter over-standard signals based on the sampling parameters and preset thresholds; the trace element abnormal signals are triggered based on detection of over-standard trace element concentration; the isotope difference abnormal signals are triggered based on isotope difference exceeding a preset deviation; and the organic parameter over-standard signals are triggered based on detection of over-standard organic parameters.

[0014] In some embodiments, correlating the water quality abnormal signal with a target device and performing chemical analysis to locate a pollution source includes:

[0015] correlating the trace element abnormal signals with a target device corrosion source or a target device pollution source and generating a fingerprint feature of the trace element abnormal signals;

[0016] determining a condenser leakage based on the isotope difference abnormal signals;

[0017] locating an oil pollution source based on the organic parameter over-standard signals.

[0018] In some embodiments, real-time monitoring of thermal state of the target device and collection of thermal parameters, and establishment of a linkage model of the thermal parameters and the water quality indexes to identify the influence of abnormal working conditions on water quality includes:

[0019] real-time monitoring of thermal state of the target device and collection of particulate pollutants, and monitoring of particulate pollutants through online particle size analysis to determine a device wear risk of the target device;

[0020] real-time monitoring of thermal state of the target device and collection of corrosion rate and iron ion concentration change to determine an oxygen corrosion risk of the target device;

[0021] based on the device wear risk and the oxygen corrosion risk, establishing a linkage model of thermal parameters and the water quality indexes to identify the influence of wear abnormal working conditions and oxygen corrosion abnormal working conditions of the target device on water quality.

[0022] In some embodiments, the real-time monitoring of the thermal state of the target equipment and the collection of the particulate contamination, the monitoring of the particulate contamination by online particle size analysis to determine the equipment wear risk of the target equipment comprises:

[0023] installing an online particle counter at a target position of the feedwater pipeline, the resolution of the online particle counter being not less than 5 μm;

[0024] when the size of the particulate contamination detected by the online particle counter is greater than 50 μm, it is inferred that there is a large particulate contamination in the feedwater pipeline, and it is determined that the target equipment has an equipment wear risk, wherein the large particulate contamination includes spalling oxide scale and residual welding slag from maintenance.

[0025] In some embodiments, the real-time monitoring of the thermal state of the target equipment and the collection of the corrosion rate and the change in the iron ion concentration to determine the oxygen corrosion risk of the target equipment comprises:

[0026] using a linear polarization resistance probe to collect the corrosion rate and the change in the iron ion concentration in real time, and when the corrosion rate exceeds 0.1 mm / a and the iron ion concentration is greater than 50 μg / L, it is determined that the target equipment has an oxygen corrosion risk.

[0027] In some embodiments, the sealing test and purity detection of the water feeding module, the shaft seal module and the chemical dosing module to identify hidden source abnormal signals comprises:

[0028] visually inspecting the internal partition of the hydrophobic expander of the water feeding module and carrying out a pressure test of maintaining 0.5 MPa water pressure for 30 minutes to perform the sealing test and detect whether the hydrophobic expander has a water feeding abnormal leakage problem;

[0029] carrying out an internal leakage test on the blowdown valve of the water feeding module, including closing the blowdown valve and detecting the pressure difference before and after, and if the pressure drop exceeds 0.3 aMP, it is determined that the blowdown valve has an internal leakage abnormal problem;

[0030] monitoring the shaft seal steam supply oil content of the shaft seal module, and when the shaft seal steam supply oil content exceeds 0.1 mg / m 3 , it is determined whether the shaft seal module has a steam leakage and oil carry-over abnormal problem;

[0031] checking whether the bypass valve of the shaft seal module is tightly closed to determine whether the main steam bypass has a backflow and contamination of condensate water abnormal problem;

[0032] checking the identification of the chemical dosing pipeline, and detecting the purity of the chemical agent of the chemical dosing module by ion chromatography to determine whether the anion and cation concentration impurities have an abnormal problem;

[0033] The hidden source abnormal signal includes a trigger signal of an abnormal water leakage problem of the hydrophobic expansion vessel, a trigger signal of an abnormal internal leakage problem of the blowdown valve, a trigger signal of an abnormal oil leakage problem of the shaft seal module, a trigger signal of an abnormal backflow pollution of the main steam bypass, and a trigger signal of an abnormal problem of the cation and anion concentration impurities.

[0034] In some embodiments, the multi-dimensional analysis of the water quality abnormal signal, the pollution source, the abnormal working condition and the hidden source abnormal signal and the building of the fault tree to generate a pollution source priority list and dynamically adjust the blowdown strategy comprises:

[0035] The fault tree is established based on a plurality of fault factors and mutual relationships, wherein the plurality of fault factors include the water quality abnormal signal, the pollution source, the abnormal working condition and the hidden source abnormal signal;

[0036] The pollution source priority list is generated based on a plurality of fault factors and mutual relationships in the fault tree, wherein the priority includes preferentially checking the fault factors with a probability of causing a fault of more than 60%;

[0037] Based on the priority list and the conventional index, the blowdown strategy is dynamically adjusted and the blowdown operation is performed to ensure that the water quality reaches the preset threshold of the water quality index.

[0038] According to a second aspect of the embodiments of the present application, a multi-dimensional detection system for steam and water pollution is provided, comprising:

[0039] A water quality sampling module is configured to set a sampling point at a target position of a condensate water, feed water, boiler water and steam system, and detect a sampling parameter at the sampling point;

[0040] A water quality abnormality identification module is configured to identify a water quality abnormal signal based on the sampling parameter and a preset threshold of a water quality index;

[0041] A pollution source positioning module is configured to associate the water quality abnormal signal with a target device and perform chemical analysis to locate a pollution source;

[0042] An abnormal working condition monitoring module is configured to monitor a thermal state of the target device in real time and collect a thermal parameter, and establish a linkage model of the thermal parameter and the water quality index to identify an influence of an abnormal working condition on water quality;

[0043] An abnormal hidden source identification module is configured to perform sealing test and purity detection on a water feeding module, a shaft seal module and a chemical feeding module according to an influence result of the abnormal working condition on water quality to identify a hidden source abnormal signal;

[0044] The multi-dimensional sewage discharge module is used to perform multi-dimensional analysis on the abnormal water quality signal, the pollution source, the abnormal working condition and the abnormal signal of the hidden source and build a fault tree to generate a priority list of pollution sources and dynamically adjust the sewage discharge strategy.

[0045] According to a third aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the multi-dimensional detection method for soda contamination described above is implemented.

[0046] The beneficial effects of the multi-dimensional detection method and system for soda contamination according to the embodiments of the present application include at least:

[0047] The embodiment of the present application performs multi-dimensional sampling and detection at key locations of the condensate water, water supply, etc., covering conventional, trace, organic matter and isotope parameters; further compares the preset threshold to quickly identify abnormal water quality signals, realizes comprehensiveness and timeliness of initial pollution screening, and completes sampling detection and abnormality identification; directly associates abnormal water quality signals with corrosion characteristics of target equipment (such as trace element fingerprints); combines isotope tracing verification, solves the defect that traditional methods cannot trace hidden leakage points, and realizes accurate positioning of pollution sources; through real-time monitoring of the thermal status of the equipment and establishment of thermal-water quality Linkage model; captures the immediate impact of sudden changes in operating conditions (such as a sudden increase in load) on water quality, warns of equipment operation risks, and realizes dynamic control of the impact of operating conditions; performs sealing tests and purity tests on hydrophobic, shaft seal, and dosing modules; blocks the pollution propagation path by identifying conventional monitoring blind spots such as valve internal leakage and chemical contamination, and realizes active detection of hidden leaks; builds a fault tree by integrating water quality anomalies, pollution sources, operating conditions, and hidden source signals, and generates an executable priority list; dynamically adjusts the sewage discharge strategy to balance water quality compliance and economic operation, and realizes intelligent decision-making and closed-loop control. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 Schematic diagram of the process of the multi-dimensional detection method of soda contamination according to an embodiment of the present application;

[0049] Figure 2 Schematic diagram of the structure of the multi-dimensional detection system for soda contamination according to an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the technical solution of the present application, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0051] The following detailed description of the embodiments of the present application is provided in conjunction with the accompanying drawings and examples. The following detailed description of the embodiments and the accompanying drawings are used to illustrate the principles of the present application, but are not intended to limit the scope of the present application, that is, the present application is not limited to the described embodiments.

[0052] Referring to the drawings Figure 1 As shown in the drawings, the embodiments of the present application disclose a specific implementation step of a steam-water pollution multi-dimensional detection method, which is executed based on a steam-water pollution multi-dimensional detection system to ensure that a person skilled in the art can realize the technical solution of the present application. The method specifically comprises the following steps 110-160.

[0053] Step 110, setting a sampling point at a target position of a condensate water, feed water, boiler water and steam system, and detecting a sampling parameter at the sampling point.

[0054] Among them, the target position of the condensate water, feed water, boiler water and steam system can be understood as the key position of the condensate water, feed water, boiler water and steam system, such as the outlet of the condenser, the inlet of the high-pressure heater, etc.

[0055] For example, the sampling parameter includes a conventional index, a trace element, an organic matter parameter and an isotope parameter.

[0056] For example, the conventional index includes conductivity, pH value and concentration of cations and anions (such as Na+, Cl

[0057] , PO43-) concentration, the conventional index can also be the concentration of substances such as silicon dioxide (SiO2), which is used for comparison and analysis with the threshold parameters provided by the current relevant policy standards to quickly identify whether the water quality is obviously abnormal, and to provide a basis for subsequent in-depth detection. The trace element includes aluminum (Al), zinc (Zn), lead (Pb) and nickel (Ni), etc., which is mainly used to represent a depth index, which can be obtained by using inductively coupled plasma mass spectrometry (ICP-MS) detection; the organic matter parameter includes total organic carbon (TOC), volatile organic compounds (VOCs) and oil content, which can be obtained by gas chromatography-mass spectrometry analysis; the isotope parameter includes hydrogen and oxygen isotopes (δD, δ 1 8O) and dissolved gas isotopes (Ar, N2), which can be obtained by isotope ratio mass spectrometry. Based on the above sampling parameters, the precise detection of trace and trace substances in water quality can be realized, and potential pollution source information can be mined.

[0058] The sampling accuracy of the present application is controlled within ±2% to ensure that the conventional water quality parameters of the steam-water system can be monitored in real time and accurately, and to provide basic data support for water quality evaluation.

[0059] Step 120, identifying a water quality abnormal signal based on the sampling parameter and a preset threshold of the water quality index.

[0060] In some embodiments, identifying the water quality abnormality signal based on the sampling parameters and the preset threshold of the water quality index comprises: identifying a trace element abnormality signal, an isotope difference abnormality signal, and an organic matter parameter over-standard signal based on the sampling parameters and the preset threshold; the trace element abnormality signal is triggered based on detection of over-standard trace element concentration; the isotope difference abnormality signal is triggered based on over-standard isotope difference; and the organic matter parameter over-standard signal is triggered based on detection of over-standard organic matter parameter, when the organic matter parameter over-standard signal is triggered.

[0061] In some embodiments, detection of over-standard trace element concentration is based on completion of a trace element detector, such as an inductively coupled plasma mass spectrometer, which has a detection limit of ppb level, enabling ultra-trace detection of trace metal elements in water and mining potential pollution source information.

[0062] In some embodiments, the isotope difference is detected based on an isotope analyzer (for example, with resolution δD controlled at ±0.5‰ and resolution δ 1 8O controlled at ±0.2‰), thereby ensuring accurate determination of hydrogen and oxygen isotopes and dissolved gas isotopes, and providing a powerful tool for tracing water pollution sources.

[0063] Step 130, associating the water quality abnormality signal with a target device and performing chemical analysis to locate a pollution source.

[0064] In some embodiments, associating the water quality abnormality signal with a target device and performing chemical analysis to locate a pollution source comprises: associating the trace element abnormality signal with a target device corrosion source or a target device pollution source, and generating a fingerprint feature of the trace element abnormality signal; determining a condenser leakage based on the isotope difference abnormality signal; and locating an oil pollution source based on the organic matter parameter over-standard signal.

[0065] For example, after generating the fingerprint feature of the trace element abnormality signal, research purposes can include in-depth study of the correlation between different trace element abnormalities and specific pollution sources. For example, Al 3 + concentration abnormality may indicate broken cation exchange resin of make-up water or excessive coagulant addition; Zn 2+ / Pb 2 + over-standard is very likely related to copper tube corrosion of low-pressure heater or valve seal wear; and Ni 2 + concentration abnormality is probably indicative of high-temperature corrosion of stainless steel components (such as superheaters), thereby providing strong evidence for rapid locking of pollution sources through accurate detection and analysis of trace elements.

[0066] For example, determining a condenser leakage based on the isotope difference abnormality signal can include isotope tracing verification, such as comparison of δD / δ 18O difference, when the deviation exceeds ±5‰, it can be determined that there is a micro-leakage in the condenser. This embodiment can use the characteristics of isotopes to accurately identify hidden leakage points, making up for the shortcomings of traditional detection methods in detecting micro-leakage.

[0067] For example, locating the source of oil pollution based on the signal of excessive organic matter parameters may include: tracing the source of organic matter. For example, if the TOC concentration exceeds 500μg / L and the oil content is greater than 2mg / L, combined with the equipment operating conditions and system layout, it is judged that there may be turbine lubricating oil leakage or heat exchanger oil contamination as the main cause of abnormal water quality, so as to carry out targeted inspection and maintenance work on the corresponding equipment.

[0068] Step 140 , monitor the thermal status of the target equipment in real time and collect thermal parameters, establish a linkage model between thermal parameters and water quality indicators, and identify the impact of abnormal working conditions on water quality.

[0069] In some embodiments, the thermal state of the target equipment is monitored in real time and thermal parameters are collected, and a linkage model of thermal parameters and water quality indicators is established to identify the impact of abnormal working conditions on water quality, including: real-time monitoring of the thermal state of the target equipment and collecting particulate pollutants, monitoring particulate pollutants through online particle size analysis to determine the equipment wear risk of the target equipment; real-time monitoring of the thermal state of the target equipment and collecting changes in corrosion rate and iron ion concentration to determine the oxygen corrosion risk of the target equipment; based on the equipment wear risk and oxygen corrosion risk, a linkage model of thermal parameters and water quality indicators is established to identify the impact of abnormal wear conditions and abnormal oxygen corrosion conditions of the target equipment on water quality.

[0070] In some embodiments, real-time monitoring of the thermal status of target equipment and collection of particulate contaminants, and monitoring of particulate contaminants through online particle size analysis to determine the risk of equipment wear for the target equipment may include: installing an online particle counter at a target location in the water supply pipeline, with a resolution of no less than 5μm; when the online particle counter detects a particle contaminant larger than 50μm, it is inferred that larger particulate contaminants are present in the water supply pipeline, and the target equipment is determined to be at risk of equipment wear. Larger particulate contaminants include flaking oxide scale and residual welding slag from maintenance. For example, if 10-20μm particles are continuously detected, it may be determined that the system is experiencing minor corrosion or valve wear. This embodiment of the present application can provide early warning of potential equipment failure risks by monitoring the dynamics of particle contamination in real time.

[0071] In some embodiments, the online particle counter has a detection range of 0-10,000 particles / mL and a particle size resolution of 1 μm, thereby monitoring the concentration and size distribution of particulate pollutants in the soda system in real time, and providing timely warnings for equipment wear, corrosion and other problems.

[0072] In some embodiments, the corrosion monitoring probe can have a linear polarization resistance (LPR) and electrochemical noise (EN) dual monitoring mode, with a sampling frequency of 1 time / minute. The embodiments of the present application can quickly and sensitively reflect the corrosion state of the metal material, and provide data basis for the corrosion prevention and maintenance of the equipment.

[0073] In some embodiments, the real-time monitoring of the thermal state of the target equipment and the collection of the corrosion rate and the change in the iron ion concentration are used to determine the oxygen corrosion risk of the target equipment, including: using a linear polarization resistance (LPR) probe to collect the corrosion rate and the change in the iron ion concentration in real time, and determining that the target equipment has an oxygen corrosion risk when the corrosion rate exceeds 0.1 mm / a and the iron ion concentration is greater than 50 μg / L. Based on this step, the embodiments of the present application can take timely measures to prevent further corrosion and ensure the integrity and reliability of the equipment.

[0074] In some embodiments, based on the equipment wear risk and the oxygen corrosion risk, a linkage model of thermal parameters and water quality indicators is established to identify the influence of the wear abnormal working condition and the oxygen corrosion abnormal working condition of the target equipment on the water quality, which may, for example, include: based on the equipment wear risk and the oxygen corrosion risk, a regression model between the thermal parameters such as boiler load and drum water level and the steam Na+ concentration is established, and when the boiler load suddenly increases, if the steam Na+ concentration suddenly rises by more than 20 μg / kg, it is analyzed that the decrease in the efficiency of the steam-water separator is the key factor causing the water quality anomaly. This step of the present application can achieve comprehensive control of the operation state of the steam-water system through linkage analysis of cross parameters.

[0075] In step 150, according to the influence result of the abnormal working condition on the water quality, the sealing test and the purity detection of the water delivery module, the shaft seal module and the chemical feeding module are performed to identify the hidden source abnormal signal.

[0076] In some embodiments, the sealing test and the purity detection of the water delivery module, the shaft seal module and the chemical feeding module to identify the hidden source abnormal signal include: visually inspecting the internal partition of the hydrophobic expansion vessel of the water delivery module, and performing a pressure test of maintaining 0.5 MPa water pressure for 30 minutes to perform the sealing test and detect whether the hydrophobic expansion vessel has a water delivery abnormal leakage problem; performing an internal leakage test on the blowdown valve of the water delivery module, including closing the blowdown valve and detecting the pressure difference before and after, and if the pressure drop exceeds 0.3 aMP, it is determined that the blowdown valve has an internal leakage abnormal problem; monitoring the shaft seal steam supply oil content of the shaft seal module, and if the shaft seal steam supply oil content exceeds 0.1 mg / m 3determine whether the condensate water is polluted by the main steam bypass; check the identification of the dosing pipeline, and detect the purity of the chemical agent of the dosing module by using ion chromatography, to determine whether there is an abnormal problem in the concentration of cation and anion impurities; wherein the hidden source abnormal signal includes a trigger signal of the drain expansion vessel existing abnormal leakage problem of water delivery, a trigger signal of the blowdown valve existing abnormal problem of internal leakage, a trigger signal of the shaft seal module existing abnormal problem of steam leakage with oil, a trigger signal of the main steam bypass existing abnormal problem of contaminated condensate water by backflow, and a trigger signal of the abnormal problem of the concentration of cation and anion impurities. The step of the embodiment of the present application can ensure the normal operation of the drain system, avoid water pollution caused by drain system failure; can prevent the main steam bypass from backflowing and contaminating the condensate water, ensure the sealing performance of the shaft seal system, and maintain the stability of the condensate water quality; can avoid water quality abnormalities caused by dosing system failure or agent pollution, and strictly control the quality of the chemical agent adding link. For example, if the detection index exceeds the standard range, for example, the Cl- concentration of the condensate water is greater than 5 μg / L, the pollution source investigation process is triggered immediately, and the subsequent detailed tracing and positioning work is started in time to ensure that the water quality abnormality is responded quickly.

[0077] In some embodiments, the sealing test and purity detection of the water delivery module, the shaft seal module and the dosing module to identify the hidden source abnormal signal according to the influence of the abnormal working condition on the water quality further includes: start-stop stage control, for example, during the shutdown period, the nitrogen charging pressure is maintained above 0.05 MPa, and the hydrazine concentration is ensured to be more than 200 mg / L, to prevent the equipment from being corroded during the shutdown period; during the startup stage, sufficient pipe flushing operation is performed until the drain Fe concentration is less than 500 μg / L, and then the grid connection is allowed to run, which can reduce the influence of impurities on steam quality during the startup process.

[0078] In some embodiments, the sealing test and purity detection of the water delivery module, the shaft seal module and the dosing module to identify the hidden source abnormal signal according to the influence of the abnormal working condition on the water quality further includes: external water source isolation, for example, a pressure sensor is installed at a key position of the industrial water standby system, when it is monitored that the water side pressure of the condenser is higher than the steam side pressure, the isolation valve is automatically closed, thereby preventing the external water source from accidentally mixing into the steam-water system and causing water quality deterioration.

[0079] In some embodiments, based on the impact of abnormal operating conditions on water quality, the water delivery module, shaft seal module and dosing module are tested for sealing and purity to identify hidden source abnormal signals. This also includes: fuel impact assessment. For example, when burning high-chlorine fuel, the correlation between the exhaust HCl concentration and the steam-water Cl- concentration is monitored simultaneously. If the correlation coefficient exceeds 0.8, it is assessed that there is a risk of coal burner leakage. This step of the present application can take corresponding preventive measures in advance to reduce the adverse effects of fuel characteristics on steam-water quality.

[0080] For example, the present application can establish a regression model between the boiler load drum water level and the steam Na+ concentration, and set the model correlation coefficient to be ≥0.9 and the prediction accuracy to ≤10%. The present application also includes: dosing calibration, such as checking the dosing pipeline markings, detecting the purity of the reagents (Cl- impurities ≤0.01%) and verifying the accuracy and reliability of the dosing pump; conducting regular water pressure tests on the condenser, with a test pressure of not less than 0.8MPa and a duration of not less than 30min, and checking the sealing of the titanium tube expansion joint and other parts; monitoring the turbine lubricating oil system, such as oil quality analysis, oil pressure detection, oil temperature monitoring, etc., to promptly detect lubricating oil leakage or contamination; conducting a comprehensive inspection of the heat exchanger, such as appearance inspection, internal structure inspection, sealing test, etc., to prevent the heat exchanger oil contamination from causing water quality abnormalities.

[0081] Step 160 , perform multi-dimensional analysis on abnormal water quality signals, pollution sources, abnormal operating conditions and hidden source abnormal signals and build a fault tree to generate a pollution source priority list and dynamically adjust the sewage discharge strategy.

[0082] In some embodiments, a multi-dimensional analysis of water quality abnormal signals, pollution sources, abnormal operating conditions, and hidden source abnormal signals is performed and a fault tree (which can also be understood as a thermal-water quality linkage model) is constructed to generate a pollution source priority list and dynamically adjust the sewage discharge strategy, including: establishing a fault tree based on multiple fault factors and their interrelationships, wherein the multiple fault factors include water quality abnormal signals, pollution sources, abnormal operating conditions, and hidden source abnormal signals; generating a pollution source priority list based on the multiple fault factors and their interrelationships in the fault tree, wherein the priority includes prioritizing the fault factors with a probability of causing the fault exceeding 60% (such as condenser leakage or dosing system failure); based on the priority list and conventional indicators, dynamically adjusting the sewage discharge strategy and executing the sewage discharge operation to ensure that the water quality reaches the preset threshold of the water quality indicator, for example, according to the conductivity and PO43- concentration of the boiler water, in accordance with the requirements of industry policy standards, automatically adjusting the sewage valve opening through the intelligent control system to ensure that the sewage discharge rate is strictly controlled within 5%. This step of the present application can improve the efficiency and pertinence of the pollution source investigation work, while optimizing the sewage discharge operation and reducing energy loss under the premise of ensuring water quality.

[0083] Exemplarily, the application realizes precise linkage adjustment of sewage valves, dosing pumps and other equipment through a programmable logic controller (PLC) supporting a Modbus protocol, ensures automatic operation of the system, and improves operation efficiency and reliability; stores historical water quality data, equipment operation data and other information through a cloud server, trains a water quality prediction model through a machine learning algorithm, realizes precise prediction and trend analysis of steam quality, and provides a scientific basis for decision-making; through a data fusion algorithm, advanced algorithms such as principal component analysis (PCA) are used to reduce the dimensionality of multi-source data, effectively extract key information, and establish a three-dimensional correlation model of “water quality-equipment-working condition”, so as to realize deep mining and fusion analysis of data, and fully reveal the internal relationship between various factors in the steam-water system; through a fault diagnosis module, a 64-type typical pollution scene knowledge base is built in, and fuzzy logic reasoning technology is used, so that the diagnosis accuracy is more than 92%, so that the pollution type and source of the steam-water system can be quickly and accurately identified, and clear guidance is provided for fault handling; through a visual interface, water quality trends, equipment states and system optimization suggestions are displayed intuitively and in real time, and mobile terminal remote access is supported, so that the operation personnel can easily master the operation of the steam-water system at any time and anywhere, make timely decisions, and improve the intelligent management level of the system.

[0084] The embodiment of the application realizes comprehensive and timely pollution preliminary screening by sampling and detecting in multiple dimensions at key positions of the condensate water and feed water systems, covering conventional, trace, organic and isotopic parameters; further compares with preset thresholds to quickly identify water quality abnormal signals, completes sampling and detection and abnormal identification; directly associates the water quality abnormal signals with the corrosion characteristics (such as trace element fingerprints) of the target equipment; combines isotopic tracing verification to solve the defect that traditional methods cannot trace hidden leakage points, realizes precise positioning of the pollution source; realizes dynamic control of working condition influence by real-time monitoring of equipment thermal state and establishing a thermal-water linkage model; capturing the immediate influence of working condition mutation (such as sudden load increase) on water quality, warning equipment operation risk, realizing dynamic control of working condition influence; performing sealing test and purity test on the drain, shaft seal and dosing module; by identifying the conventional monitoring blind area such as valve leakage and reagent pollution, blocking the pollution transmission path, realizing active investigation of hidden leakage; by fusing water quality abnormality, pollution source, working condition and hidden source signals to build a fault tree, generating an executable priority list; dynamically adjusting the sewage strategy to balance water quality compliance and economic operation, realizing intelligent decision-making and closed-loop control.

[0085] The application embodiment further significantly improves the micro-leak detection rate from 60% of the traditional method to more than 90% through in-depth application of isotope tracing and trace element analysis technology, greatly enhances the identification ability of hidden pollution sources, ensures precise control of steam quality, and improves precision; with the aid of dynamic monitoring technology and intelligent model analysis, the pollution source investigation time is greatly shortened, the investigation cost is reduced by 30%-50%, the chemical flushing frequency is reduced by 40%, the operation efficiency and maintenance economy of the thermal power unit are effectively improved, and the efficiency is optimized; the application strictly follows the requirements of industry policy standards, can automatically generate standard and accurate water quality reports, ensures that the operation and management of the thermal power unit meet relevant regulations and standards, reduces compliance risks and ensures compliance; the application realizes full-process automation and intelligentization from data acquisition, analysis to processing, significantly reduces the artificial intervention cost by more than 50%, reduces the work burden of the operation personnel, improves the intelligent level of the operation and maintenance of the thermal power unit, promotes the progress of the industry technology, and promotes the intelligent upgrading.

[0086] The following is a specific example of the above-mentioned method of the application for an implementation of a 300MW unit condensate water Cl- exceeding standard investigation: it is found that the Cl- concentration of the condensate water of the unit reaches 8μg / L, which exceeds the limit value of 5μg / L specified by the industry policy standard. At the same time, the hydrogen and oxygen isotopes of the condensate water and circulating water are analyzed, and the results show that the δD value of the condensate water is 8‰ more negative than that of the circulating water. Based on the isotope tracing principle, it is preliminarily judged that the condenser may have a micro-leak. In view of the preliminary judgment, a comprehensive special detection is carried out on the condenser, including 0.8MPa water filling test. During the test, it is found that there are bubbles continuously overflowing at the expansion joint of the titanium tube, which is confirmed as a condenser micro-leak through further inspection, and the pollution source is accurately located. According to the detection results, corresponding treatment measures are developed and implemented, including shutdown repair of the expansion joint and comprehensive flushing of the condensate water system. After the repair is completed, the Cl- concentration of the condensate water is detected again, and the result is reduced to 2μg / L, which meets the requirements of the industry policy standard, and the problem of condensate water Cl- exceeding standard is successfully solved, ensuring the safe and stable operation of the unit.

[0087] The following is a specific example of the above method of the present application for an embodiment of boiler water pH anomaly analysis: During the operation of the boiler, it was found by the dynamic monitoring system that when the boiler load increased, the pH value of the boiler water suddenly dropped. Combined with the thermal-water quality linkage model for analysis, the model suggested that the dosing system may be abnormal, resulting in the pH value of the boiler water being unable to maintain in the normal range. According to the model analysis result, the dosing system was further investigated. The purity of the phosphate agent was detected by ion chromatography, and it was found that the Cl- content in the agent was as high as 0.5%, far exceeding the standard limit of 0.01%, and it was determined that the incomplete cleaning of the drug tank caused the contamination of hydrochloric acid, which further affected the pH value of the boiler water. In view of the problems found, an optimization scheme was developed and implemented, including replacing the contaminated agent and comprehensively cleaning the dosing system. After optimization, the pH value of the boiler water returned to the qualified interval of 9.0-9.5, ensuring that the boiler water quality meets the requirements and ensuring the safe and efficient operation of the boiler.

[0088] The embodiment of the present application can perform deep mining and analysis on historical water quality data, equipment operation data, fault diagnosis data, etc. based on big data analysis and machine learning algorithms, continuously optimize the fault tree analysis model, and improve the accuracy and reliability of pollution source identification. According to the pollution source priority list, a detailed investigation plan and treatment scheme are automatically generated, including recommended detection methods, equipment, tools, and corresponding safety measures and precautions. Through real-time tracking of the pollution source investigation and treatment process, the treatment effect is evaluated and feedback, and the investigation and treatment strategy is adjusted in time to ensure that the steam and water quality returns to normal. By comprehensively using chemical analysis, dynamic monitoring, special equipment investigation and other means, the pollution source of poor steam and water quality of the thermal power unit is accurately located, the steam and water quality of the thermal power unit is improved, and the corrosion and cracking of important components such as boiler heating surface and steam turbine caused by water pollution is avoided, and the safety of the unit is improved. The embodiment of the present application can solve the deficiencies of the existing method in pollution source positioning accuracy, dynamic monitoring capability and system integration, ensure that the steam and water quality of the thermal power unit meets the industry standard, and improve the operation safety and economy.

[0089] Referring to the accompanying Figure 2 The embodiment of the present application discloses a multi-dimensional detection system for steam and water pollution. The system includes a water quality sampling module 210, a water quality anomaly identification module 220, a pollution source positioning module 230, an abnormal working condition monitoring module 240, an abnormal hidden source identification module 250, and a multi-dimensional pollution control module 260.

[0090] The water quality sampling module 210 is configured to set a sampling point at a target position of the condensate water, feed water, boiler water and steam system, and detect a sampling parameter at the sampling point. Based on this, the embodiment of the present application can collect representative water samples from key positions of the steam-water system, has two modes of automatic sampling and manual sampling, and can perform preliminary processing (such as filtering, cooling, pressure adjustment, etc.) on the collected water samples.

[0091] The water quality anomaly identification module 220 is configured to identify a water quality anomaly signal based on the sampling parameter and a preset threshold of the water quality index.

[0092] The pollution source positioning module 230 is configured to associate the water quality anomaly signal with the target device and perform chemical analysis to locate the pollution source.

[0093] The abnormal working condition monitoring module 240 is configured to monitor the thermal state of the target device in real time and collect thermal parameters, establish a linkage model of the thermal parameters and the water quality index, and identify the influence of the abnormal working condition on the water quality.

[0094] The abnormal hidden source identification module 250 is configured to perform sealing test and purity detection on the water feeding module, shaft seal module and chemical adding module according to the influence of the abnormal working condition on the water quality, to identify a hidden source anomaly signal.

[0095] The multi-dimensional pollution discharge module 260 is configured to perform multi-dimensional analysis on the water quality anomaly signal, the pollution source, the abnormal working condition and the hidden source anomaly signal, and build a fault tree to generate a pollution source priority list and dynamically adjust a pollution discharge strategy.

[0096] Based on this, the embodiment of the present application can integrate a plurality of high-precision detection instruments to comprehensively detect multi-dimensional parameters such as conventional indexes, trace elements, organic matter and isotopes in the water sample.

[0097] In addition, the multi-dimensional detection system for steam-water pollution of the present application further comprises a data transmission module that uses wired or wireless communication technology to transmit detection data to an intelligent control unit in real time and stably, ensuring the timeliness and accuracy of the data; a power module that provides stable and reliable power support for the entire device, has functions such as overload protection, short circuit protection and voltage stabilization, and is suitable for complex and variable environmental conditions in the field of thermal power generating units; a shell protection module that uses a solid, corrosion-resistant, dustproof and waterproof shell material to effectively protect each component inside the device, ensuring that the device can operate stably for a long time in harsh environments.

[0098] According to a multi-dimensional detection device for steam-water pollution according to the third aspect of the present application, the device comprises a water quality detection module, a dynamic monitoring module and an intelligent control module.

[0099] The water quality detection module is used for integrating multi-parameter online analyzers, trace element detectors, and isotope analyzers, has high-precision detection capability, and meets the detection needs of different water quality parameters; the dynamic monitoring module includes online particle counters and corrosion monitoring probes, can monitor particle pollutants and corrosion conditions in the steam-water system in real time, and provides dynamic monitoring data; the intelligent control module includes programmable logic controllers (PLCs) and cloud data analysis platforms, and realizes automatic control of the equipment and intelligent analysis and processing of data.

[0100] In some embodiments, the cloud data analysis platform further includes a data storage submodule, adopts a distributed storage architecture, has massive data storage capability, can safely and reliably store historical water quality data, equipment operation data, fault diagnosis data, and other information, and has a data storage period of no less than 10 years; a data processing submodule uses data cleaning, data conversion, data fusion, and other technologies to pre-process the collected multi-source data, improves the quality and availability of the data; a data analysis submodule integrates machine learning algorithms, fault tree analysis models, and thermal-water linkage models, and performs deep analysis and mining on the data to realize water quality prediction, fault diagnosis, optimization suggestions, and other functions; and a visualization submodule provides an intuitive and friendly visualization interface, supports access by various terminal devices such as computer terminals and mobile terminals, facilitates users to view water quality trends, equipment states, system alarms, and other information in real time, and has functions such as report generation and data export.

[0101] In some embodiments, the water quality detection unit further includes: a portable water quality analyzer for on-site rapid detection and emergency monitoring, has characteristics such as simple operation, rapid detection, and reliable precision, can detect conventional indexes such as conductivity, pH value, and ion concentration, and some trace elements and organic matter; laboratory analysis equipment including inductively coupled plasma mass spectrometry, gas chromatography-mass spectrometry, and isotope ratio mass spectrometry, is used for in-depth analysis and accurate detection of water samples, and provides high-precision data support for pollution source tracing; and an automatic sampling device that can automatically collect water samples at key positions of the steam-water system according to predetermined time intervals and sampling amounts, and has functions such as sample preservation and sample transmission, ensures the representativeness and integrity of the water samples.

[0102] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the program is executed by a processor to implement the method for inhibiting the dead zone of the coal-fired boiler load increase. For example, the method for inhibiting the dead zone of the coal-fired boiler load increase can be implemented by computer program instructions, and the related codes can be stored in the computer readable storage medium (such as a hard disk, an SSD or a cloud server). When the program is executed by the processor, the steps of the above method are automatically executed, and the following functions are provided: the full-process automatic control and management of the method for checking the steam and water pollution of the thermal power generating unit are implemented, including the data acquisition, analysis, diagnosis, decision, processing and other links; the user permission management function is provided, the login and operation of different levels of users are supported, and the security of the system and the confidentiality of the data are ensured; the data interaction and integration with other management systems (such as an equipment management system, an operation monitoring system and the like) of the thermal power generating unit are enabled, the information sharing and collaborative work are implemented; the system self-checking and fault alarm functions are provided, the abnormal conditions in the system operation process can be found and handled in time, and the stable and reliable operation of the system is ensured.

[0103] It can be understood that the above embodiments are only exemplary embodiments for illustrating the principles of the present application, and the present application is not limited thereto. Various modifications and improvements can be made by those skilled in the art without departing from the spirit and essence of the present application, and these modifications and improvements are also considered as the protection scope of the present application.

Claims

1. A multi-dimensional detection method for soda contamination, characterized in that: include: Setting sampling points at target locations of condensate, feed water, boiler water and steam systems, and detecting sampling parameters at said sampling points; Identifying abnormal water quality signals based on the sampling parameters and preset thresholds of water quality indicators; Correlating the abnormal water quality signal with the target equipment and performing chemical analysis to locate the pollution source; Real-time monitoring of the thermal status of the target equipment and collection of thermal parameters, and establishment of a linkage model between the thermal parameters and the water quality indicators to identify the impact of abnormal operating conditions on water quality; Based on the impact of the abnormal operating conditions on water quality, the water delivery module, shaft seal module and dosing module are tested for sealing and purity to identify hidden source abnormal signals; A multi-dimensional analysis is performed on the abnormal water quality signal, the pollution source, the abnormal operating condition and the abnormal signal of the hidden source, and a fault tree is constructed to generate a priority list of pollution sources and dynamically adjust the sewage discharge strategy.

2. The method according to claim 1, characterized in that The sampling parameters include conventional indicators, trace elements, organic matter parameters and isotope parameters, wherein the conventional indicators include conductivity, pH value and anion and cation concentrations, the trace elements include aluminum, zinc, lead and nickel, the organic matter parameters include total organic carbon, volatile organic compounds and oil content, and the isotope parameters include hydrogen and oxygen isotopes and dissolved gas isotopes.

3. The method according to claim 2, characterized in that The identifying of abnormal water quality signals based on the sampling parameters and preset thresholds of water quality indicators includes: Based on the sampling parameters and preset thresholds, identifying abnormal trace element signals, abnormal isotope difference signals, and signals exceeding the organic parameter limit; The trace element abnormality signal is triggered based on the detection of the trace element concentration exceeding the standard; The isotope difference abnormal signal is triggered when the isotope difference exceeds a preset deviation; The organic matter parameter exceeding standard signal is triggered based on detecting that the organic matter parameter exceeds standard. When the organic matter parameter exceeding standard signal is triggered.

4. The method according to claim 3, characterized in that The step of associating the abnormal water quality signal with the target device and performing chemical analysis to locate the pollution source includes: Associating the abnormal trace element signal with a corrosion source of a target device or a pollution source of a target device, and generating a fingerprint feature of the abnormal trace element signal; determining condenser leakage based on the isotope difference abnormal signal; The oil pollution source is located based on the organic matter parameter exceeding the standard signal.

5. The method according to claim 2, characterized in that The real-time monitoring of the thermal status of the target equipment and the collection of thermal parameters, and the establishment of a linkage model between the thermal parameters and the water quality indicators to identify the impact of abnormal operating conditions on water quality include: Real-time monitoring of the thermal status of the target equipment and collection of particulate contaminants, and monitoring of the particulate contaminants through online particle size analysis to determine the equipment wear risk of the target equipment; Real-time monitoring of the thermal status of the target equipment and acquisition of changes in corrosion rate and iron ion concentration to determine the oxygen corrosion risk of the target equipment; Based on the equipment wear risk and the oxygen corrosion risk, a linkage model between thermal parameters and the water quality indicators is established to identify the impact of abnormal wear conditions and abnormal oxygen corrosion conditions of the target equipment on water quality.

6. The method according to claim 5, characterized in that The real-time monitoring of the thermal state of the target equipment and the collection of particulate pollutants, and the monitoring of the particulate pollutants by online particle size analysis to determine the equipment wear risk of the target equipment include: Install an online particle counter at a target location in the water supply pipeline, wherein the resolution of the online particle counter is not less than 5 μm; When the linear particle counter detects that the size of the particle pollutants is greater than 50 μm, it is inferred that there are larger particle pollutants in the water supply pipeline, and it is determined that the target equipment has a risk of equipment wear, wherein the larger particle pollutants include flaking oxide scale and residual welding slag from maintenance.

7. The method according to claim 5, characterized in that The real-time monitoring of the thermal state of the target equipment and collecting the corrosion rate and iron ion concentration changes to determine the oxygen corrosion risk of the target equipment includes: A linear polarization resistance probe is used to collect the corrosion rate and the iron ion concentration changes in real time. When the corrosion rate exceeds 0.1 mm / a and the iron ion concentration is greater than 50 μg / L, it is determined that the target device has an oxygen corrosion risk.

8. The method according to claim 2, characterized in that The sealing test and purity test of the water delivery module, the shaft seal module and the dosing module to identify the abnormal signal of the hidden source include: Conduct a visual inspection of the internal partitions of the hydrophobic expansion vessel of the water transfer module and perform a pressure test at a water pressure of 0.5 MPa for 30 minutes to perform the sealing test and detect whether the hydrophobic expansion vessel has abnormal water transfer leakage; Perform an internal leakage test on the drain valve of the water delivery module, including closing the drain valve and detecting the pressure difference before and after. If the pressure drop exceeds 0.3aMP, it is determined that the drain valve has an abnormal internal leakage problem; Monitor the gasoline content of the shaft seal module. When the gasoline content of the shaft seal exceeds 0.1 mg / m 3 to determine whether the shaft seal module has an abnormal problem of steam leakage with oil; Check whether the bypass valve of the shaft seal module is tightly closed to determine whether there is abnormal backflow of contaminated condensate in the main steam bypass; Check the dosing pipeline markings and use ion chromatography to detect the purity of the dosing module to determine whether there are abnormalities in the anion and cation concentration impurities; Among them, the hidden source abnormal signals include the trigger signal of the abnormal water leakage problem in the hydrophobic expansion tank, the trigger signal of the abnormal internal leakage problem in the drain valve, the trigger signal of the abnormal steam leakage with oil problem in the shaft seal module, the trigger signal of the abnormal backflow of contaminated condensate in the main steam bypass and the trigger signal of the abnormal problem of anion and cation concentration impurities.

9. The method according to claim 2, characterized in that The multi-dimensional analysis of the abnormal water quality signal, the pollution source, the abnormal working condition and the abnormal hidden source signal and the construction of a fault tree to generate a pollution source priority list and dynamically adjust the sewage discharge strategy includes: Establishing the fault tree based on multiple fault factors and their interrelationships, wherein the multiple fault factors include the abnormal water quality signal, the pollution source, the abnormal working condition, and the abnormal signal from the hidden source; Based on the multiple fault factors and their interrelationships in the fault tree, generating the pollution source priority list, wherein the priority includes prioritizing the fault factors with a probability of causing the fault exceeding 60%; Based on the priority list and the conventional indicators, the sewage discharge strategy is dynamically adjusted and sewage discharge operations are performed to ensure that the water quality reaches the preset threshold value of the water quality indicator.

10. A multi-dimensional detection system for soda contamination, characterized in that: include: Water quality sampling module, used to set sampling points at target locations of condensate water, feed water, boiler water and steam systems, and detect sampling parameters at the sampling points; A water quality anomaly identification module, configured to identify water quality anomaly signals based on the sampling parameters and preset thresholds of water quality indicators; A pollution source locating module, configured to associate the abnormal water quality signal with a target device and perform chemical analysis to locate the pollution source; An abnormal operating condition monitoring module is used to monitor the thermal status of the target equipment in real time and collect thermal parameters, establish a linkage model between the thermal parameters and the water quality indicators, and identify the impact of abnormal operating conditions on water quality; An abnormal hidden source identification module is used to perform sealing and purity tests on the water delivery module, shaft seal module, and dosing module based on the impact of the abnormal operating conditions on water quality, so as to identify abnormal signals from hidden sources; The multi-dimensional sewage discharge module is used to perform multi-dimensional analysis on the abnormal water quality signal, the pollution source, the abnormal working condition and the abnormal signal of the hidden source and build a fault tree to generate a priority list of pollution sources and dynamically adjust the sewage discharge strategy.

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