SEC-based air cooling island flushing system data processing method
By collecting and processing multi-source data from the air-cooled island, a normalized dynamic SEC baseline value is generated and combined with visual perception data to predict the trend of fouling evolution, optimize flushing timing and parameters, solve the problems of distorted fouling assessment and resource waste in air-cooled islands, and achieve efficient and economical flushing decisions.
Patent Information
- Application Number
- CN202511868541.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-11
- Publication Date
- 2026-05-15
AI Technical Summary
In existing technologies, the contamination assessment of air-cooled islands is distorted, making it difficult to identify complex contamination patterns. Over-rinsing or under-rinsing occurs, and there is a lack of ability to predict future contamination evolution trends. Furthermore, it is impossible to combine electricity price fluctuations, water resource costs, and meteorological conditions for economic optimization, resulting in serious resource waste, delayed response, and extensive zoning control.
By collecting operational data of the air-cooled island, a normalized dynamic SEC baseline value is generated. This value is then combined with visual perception data for spatiotemporal alignment, input into a multimodal representation learning network, and a time series sample set is constructed to predict the evolution trend of the SEC. Finally, by combining electricity price, water price, and meteorological information, the comprehensive resource cost is calculated, and the optimal flushing time and parameters are determined.
It achieves high-dimensional and precise characterization of the dirt and grime status of the air-cooled island, improves the foresight and accuracy of flushing decisions, reduces resource waste, ensures unit efficiency and economy, and realizes intelligent operation that saves water, electricity and improves efficiency.
Smart Images
Figure CN122045618A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of intelligent operation and maintenance technology for power plant thermal systems, and in particular to a data processing method for an air-cooled island flushing system based on SEC. Background Technology
[0002] As the core heat exchange equipment in direct air-cooled units, the performance of the air-cooled island directly affects the back pressure level and coal consumption of the power plant. With the large-scale construction of air-cooled thermal power units in coal-rich and water-scarce western my country, the problem of heat exchange tube bundle fouling caused by environmental dust, willow catkins, and salt deposits in the air-cooled island has become increasingly prominent, becoming a key factor restricting the improvement of unit energy efficiency. To maintain heat exchange efficiency, regular flushing has become a necessary maintenance measure. In recent years, some studies have attempted to introduce a standardized energy consumption coefficient (SEC) as an evaluation index for the performance degradation of the air-cooled island, reflecting the system's energy consumption level through the ratio of fan power consumption to steam flow rate. However, in practical applications, this index is easily affected by strong interference factors such as unit load, ambient temperature, and wind speed, resulting in incomparable SEC values under different operating conditions, making it difficult to support accurate decision-making.
[0003] Existing technologies still have shortcomings in the field of intelligent flushing of air-cooled islands. For example, the SEC index does not isolate interference from non-dirt factors, resulting in distorted dirt assessment, difficulty in identifying complex pollution patterns, over-flushing or under-flushing, lack of ability to predict future dirt evolution trends, inability to combine electricity price fluctuations, water resource costs and meteorological conditions for economic optimization, failure to achieve deep integration with physical performance indicators, failure to form a high-dimensional and interpretable state representation, and problems such as serious resource waste, slow response, and extensive zoning control. Summary of the Invention
[0004] In view of the aforementioned existing problems, the present invention is proposed.
[0005] Therefore, this invention provides a data processing method for an air-cooled island flushing system based on SEC to address issues such as the failure to remove non-fouling factors from SEC indicators, resulting in distorted fouling assessments, difficulty in identifying complex fouling patterns, over-flushing or under-flushing, lack of predictive ability for future fouling evolution trends, inability to combine electricity price fluctuations, water resource costs, and meteorological conditions for economic optimization, failure to achieve deep integration with physical performance indicators, failure to form a high-dimensional, interpretable state representation, serious resource waste, delayed response, and extensive zoning control.
[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a data processing method for an air-cooled island flushing system based on SEC, comprising: Collect thermal parameters, fluid parameters, environmental parameters, and visual perception data generated during the operation of the air-cooled island; The original standardized energy consumption coefficient is calculated based on thermal and fluid parameters, and a normalized dynamic SEC baseline value is generated by combining the current load rate, ambient temperature and wind speed through the operating condition normalization model. After spatiotemporally aligning the normalized dynamic SEC baseline value with the visual perception data, the data is input into a multimodal representation learning network, which outputs a high-dimensional enhanced SEC state vector. A time series sample set is constructed based on the normalized dynamic SEC baseline value and the high-dimensional enhanced SEC state vector corresponding to the dynamic SEC baseline value, which are continuously generated within the historical period. Input the time series sample set into the time series evolution prediction model to predict the SEC evolution trend within a preset time window in the future; By combining the SEC evolution trend, real-time electricity price information, demineralized water unit price and short-term weather forecast, the comprehensive resource cost of each candidate flushing time is calculated; Based on the result of minimizing the overall resource cost, the optimal flushing execution time and flushing parameters are determined, and flushing control commands are generated and sent to the flushing execution platform.
[0007] As a preferred embodiment of the data processing method for the SEC-based air-cooled island flushing system described in this invention, the specific steps for collecting thermal parameters, fluid parameters, environmental parameters, and visual perception data generated during the operation of the air-cooled island are as follows: Temperature sensors are installed in the exhaust steam inlet pipe and cooling air outlet duct of the air-cooled island to obtain the exhaust steam temperature and cooling air outlet temperature. An air volume meter is installed at the air inlet of the fan to measure the volumetric flow rate of the cooling air, and a pressure transmitter is installed at the back pressure measuring point to collect the current back pressure value. Meteorological stations are deployed around the air-cooled island to simultaneously acquire ambient temperature, relative humidity and wind speed. An infrared thermal imager is installed on the track above the air-cooled island to periodically scan the surface of each sector tube bundle and generate an infrared image sequence with spatial coordinates. All devices are connected to the central data processing platform via an industrial communication bus to achieve multi-source data time synchronization and preliminary calibration.
[0008] As a preferred embodiment of the data processing method for the air-cooled island flushing system based on SEC described in this invention, the steps of calculating the original standardized energy consumption coefficient based on thermodynamic and fluid parameters, and generating a normalized dynamic SEC baseline value through a normalized operating condition model in conjunction with the current load rate, ambient temperature, and wind speed are as follows: Read the current wind turbine shaft power from the central data processing unit. With unit load rate Combined with the design maximum steam flow rate Calculate the current exhaust steam mass flow rate. ; in accordance with and Calculate the original standardized energy consumption coefficient The formula is: ; Because the original standardized energy consumption coefficient is affected by non-pollution factors, a normalized operating condition model is constructed. Based on load factor Ambient temperature and wind speed Input: Normalization correction factor ; Will and Multiply to generate a normalized dynamic SEC benchmark value. The expression is: ; in, For the function Output operating condition correction factor, Original standardized energy consumption coefficient, This is a normalized SEC benchmark value that only reflects the deterioration of heat exchange performance.
[0009] As a preferred embodiment of the data processing method for the air-cooled island flushing system based on SEC described in this invention, the steps of spatiotemporally aligning the normalized dynamic SEC baseline value with the visual perception data and then inputting it into a multimodal representation learning network to output a high-dimensional enhanced SEC state vector are as follows: Infrared thermal imager at all times The acquired image and the image at the same time Perform time alignment; The image is divided into sections based on the physical structure of the air-cooled island. Each logical sector, for each sector Extraction average temperature with temperature standard deviation ; Will , With the global Concatenate them into a three-dimensional feature matrix; The 3D feature matrix is input into a pre-trained multimodal representation learning network. This network integrates convolutional coding and cross-modal attention mechanisms, and its output dimension is... High-dimensional augmented SEC state vector ; The high-dimensional enhanced SEC state vector characterizes the overall heat transfer degradation and local ash accumulation unevenness.
[0010] As a preferred embodiment of the data processing method for the air-cooled island flushing system based on SEC described in this invention, the specific steps for constructing a time series sample set based on the normalized dynamic SEC baseline values continuously generated within historical time periods and the high-dimensional enhanced SEC state vectors corresponding to the dynamic SEC baseline values are as follows: Continuously record the data generated in each round over the past several hours at a fixed sampling period. and ,in For time step index; The sequences are arranged in chronological order, and a sliding window mechanism is used with a window length of [value missing]. Generate multiple consecutive samples, each containing A series of time steps Yes, it constitutes a structured time series sample set.
[0011] As a preferred embodiment of the data processing method for the air-cooled island flushing system based on SEC described in this invention, the specific steps of inputting the time series sample set into the time series evolution prediction model to predict the SEC evolution trend within a future preset time window are as follows: Input the time series sample set into the time series evolution prediction model based on the structured state space model; The time-series evolution prediction model learns the hidden dynamic processes of dirt accumulation and outputs future... SEC forecasts at each time step With state vector ,in ; To enhance decision-making sensitivity to persistent deterioration trends, a trend enhancement mechanism is introduced, defining an effective SEC evolution value. The formula is: ; in, For the first The normalized SEC value predicted by step. This is the current measured normalized SEC value. This is the trend enhancement coefficient, with a value ranging from 0 to 0.3. This is the effective SEC value after trend weighting.
[0012] As a preferred embodiment of the data processing method for the air-cooled island flushing system based on SEC as described in this invention, the specific steps for calculating the comprehensive resource cost of each candidate flushing time by combining SEC evolution trends, real-time electricity price information, demineralized water unit price, and short-term weather forecasts are as follows: For each candidate time According to the effective SEC value Compared with design benchmark value Deviation calculation of power generation loss cost The formula is: ; in, This represents the power generation revenue loss coefficient corresponding to a unit SEC degradation. The design SEC baseline value for the air-cooled island under clean conditions; Based on the required water pump power for rinsing runtime and real-time electricity price Calculate electricity consumption cost ,in, Real-time electricity price at the candidate time. The rated power of the flushing water pump, This refers to the standard duration of a single rinse. According to water consumption Price per unit of demineralized water Calculate water consumption cost ,in, This is the standard water consumption for a single flush. This refers to the unit price of demineralized water. Introducing meteorological risk correction factors Based on the probability of rainfall With wind speed A decision is defined as: ; in , To preset weights, This is the critical wind speed. For indicator functions, For weather forecast times The probability of rainfall, Forecast wind speed for the corresponding time; Comprehensive resource cost The expression is: ; in, For meteorological risk correction factors, For electricity consumption costs, For water consumption costs, The comprehensive resource cost of the candidate time.
[0013] As a preferred embodiment of the data processing method for the air-cooled island flushing system based on SEC described in this invention, the steps of determining the optimal flushing execution time and flushing parameters based on the minimization of comprehensive resource costs, and generating flushing control commands to be sent to the flushing execution platform, are as follows: Traverse all candidate moments corresponding Select to make Minimum moment As the optimal time to perform flushing; Read the predicted high-dimensional enhanced SEC state vector corresponding to the optimal flushing execution time. After normalizing each component of the predicted high-dimensional enhanced SEC state vector corresponding to the time step, a threshold is set. Identify and satisfy sector index set As the target flushing area; Based on each sector in the target flushing area The value is used to calculate the flushing intensity weight, and the formula is: ; in, Represents the high-dimensional augmented SEC state vector The corresponding number in the middle Component values of each sector This indicates the set of target sectors that need to be flushed. As an indicator of dirt and grime; The flushing water pressure and spray density for each area are set according to the flushing intensity weight; The optimal moment Region set Weight The commands are encapsulated as structured control instructions and sent to the rinsing execution platform via industrial communication protocols to drive the automatic rinsing equipment to perform precise zoned operations, thus completing data-driven closed-loop control.
[0014] In a second aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, it implements any step of the data processing method for the SEC-based air-cooled island flushing system as described in the first aspect of the present invention.
[0015] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the data processing method for the SEC-based air-cooled island flushing system as described in the first aspect of the present invention.
[0016] The beneficial effects of this invention are as follows: By introducing a normalized dynamic SEC benchmark value under operating conditions, the interference of non-pollution factors such as load, ambient temperature, and wind speed on energy consumption assessment is effectively eliminated, and the degree of heat exchange performance degradation of the air-cooled island is truly reflected. Combined with infrared visual perception data and a multimodal characterization learning network, a high-dimensional and accurate characterization of the overall and local dust accumulation state is achieved. Furthermore, based on a time-series evolution prediction model, the SEC degradation trend is predicted, and a comprehensive resource cost model is constructed by integrating electricity price, water price, and meteorological information. Thus, the optimal flushing time and zone flushing parameters are intelligently determined under all operating conditions, improving the foresight, accuracy, and economy of flushing decisions, and ultimately achieving the intelligent operation goal of saving water, saving electricity, and improving efficiency. Attached Figure Description
[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a flowchart of the data processing method for the SEC-based air-cooled island flushing system in Example 1. Detailed Implementation
[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0020] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.
[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.
[0022] Example 1, referring to Figure 1 As an embodiment of the present invention, this embodiment provides a data processing method for an air-cooled island flushing system based on SEC, comprising the following steps: S1. Collect thermal parameters, fluid parameters, environmental parameters, and visual perception data generated during the operation of the air-cooled island.
[0023] Furthermore, temperature sensors are installed in the exhaust steam inlet pipe and cooling air outlet duct of the air-cooled island to obtain the exhaust steam temperature and cooling air outlet temperature. An air volume meter is installed at the air inlet of the fan to measure the volumetric flow rate of the cooling air, and a pressure transmitter is installed at the back pressure measuring point to collect the current back pressure value. Meteorological stations are deployed around the air-cooled island to simultaneously acquire ambient temperature, relative humidity and wind speed. An infrared thermal imager is installed on the track above the air-cooled island to periodically scan the surface of each sector tube bundle and generate an infrared image sequence with spatial coordinates. All devices are connected to the central data processing platform via an industrial communication bus to achieve multi-source data time synchronization and preliminary calibration.
[0024] It should be noted that by deploying temperature sensors, air volume meters, pressure transmitters, weather stations, and infrared thermal imagers at key locations in the air-cooled island, and connecting all devices to a unified industrial communication bus and central data processing platform, high-precision synchronous acquisition and preliminary calibration of multi-source heterogeneous data from thermal, fluid, environmental, and visual sources were achieved. This provides complete, reliable, and spatiotemporally aligned basic data support for subsequent SEC indicator construction and dirt status identification, effectively avoiding evaluation biases caused by data loss, time sequence misalignment, or noise interference.
[0025] S2. Calculate the original standardized energy consumption coefficient based on the thermal and fluid parameters, and generate the normalized dynamic SEC baseline value by combining the current load rate, ambient temperature and wind speed through the operating condition normalization model.
[0026] Furthermore, the current wind turbine shaft power is read from the central data processing unit. With unit load rate Combined with the design maximum steam flow rate Calculate the current exhaust steam mass flow rate. ; in accordance with and Calculate the original standardized energy consumption coefficient The formula is: ; Because the original standardized energy consumption coefficient is affected by non-pollution factors, a normalized operating condition model is constructed. Based on load factor Ambient temperature and wind speed Input: Normalization correction factor ; Will and Multiply to generate a normalized dynamic SEC benchmark value. The expression is: ; in, For the function Output operating condition correction factor, Original standardized energy consumption coefficient, This is a normalized SEC benchmark value that only reflects the deterioration of heat exchange performance.
[0027] It should be noted that by introducing a normalized operating condition model based on load rate, ambient temperature, and wind speed, the original standardized energy consumption coefficient is corrected to a normalized dynamic SEC benchmark value that only reflects the deterioration of heat exchange performance. This fundamentally eliminates the interference of unit operating condition variations on the SEC index, making the SEC index truly comparable across time periods and operating conditions. This lays a scientific foundation for achieving objective and stable quantitative assessment of dirt and grime status and improves the accuracy and robustness of flushing decisions.
[0028] S3. After spatiotemporally aligning the normalized dynamic SEC baseline value with the visual perception data, input it into the multimodal representation learning network to output a high-dimensional enhanced SEC state vector.
[0029] Furthermore, the infrared thermal imager will be used in real time. The acquired image and the image at the same time Perform time alignment; The image is divided into sections based on the physical structure of the air-cooled island. Each logical sector, for each sector Extraction average temperature with temperature standard deviation ; Will , With the global Concatenate them into a three-dimensional feature matrix; The 3D feature matrix is input into a pre-trained multimodal representation learning network. This network integrates convolutional coding and cross-modal attention mechanisms, and its output dimension is... High-dimensional augmented SEC state vector ; The high-dimensional enhanced SEC state vector characterizes the overall heat transfer degradation and local ash accumulation unevenness.
[0030] It should be noted that by aligning the normalized SEC baseline value with the infrared image in time and space, and using a multimodal representation learning network that integrates convolutional coding and cross-modal attention mechanisms to generate a high-dimensional enhanced SEC state vector, not only is the global heat transfer performance degradation information preserved, but the non-uniform distribution characteristics of local dust accumulation on the tube bundle surface can also be accurately captured. This breaks through the limitation of traditional single scalar SEC in being unable to identify spatial differences in dirt, and provides a high-resolution state basis for subsequent zoned differentiated flushing.
[0031] S4. Construct a time series sample set based on the normalized dynamic SEC benchmark values continuously generated within the historical period and the high-dimensional enhanced SEC state vectors corresponding to the dynamic SEC benchmark values.
[0032] Furthermore, it continuously records the data generated in each round over the past several hours at a fixed sampling period. and ,in For time step index; The sequences are arranged in chronological order, and a sliding window mechanism is used with a window length of [value missing]. Generate multiple consecutive samples, each containing A series of time steps Yes, it constitutes a structured time series sample set.
[0033] It should be noted that by recording historical SEC baseline values and high-dimensional state vectors with a fixed sampling period and constructing a structured time series sample set using a sliding window mechanism, the temporal dependence and spatial dynamic characteristics in the process of contamination evolution are effectively preserved. This provides high-quality, high-dimensional training and inference input for the time series prediction model, enhancing the modeling ability and generalization performance for future SEC deterioration trends.
[0034] S5. Input the time series sample set into the time series evolution prediction model to predict the SEC evolution trend within the preset time window.
[0035] Furthermore, the time series sample set is input into a time series evolution prediction model based on a structured state space model; The time-series evolution prediction model learns the hidden dynamic processes of dirt accumulation and outputs future... SEC forecasts at each time step With state vector ,in ; To enhance decision-making sensitivity to persistent deterioration trends, a trend enhancement mechanism is introduced, defining an effective SEC evolution value. The formula is: ; in, For the first The normalized SEC value predicted by step. This is the current measured normalized SEC value. This is the trend enhancement coefficient, with a value ranging from 0 to 0.3. This is the effective SEC value after trend weighting.
[0036] It should be noted that by introducing a time-series evolution prediction mechanism based on a structured state-space model and combining it with a trend enhancement formula to weight and correct the prediction results, the system can not only predict the future value of SEC, but also actively identify and amplify the continuous deterioration trend, thereby providing early warning of accelerated fouling risks and providing a more sensitive and reliable decision-making basis for the forward-looking selection of flushing windows, avoiding power generation efficiency losses due to response lag.
[0037] S6. Calculate the comprehensive resource cost for each candidate flushing time by combining the SEC evolution trend, real-time electricity price information, demineralized water unit price and short-term weather forecast.
[0038] Furthermore, for each candidate moment... According to the effective SEC value Compared with design benchmark value Deviation calculation of power generation loss cost The formula is: ; in, This represents the power generation revenue loss coefficient corresponding to a unit SEC degradation. The design SEC baseline value for the air-cooled island under clean conditions; Based on the required water pump power for rinsing runtime and real-time electricity price Calculate electricity consumption cost ,in, Real-time electricity price at the candidate time. The rated power of the flushing water pump, This refers to the standard duration of a single rinse. According to water consumption Price per unit of demineralized water Calculate water consumption cost ,in, This is the standard water consumption for a single flush. This refers to the unit price of demineralized water. Introducing meteorological risk correction factors Based on the probability of rainfall With wind speed A decision is defined as: ; in , To preset weights, This is the critical wind speed. For indicator functions, For weather forecast times The probability of rainfall, Forecast wind speed for the corresponding time; Comprehensive resource cost The expression is: ; in, For meteorological risk correction factors, For electricity consumption costs, For water consumption costs, The comprehensive resource cost of the candidate time.
[0039] It should be noted that by deeply integrating the SEC evolution trend with real-time electricity prices, demineralized water unit prices and weather forecasts, a comprehensive resource cost model including power generation losses, hydropower consumption and weather risks is constructed. Furthermore, a weather correction factor is introduced to dynamically adjust the flushing priority, achieving a decision-making leap from technical feasibility to economic optimization. This ensures that flushing behavior, while guaranteeing unit efficiency, also minimizes operating costs and operational feasibility, thereby improving the overall economic efficiency of the power plant.
[0040] S7. Based on the result of minimizing the overall resource cost, determine the optimal flushing execution time and flushing parameters, and generate flushing control instructions to send to the flushing execution platform.
[0041] Furthermore, iterate through all candidate moments. corresponding Select to make Minimum moment As the optimal time to perform flushing; Read the predicted high-dimensional enhanced SEC state vector corresponding to the optimal flushing execution time. After normalizing each component of the predicted high-dimensional enhanced SEC state vector corresponding to the time step, a threshold is set. Identify and satisfy sector index set As the target flushing area; Based on each sector in the target flushing area The value is used to calculate the flushing intensity weight, and the formula is: ; in, Represents the high-dimensional augmented SEC state vector The corresponding number in the middle Component values of each sector This indicates the set of target sectors that need to be flushed. As an indicator of dirt and grime; The flushing water pressure and spray density for each area are set according to the flushing intensity weight; The optimal moment Region set Weight The commands are encapsulated as structured control instructions and sent to the rinsing execution platform via industrial communication protocols to drive the automatic rinsing equipment to perform precise zoned operations, thus completing data-driven closed-loop control.
[0042] It should be noted that by determining the optimal flushing time with the goal of minimizing comprehensive resource costs, and by identifying severely soiled areas based on high-dimensional SEC state vectors and calculating the flushing intensity weights for each zone, a structured control command containing time, area, and parameters is finally generated. This achieves a closed-loop control across the entire chain from data perception and intelligent analysis to physical execution, transforming the flushing operation from extensive full-coverage to precise operation based on demand, area, and intensity. This significantly reduces water and electricity waste, while extending the equipment cleaning cycle and improving the long-term operational stability of the air-cooled island.
[0043] This embodiment also provides a computer device applicable to the data processing method of an air-cooled island flushing system based on SEC, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the data processing method of an air-cooled island flushing system based on SEC as proposed in the above embodiment.
[0044] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device's casing, or an external keyboard, touchpad, or mouse.
[0045] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the data processing method for the SEC-based air-cooled island flushing system as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.
[0046] In summary, this invention effectively eliminates the interference of non-pollution factors such as load, ambient temperature, and wind speed on energy consumption assessment by introducing a normalized dynamic SEC benchmark value under operating conditions. This accurately reflects the degree of heat exchange performance degradation in the air-cooled island. By combining infrared visual perception data with a multimodal characterization learning network, it achieves a high-dimensional and accurate characterization of the overall and local dust accumulation state. Furthermore, it predicts the SEC degradation trend based on a time-series evolution prediction model and integrates electricity price, water price, and meteorological information to construct a comprehensive resource cost model. This enables the intelligent determination of the optimal flushing time and zone flushing parameters under all operating conditions, improving the foresight, accuracy, and economy of flushing decisions. Ultimately, it achieves the intelligent operation goal of saving water, saving electricity, and improving efficiency.
[0047] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A data processing method for an air-cooled island flushing system based on SEC, characterized in that: include: Collect thermal parameters, fluid parameters, environmental parameters, and visual perception data generated during the operation of the air-cooled island; The original standardized energy consumption coefficient is calculated based on thermal and fluid parameters, and a normalized dynamic SEC baseline value is generated by combining the current load rate, ambient temperature and wind speed through the operating condition normalization model. After spatiotemporally aligning the normalized dynamic SEC baseline value with the visual perception data, the data is input into a multimodal representation learning network, which outputs a high-dimensional enhanced SEC state vector. A time series sample set is constructed based on the normalized dynamic SEC baseline value and the high-dimensional enhanced SEC state vector corresponding to the dynamic SEC baseline value, which are continuously generated within the historical period. Input the time series sample set into the time series evolution prediction model to predict the SEC evolution trend within a preset time window in the future; By combining the SEC evolution trend, real-time electricity price information, demineralized water unit price and short-term weather forecast, the comprehensive resource cost of each candidate flushing time is calculated; Based on the result of minimizing the overall resource cost, the optimal flushing execution time and flushing parameters are determined, and flushing control commands are generated and sent to the flushing execution platform.
2. The data processing method for the SEC-based air-cooled island flushing system as described in claim 1, characterized in that: The specific steps for collecting thermal parameters, fluid parameters, environmental parameters, and visual perception data generated during the operation of the air-cooled island are as follows: Temperature sensors are installed in the exhaust steam inlet pipe and cooling air outlet duct of the air-cooled island to obtain the exhaust steam temperature and cooling air outlet temperature. An air volume meter is installed at the air inlet of the fan to measure the volumetric flow rate of the cooling air, and a pressure transmitter is installed at the back pressure measuring point to collect the current back pressure value. Meteorological stations are deployed around the air-cooled island to simultaneously acquire ambient temperature, relative humidity and wind speed. An infrared thermal imager is installed on the track above the air-cooled island to periodically scan the surface of each sector tube bundle and generate an infrared image sequence with spatial coordinates. All devices are connected to the central data processing platform via an industrial communication bus to achieve multi-source data time synchronization and preliminary calibration.
3. The data processing method for the SEC-based air-cooled island flushing system as described in claim 2, characterized in that: The steps for calculating the original standardized energy consumption coefficient based on thermodynamic and fluid parameters, and generating a normalized dynamic SEC baseline value through a normalized operating condition model, combined with the current load rate, ambient temperature, and wind speed, are as follows: Read the current wind turbine shaft power from the central data processing unit. With unit load rate Combined with the design maximum steam flow Calculate the current exhaust steam mass flow rate. ; in accordance with and Calculate the original standardized energy consumption coefficient The formula is: ; Because the original standardized energy consumption coefficient is affected by non-pollution factors, a normalized operating condition model is constructed. Based on load factor Ambient temperature and wind speed Input: Normalization correction factor ; Will and Multiply to generate a normalized dynamic SEC benchmark value. The expression is: ; in, For the function Output operating condition correction factor, Original standardized energy consumption coefficient, This is a normalized SEC benchmark value that only reflects the deterioration of heat exchange performance.
4. The data processing method for the SEC-based air-cooled island flushing system as described in claim 3, characterized in that: The steps for spatiotemporally aligning the normalized dynamic SEC baseline value with visual perception data and then inputting it into the multimodal representation learning network to output a high-dimensional enhanced SEC state vector are as follows: Infrared thermal imager at all times The acquired image and the image at the same time Perform time alignment; The image is divided into sections based on the physical structure of the air-cooled island. Each logical sector, for each sector Extraction average temperature with temperature standard deviation ; Will , With the global Concatenate them into a three-dimensional feature matrix; The 3D feature matrix is input into a pre-trained multimodal representation learning network. This network integrates convolutional coding and cross-modal attention mechanisms, and its output dimension is... High-dimensional augmented SEC state vector ; The high-dimensional enhanced SEC state vector characterizes the overall heat transfer degradation and local ash accumulation unevenness.
5. The data processing method for the SEC-based air-cooled island flushing system as described in claim 4, characterized in that: The specific steps for constructing a time series sample set based on the normalized dynamic SEC baseline values continuously generated within historical periods and the high-dimensional enhanced SEC state vectors corresponding to the dynamic SEC baseline values are as follows: Continuously record the data generated in each round over the past several hours at a fixed sampling period. and ,in For time step index; The sequences are arranged in chronological order, and a sliding window mechanism is used with a window length of [value missing]. Generate multiple consecutive samples, each containing A series of time steps Yes, it constitutes a structured time series sample set.
6. The data processing method for the SEC-based air-cooled island flushing system as described in claim 5, characterized in that: The specific steps for inputting the time series sample set into the time series evolution prediction model to predict the SEC evolution trend within a preset time window are as follows: Input the time series sample set into the time series evolution prediction model based on the structured state space model; The time-series evolution prediction model learns the hidden dynamic processes of dirt accumulation and outputs future... SEC forecasts at each time step With state vector ,in ; To enhance decision-making sensitivity to persistent deterioration trends, a trend enhancement mechanism is introduced, defining an effective SEC evolution value. The formula is: ; in, For the first The normalized SEC value predicted by step. This is the current measured normalized SEC value. This is the trend enhancement coefficient, with a value ranging from 0 to 0.
3. This is the effective SEC value after trend weighting.
7. The data processing method for the SEC-based air-cooled island flushing system as described in claim 6, characterized in that: The method of combining SEC evolution trends, real-time electricity price information, demineralized water unit price, and short-term weather forecasts to calculate the comprehensive resource cost for each candidate flushing time involves the following steps: For each candidate time According to the effective SEC value Compared with design benchmark value Deviation calculation of power generation loss cost The formula is: ; in, This represents the power generation revenue loss coefficient corresponding to a unit SEC degradation. The design SEC baseline value for the air-cooled island under clean conditions; Based on the required water pump power for rinsing runtime and real-time electricity price Calculate electricity consumption cost ,in, Real-time electricity price at the candidate time. The rated power of the flushing water pump, This refers to the standard duration of a single rinse. According to water consumption Price per unit of demineralized water Calculate water consumption cost ,in, This is the standard water consumption for a single flush. This refers to the unit price of demineralized water. Introducing meteorological risk correction factors Based on the probability of rainfall With wind speed A decision is defined as: ; in , To preset weights, This is the critical wind speed. For indicator functions, For weather forecast times The probability of rainfall, Forecast wind speed for the corresponding time; Comprehensive resource cost The expression is: ; in, For meteorological risk correction factors, For electricity consumption costs, For water consumption costs, The total resource cost of the candidate time.
8. The data processing method for the SEC-based air-cooled island flushing system as described in claim 7, characterized in that: The steps for determining the optimal flushing execution time and flushing parameters based on minimizing the overall resource cost, and generating flushing control commands to send to the flushing execution platform are as follows: Traverse all candidate moments corresponding Select to make Minimum moment As the optimal time to perform flushing; Read the predicted high-dimensional enhanced SEC state vector corresponding to the optimal flushing execution time. After normalizing each component of the predicted high-dimensional enhanced SEC state vector corresponding to the time step, a threshold is set. Identify and satisfy sector index set As the target flushing area; Based on each sector in the target flushing area The value is used to calculate the flushing intensity weight, and the formula is: ; in, Represents the high-dimensional augmented SEC state vector The corresponding number in the middle Component values of each sector This indicates the set of target sectors that need to be flushed. As an indicator of dirt and grime; The flushing water pressure and spray density for each area are set according to the flushing intensity weight; The optimal moment Region set Weight The commands are encapsulated as structured control instructions and sent to the rinsing execution platform via industrial communication protocols to drive the automatic rinsing equipment to perform precise zoned operations, thus completing data-driven closed-loop control.
9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the data processing method for the SEC-based air-cooled island flushing system as described in any one of claims 1 to 8.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the data processing method for the SEC-based air-cooled island flushing system as described in any one of claims 1 to 8.