Intelligent filtering system for cooling water of nuclear power station and self-cleaning control method

Abstract

The invention discloses a nuclear power station cooling water intelligent filtration system and a self-cleaning control method, and relates to the technical field of cooling water filtration, the nuclear power station cooling water intelligent filtration system comprises a detection unit, a filtration unit, a self-cleaning unit, a control unit and a pipeline connection assembly, and the core is that the detection unit collects water flow, suspended matter concentration, radioactive intensity, temperature and other parameters according to priority; a water body fluctuation model is arranged in the control unit, water body flow serves as a first priority, logic analysis such as parameter preprocessing, different unit fitting calculation and action node threshold set generation is completed through cooperation of multiple modules, and regulation and control actions such as water body closure and back flushing are dynamically triggered; the problems that a conventional regular cleaning mode is poor in timeliness and cannot adapt to impurity generation amount fluctuation are optimized, self-adaptive cleaning according to real-time fluctuation of water body parameters is achieved, stable operation of a filtering system is guaranteed, and the filtering efficiency and the intelligent level of system operation and maintenance are improved.

Description

Technical Field

[0001] This invention relates to the field of cooling water filtration technology, specifically to an intelligent cooling water filtration system and self-cleaning control method for nuclear power plants. Background Technology

[0002] The key function of cooling water filtration systems is to remove suspended solids, salts, heavy metals, or biological impurities to meet emission standards. Conventional filtration methods include reverse osmosis, evaporation crystallization, and membrane separation. However, for cooling water used in nuclear power plants, the main concerns are radioactive substances and corrosive ions, which make the filtration system significantly different from conventional cooling water systems.

[0003] Given that nuclear power plant cooling water is mostly seawater, desalination is an essential step. Nuclear power plant cooling water may have its radionuclide deposition accelerated by adding precipitants. Further explanation is needed: Firstly, salt crystals accumulate more easily and are mixed with radionuclide deposits and solid impurities. Whether using sedimentation, evaporation, or membrane technology, it is crucial to remove these deposits. The specific reasons include the following: 1. If impurities are not removed, these radioactive substances will accumulate with the circulating cooling water, increasing the system's radioactivity and raising the difficulty of subsequent treatment and environmental risks; 2. Impurities (such as chloride ions and dissolved oxygen) can accelerate the electrochemical corrosion of metal pipes. Especially in high water temperature (40–50℃) environments, copper / brass pipes are prone to oxygen corrosion. Corrosion products (such as iron oxides) can further form scale, exacerbating equipment wear and even leading to perforation and leakage. Alternatively, dense crystalline scale (such as calcium carbonate) can be deposited on the heat exchange surface. Scale formation reduces heat exchange efficiency and increases power consumption.

[0004] In addition to the above, because the amount of impurities generated is difficult to control, especially given the varying degrees of impact on different filtration processes, if methods such as periodic impurity cleaning are used, a significant increase in impurity production at a certain time, if not cleaned in time, may lead to the aforementioned problems. This invention proposes a solution to this problem. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent filtration system and self-cleaning control method for cooling water in nuclear power plants. In the process of removing impurities in the filtration of cooling water in nuclear power plants, the degree of impact of impurities varies in different filtration processes, especially the amount of impurities generated. If a periodic removal method is adopted, the filtration process or equipment may be affected by the time difference in impurity removal.

[0006] The objective of this invention can be achieved through the following technical solution: a smart filtration system for cooling water in nuclear power plants, comprising a detection unit, a filtration unit, a self-cleaning unit, a control unit, and pipeline connection components. The detection unit is connected to the cooling water pipeline and is used to collect water parameters of the cooling water. The filtration unit is used to perform impurity filtration actions related to the cooling water. The self-cleaning unit is linked with the filtration unit and is used to remove impurities attached to the filtration unit. The control unit has control over the signals of the detection unit, the filtration unit, and the self-cleaning unit, and controls the start-up and operation of the self-cleaning unit based on the data collected by the detection unit. A water fluctuation model is also established in the control unit. In the water wave model, action node threshold sets are formed based on water parameters, and control actions are generated based on the action node threshold sets. The control actions include water interception stage and water flushing stage.

[0007] A smart filtration system and self-cleaning control method for cooling water in nuclear power plants are disclosed. The water parameters include water radioactivity, suspended solids concentration, water temperature, and water flow rate. Multiple filtration components are provided in the filtration unit, and each filtration component has an independent interface with the self-cleaning unit. A detection unit is applied at the independent interface.

[0008] The self-cleaning unit is further configured to include a backwashing structure and a collection structure. The backwashing module is used to introduce a backwashing medium into the filter unit to remove attached impurities, and the collection module is used to temporarily store the impurities removed during the self-cleaning process.

[0009] The control unit is further configured to include a parameter threshold feedback module for the associated water body fluctuation model, a multi-node logic analysis module, a parameter analysis and prediction module, and an anomaly handling module. The parameter threshold feedback module is used to collect water body parameters and form a parameter set. The multi-node logic analysis module preprocesses the parameter set and sends it to the parameter analysis and prediction module. The parameter analysis and prediction module performs heterogeneous unit fitting calculations based on the parameter set fed back by the multi-node logic analysis module to obtain the time difference, and forms an action node threshold set by combining multiple time differences, and generates data consistency in the action node threshold set.

[0010] The parameters are further configured such that the priority order for collecting each parameter in the water body parameters is as follows: water flow rate, suspended solids concentration in the water body, radioactivity in the water body, and water temperature. The detection unit is also configured with a collection period Z, where Z is a time unit and a relative variable.

[0011] The configuration is further defined as follows: in the parameter analysis and prediction module, the peak values ​​of the water parameters before and after the collection period are obtained, and the positive and negative fluctuation rates of the water flow rate and the concentration of suspended solids in the water are obtained. The obtained positive and negative fluctuation rates are recorded into the action node threshold set and entered into the anomaly handling module. The execution process of the control action is determined according to the positive and negative fluctuation rate of the water flow rate. Then, the execution order of the water interception stage and the water flushing stage is determined according to the concentration of suspended solids in the water and the water temperature.

[0012] Further settings include: after completing the adjustment action, the acquisition period Z is changed again according to the data consistency, and the parameter threshold feedback module is re-entered to repeat the heterogeneous unit fitting calculation, and historical data is synchronously acquired in the control unit, and the historical data is used as the reference data in the multi-node logic analysis module.

[0013] The present invention has the following beneficial effects: 1. Regarding the impurity removal process during the continuous filtration of cooling water, it no longer relies on a fixed cleaning cycle, but triggers the cleaning action based on real-time fluctuations in parameters such as water flow rate and suspended solids concentration. Whether it is a sudden increase in impurities at a certain time or the filter components show signs of clogging, the system can respond quickly, avoiding problems such as the accumulation of radioactive materials, pipe corrosion, or decreased heat exchange efficiency caused by untimely cleaning. This allows the impurity cleaning to be precise and meet actual needs. The overall cleaning process is as follows: by dynamically adjusting the water interception flow rate and backwash parameters, the self-cleaning process is completed in the most suitable way. 2. Based on the above, this invention forms a closed-loop control process with a parameter threshold feedback module, a multi-node logic analysis module, a parameter analysis and prediction module, an anomaly handling module, execution of control actions, and data feedback correction. The detection unit collects data according to the priority of "water flow rate > suspended solids concentration > radioactivity intensity > temperature", focusing on ensuring the monitoring accuracy of key parameters. The control unit can automatically adapt to water quality changes under different working conditions through logic such as heterogeneous unit fitting calculation and data consistency analysis. Whether it is the high salinity of seawater or the impurity interception requirements of different filtration components, the control strategy can be flexibly adjusted without manual intervention. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the operation of the intelligent filtration system for nuclear power plant cooling water proposed in this invention; Figure 2 This is a schematic diagram of the operation of the intelligent filtration system and self-cleaning control method for nuclear power plant cooling water proposed in this invention. Detailed Implementation

[0016] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1: Regarding the impurity removal process in the cooling water filtration process of nuclear power plants, the degree of impact of impurities varies in different filtration processes, especially the amount of impurities generated. If a periodic removal method is adopted, the filtration process or equipment may be affected by the time difference in impurity removal. The following technical solution is proposed to address this issue: Reference Figure 1 The intelligent filtration system for cooling water in nuclear power plants includes a detection unit, a filtration unit, a self-cleaning unit, a control unit, and pipeline connection components. The detection unit is connected to the cooling water pipeline and is used to collect water parameters of the cooling water. The filtration unit is used to perform impurity filtration actions related to the cooling water. The self-cleaning unit is linked with the filtration unit and is used to remove impurities attached to the filtration unit. The control unit has the control authority over the signals of the detection unit, the filtration unit, and the self-cleaning unit, and controls the start and operation of the self-cleaning unit based on the data collected by the detection unit. A water fluctuation model is also established in the control unit. In the water wave model, action node threshold sets are formed based on water parameters, and control actions are generated based on the action node threshold sets. The control actions include water interception stage and water flushing stage.

[0018] Basic Structure Description: A brief explanation of the cooling water filtration system: Its essence is based on physical or chemical methods such as membrane separation, evaporation, and chemical removal. The key purpose is to remove soluble, slightly soluble, and insoluble impurities. Specifically, the pipelines and treatment equipment are laid out according to the actual situation. This invention takes the detection unit, filtration unit, and pipeline connection components as examples. The detection unit is mostly a sensor dedicated to various parameters, while the filtration unit is determined according to the requirements of the cooling water composition. The pipeline connection components are mostly various valve bodies. These parts are not described in detail in this invention. Since this invention is mainly aimed at nuclear power plant cooling water, there is still a radioactivity problem even without contact with the nuclear core. Therefore, a dedicated radioactivity sensor must be added to the detection unit. In addition, since nuclear power plant cooling water is mostly seawater with a relatively high salinity, even without considering insoluble impurities, the precipitated salt crystals still pose problems such as blockage / corrosion. Therefore, a backwashing self-cleaning process must be adopted for the filtration unit. However, there is a problem: if a periodic cleaning method is used, there is a problem of poor timeliness. Therefore, the key content of this invention is to regulate according to the fluctuation process of water parameters. The key function of the regulation action is to use two types of methods: interception (reducing the cooling water flow rate) and water backwashing (backwashing the filter screen structure in the filter unit).

[0019] Example 2: The self-cleaning control method in Example 1 will be described in detail: Reference Figure 2 The water parameters include water radioactivity, suspended solids concentration, water temperature, and water flow rate. Multiple filter components are set in the filtration unit, and each filter component has an independent interface with the self-cleaning unit. The detection unit is applied at the independent interface. The self-cleaning unit is equipped with a backwashing structure and a collection structure. The backwashing module is used to introduce backwashing medium into the filtration unit to remove attached impurities, and the collection module is used to temporarily store the impurities removed during the self-cleaning process.

[0020] Basic Principle Explanation: One of the key aspects of this invention lies in the placement of the filter component relative to the detection component. This invention primarily uses an independent interface. After the cooling water passes through the filter component, water parameters are acquired in real time. In this invention, these parameters are represented as water flow rate F, suspended solids concentration S, radioactivity intensity I, and temperature T. If there are impurities clogging the filter component, it will inevitably affect the water flow rate. Therefore, this invention prioritizes the water flow rate as the first parameter. The acquisition priority is as follows: acquisition is performed in the order of "water flow rate > suspended solids concentration > radioactivity intensity > temperature," prioritizing the real-time performance of key parameters. Thus, the parameter set should be represented as: (F1 / S1 / I1 / T1, F2 / S2 / I2 / T2…Fn / Sn / In / Tn), where n only represents the time unit.

[0021] Example 3: Supplementary explanation regarding the overall self-cleaning process: The control unit includes a parameter threshold feedback module for the associated water body fluctuation model, a multi-node logic analysis module, a parameter analysis and prediction module, and an anomaly handling module. The parameter threshold feedback module is used to collect water body parameters and form a parameter set. The multi-node logic analysis module preprocesses the parameter set and sends it to the parameter analysis and prediction module. The parameter analysis and prediction module performs heterogeneous unit fitting calculations based on the parameter set fed back by the multi-node logic analysis module to obtain the time difference. Multiple time differences are combined to form an action node threshold set, and data consistency is generated within this threshold set. The priority order for collecting various water parameters is as follows: water flow rate, suspended solids concentration, radioactivity, and water temperature. A collection period Z is set in the detection unit, where Z is a time unit and a relative variable. The parameter analysis and prediction module obtains the initial and subsequent peak values ​​of water parameters within the collection period, and calculates the water flow rate and suspended solids concentration. The positive and negative fluctuation rates of suspended solids concentration are recorded and entered into the action node threshold set and the anomaly handling module. The execution process of the control action is determined based on the positive and negative fluctuation rates of water flow. Then, the execution order of the water interception stage and the water flushing stage is determined based on the suspended solids concentration and water temperature in the water. After the control action is completed, the acquisition period Z is changed again according to the data consistency, and the heterogeneous unit fitting calculation is repeated in the parameter threshold feedback module. Historical data is synchronously acquired in the control unit and used as reference data in the multi-node logic analysis module.

[0022] Solution Description: The parameter threshold set feedback module is associated with the detection unit. The multi-node logic analysis module mainly extracts corrupted data from the acquired action node threshold sets to avoid affecting the fitting calculation process in the parameter analysis and prediction module. First, a sampling period Z is preset, and the peak values ​​of the water parameters before and after the sampling period Z are obtained. Taking the water flow rate F as an example, Fmax and Fmin are set. The time difference is calculated as ΔF=|Fmax-Fmin| / Δt, where |Fmax-Fmin| is the absolute value, and Δt represents the time difference between the peak value before and after the peak value. Although the time difference is the absolute value, it can be fed back as positive and negative fluctuation rates according to the changes in the water flow rate in a single sampling period Z. Thus, the threshold set of action nodes is (ΔF, ΔS, ΔI, ΔT), where each time difference corresponds to a control action node. Because this invention primarily targets the cleaning process that addresses blockages caused by impurities, it uses water flow rate F as a key parameter, and generates the following process in the anomaly handling module: S1: Obtain the time difference of water flow rate in a single acquisition period Z and set it as ΔF. Z If ΔF Z The presence of negative fluctuations indicates an anomaly in the water body during the collection period. Based on the overall filtration system settings, the fluctuation range (A~B) for the time-dependent difference in water flow is defined, and three judgment levels are established within this range: A~A1, A1~B1, and B1~B, where A < A1 < B1 < B. This is used to determine the ΔF... ZSubstituting the values ​​into the fluctuation threshold, we can initially determine the three levels of minor, moderate, and severe water body anomalies. S2: If a severe water quality anomaly is detected, control measures will be implemented directly, starting with a water interception phase to reduce the cooling water flow rate, followed by a water flushing phase. If a mild or moderate water quality anomaly is detected, the time difference value ΔF from the previous data collection cycle Z needs to be retrieved. Z-1 Data consistency is calculated based on the difference between two timeliness values, according to ΔF. Z and ΔF Z-1 The positive difference between the values ​​determines the execution order of the control actions, and a stable interval (C~D) is preset in the data consistency, as shown below: S2-1: If there are minor water quality anomalies, ΔF is not considered. Z and ΔF Z-1 The positive difference between them allows for the execution of the water interception stage without entering the water flushing stage; S2-2: If a moderate water quality anomaly exists, ΔF Z and ΔF Z-1 When the positive difference between the two values ​​is greater than 0 and is located in or exceeds the stable range, the water flushing stage should be carried out first and the water interception stage can be skipped. S2-3: If a moderate water quality anomaly exists, ΔF Z and ΔF Z-1 When the positive difference between the two is less than 0 and is within the stable range, the water interception stage is carried out first, followed by the water flushing stage; if it exceeds the stable range, the water interception stage is carried out simultaneously with the water flushing stage.

[0023] After completing the control actions according to S2-1~S2-3, further based on ΔF Z and ΔF Z-1 The positive difference between the two values ​​is used to determine the acquisition cycle time. If the positive difference is less than 0, the acquisition cycle time is shortened. If the positive difference is greater than 0, the acquisition cycle time remains unchanged or is increased.

[0024] In summary, the system comprises a detection unit, a filtration unit, a self-cleaning unit, a control unit, and piping connection components. The core functionality involves the detection unit prioritizing parameters such as water flow rate, suspended solids concentration, radioactivity intensity, and temperature. The control unit incorporates a water fluctuation model, with water flow rate as the highest priority. Through multi-module collaboration, it performs parameter preprocessing, heterogeneous unit fitting calculations, and action node threshold set generation, dynamically triggering control actions such as water interception and backwashing. This optimizes conventional periodic cleaning methods, addressing their poor timeliness and inability to adapt to fluctuations in impurity levels. It achieves adaptive cleaning based on real-time fluctuations in water parameters, ensuring stable operation of the filtration system and improving filtration efficiency and the intelligence level of system maintenance.

[0025] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0026] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0027] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementations. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A smart filtration system for cooling water in a nuclear power plant, characterized in that, The system includes a detection unit, a filtration unit, a self-cleaning unit, a control unit, and pipeline connection components. The detection unit is connected to the cooling water pipeline and is used to collect water parameters of the cooling water. The filtration unit is used to perform impurity filtration actions related to the cooling water. The self-cleaning unit is linked with the filtration unit and is used to remove impurities attached to the filtration unit. The control unit has the control authority over the signals of the detection unit, the filtration unit, and the self-cleaning unit, and controls the start and operation of the self-cleaning unit according to the data collected by the detection unit. A water fluctuation model is also established in the control unit. In the water wave model, action node threshold sets are formed based on water parameters, and control actions are generated based on the action node threshold sets. The control actions include water interception stage and water flushing stage.

2. A smart filtration system and self-cleaning control method for nuclear power plant cooling water, applied in the smart filtration system for nuclear power plant cooling water as described in claim 1, characterized in that, The water parameters include water radioactivity, suspended solids concentration, water temperature, and water flow rate. Multiple filter components are provided in the filtration unit, and each filter component has an independent interface with the self-cleaning unit. The detection unit is applied at the independent interface.

3. The intelligent filtration system and self-cleaning control method for nuclear power plant cooling water according to claim 2, characterized in that, The self-cleaning unit is provided with a backwashing structure and a collection structure. The backwashing module is used to introduce backwashing medium into the filter unit to remove attached impurities, and the collection module is used to temporarily store the impurities removed during the self-cleaning process.

4. The intelligent filtration system and self-cleaning control method for nuclear power plant cooling water according to claim 3, characterized in that, The control unit includes a parameter threshold feedback module for the associated water body fluctuation model, a multi-node logic analysis module, a parameter analysis and prediction module, and an anomaly handling module. The parameter threshold feedback module is used to collect water body parameters and form a parameter set. The multi-node logic analysis module preprocesses the parameter set and sends it to the parameter analysis and prediction module. The parameter analysis and prediction module performs heterogeneous unit fitting calculations based on the parameter set fed back by the multi-node logic analysis module to obtain the time difference, and forms an action node threshold set by combining multiple time differences, and generates data consistency in the action node threshold set.

5. The intelligent filtration system and self-cleaning control method for nuclear power plant cooling water according to claim 4, characterized in that, The priority order of the water parameters is as follows: water flow rate, suspended solids concentration, radioactivity, and temperature. The detection unit is set with a collection period Z, which is a time unit and a relative variable.

6. The intelligent filtration system and self-cleaning control method for nuclear power plant cooling water according to claim 5, characterized in that, The parameter analysis and prediction module obtains the peak values ​​of water parameters before and after the collection period. Based on the peak values ​​before and after the collection period, it feeds back the positive and negative fluctuation rates of water flow and suspended solids concentration in the water. The obtained positive and negative fluctuation rates are entered into the action node threshold set and sent to the anomaly handling module. The execution process of the control action is determined based on the positive and negative fluctuation rate of water flow. Then, the execution order of the water interception stage and the water flushing stage is determined based on the suspended solids concentration and water temperature in the water.

7. The intelligent filtration system and self-cleaning control method for nuclear power plant cooling water according to claim 6, characterized in that, After completing the adjustment action, the acquisition period Z is changed again according to the data consistency, and the heterogeneous unit fitting calculation is repeated in the parameter threshold feedback module. Historical data is also acquired synchronously in the control unit and used as reference data in the multi-node logic analysis module.

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