Industrial silicon circulating cooling water treatment equipment and method

Abstract

The invention discloses industrial silicon circulating cooling water treatment equipment and method, and belongs to the technical field of industrial water treatment. The water quality monitoring unit is arranged on the reaction tank main body and is used for acquiring water quality data; the medicament adding unit is communicated with the reaction tank main body and is used for adding medicaments into the reaction tank main body; the physical cleaning unit is mounted at the top of the reaction tank main body and is used for mechanically cleaning the inner surface of the reaction tank main body; the controller is electrically connected with the water quality monitoring unit, the agent adding unit and the physical cleaning unit and used for controlling operation of the agent adding unit and the physical cleaning unit according to the water quality data. And the conversion from decedent treatment to preventive management is realized.

Description

Technical Field

[0001] This invention relates to the field of industrial water treatment, specifically to an industrial silicon circulating cooling water treatment device and method. Background Technology

[0002] Traditional water treatment technologies face the following limitations in cooling water systems for industrial silicon production:

[0003] Limitations of data collection and analysis: Traditional treatment methods lack real-time, multi-dimensional monitoring of water quality, resulting in managers being unclear about the specific scaling risks and trends of circulating cooling water, and treatment measures are often blind and lack data basis.

[0004] The passive and inefficient nature of the treatment method: It mainly relies on periodic shutdown pickling operations to remove the hardened silica scale that has already formed; this method is a passive and delayed treatment approach, which not only has limited effect of chemical cleaning, but also requires interruption of production, affecting the continuity of production.

[0005] Potential safety and environmental risks: Regular chemical pickling operations can lead to operational safety issues and environmental problems related to chemical disposal.

[0006] The aforementioned problems mainly stem from the lack of effective real-time monitoring and feedback mechanisms and proactive intervention methods in traditional technologies. As a result, when scale problems occur, managers cannot obtain comprehensive information in a timely manner to take precise preventive measures, and can only deal with the issue through shutdown maintenance that affects production, resulting in high costs and low efficiency.

[0007] The information disclosed in the background section above is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0008] The purpose of this invention is to provide an industrial silicon circulating cooling water treatment device and method to solve the problems mentioned in the background art.

[0009] The technical solution of the present invention includes:

[0010] The main body of the reaction vessel;

[0011] A water quality monitoring unit is installed on the main body of the reaction tank to acquire water quality data;

[0012] A reagent dosing unit is connected to the main body of the reaction vessel and is used to add reagents into the main body of the reaction vessel;

[0013] A physical cleaning unit is installed on the top of the reaction vessel body and is used to mechanically clean the inner surface of the reaction vessel body.

[0014] The system includes a controller, which is electrically connected to the water quality monitoring unit, the chemical dosing unit, and the physical cleaning unit, respectively, and is used to control the operation of the chemical dosing unit and the physical cleaning unit based on the water quality data.

[0015] Preferably, a swirling mixing conduit is provided on the inner side of the upper water inlet of the reaction tank body, and the inner wall of the swirling mixing conduit is machined with a spiral guide groove to form a rotating flow field for the incoming water.

[0016] Preferably, the water quality monitoring unit includes a multi-channel sensor integrated flange installed on the side wall of the main body of the reaction tank. The flange integrates a turbidity sensor, a conductivity sensor, a pH sensor, a laser scattering probe, and a temperature sensor for collecting multi-dimensional water quality data.

[0017] Preferably, the reagent dosing unit includes multiple independent reagent storage containers and precision peristaltic pump sets connected to each container respectively. Each peristaltic pump is independently controlled by the controller, and the outlets of all pumps are collected and connected to the reagent injection port of the main body of the reaction vessel.

[0018] Preferably, the physical cleaning unit is an integrated scraping and sampling robotic arm. The robotic arm includes a base that rotates horizontally via a slewing bearing assembly, and a two-stage telescopic arm that extends vertically via a ball screw assembly. The end of the telescopic arm is equipped with a replaceable scraper head and a micro sampling pump.

[0019] A method for treating circulating cooling water for industrial silicon includes the following steps:

[0020] Define a water quality characteristic list, which is acquired in real time by the water quality monitoring unit and includes real-time water quality parameters and real-time water temperature values.

[0021] The controller calculates and generates a real-time scaling risk index based on the water quality characteristic list;

[0022] A first risk event is set, the trigger condition of which is that the real-time scaling risk index exceeds a first preset threshold; when the first risk event is triggered, the controller drives the reagent dosing unit to dynamically decide the reagent ratio and dosing rate based on the composition of the real-time scaling risk index.

[0023] A second risk event is set, the trigger condition of which is that the real-time scaling risk index exceeds a second preset threshold; when the second risk event is triggered, the controller starts the physical cleaning unit to mechanically clean the main body of the reaction tank.

[0024] Preferably, the calculation steps of the real-time scaling risk index are as follows: First, a basic risk value is calculated based on the turbidity, particulate matter size distribution, conductivity and pH value in the real-time water quality parameters; then, a temperature risk gain coefficient is calculated based on the difference between the real-time water temperature value and the reference temperature; finally, the basic risk value and the temperature risk gain coefficient are multiplied to obtain the real-time scaling risk index.

[0025] Preferably, the step of dynamically deciding the reagent ratio and dosage rate is as follows: when the increase in the real-time scaling risk index is mainly contributed by high conductivity, the dosage ratio of scale inhibitor is increased first; when the increase in the real-time scaling risk index is mainly contributed by the increase in the number of micron-sized particles, the dosage of scale inhibitor and dispersant is increased simultaneously.

[0026] Preferably, the triggering condition for the second risk event further includes a predictive triggering condition; the predictive triggering condition is defined as: when the controller analyzes historical data and identifies that the time series change rate of the real-time scaling risk index continuously exceeds the historical average change rate in the short term and forms an accelerating trend, the physical cleaning unit is activated in advance.

[0027] Preferably, the step of activating the physical cleaning unit further includes: instructing the agent dosing unit to increase the amount of stripping agent added; after a preset delay, activating the robotic arm of the physical cleaning unit so that its end scraper head scrapes off the inner wall deposits along a preset path; after scraping is completed, instructing the micro sampling pump at the end of the robotic arm to extract a water sample for evaluating the cleaning effect.

[0028] This invention provides an improved industrial silicon circulating cooling water treatment device and method, which, compared with the prior art, has the following improvements and advantages:

[0029] 1. The core difference of this solution lies in the establishment of a closed-loop control system based on real-time data. Instead of waiting for scale to form before performing regular shutdown cleaning, it uses real-time monitoring and risk index calculation to intervene chemically in the early stages of scaling. Furthermore, it introduces predictive triggering conditions based on the rate of change of the risk index, which can initiate physical cleaning in advance before the scaling problem worsens, realizing the transformation from reactive treatment to preventive management.

[0030] 2. This solution achieves a high degree of targeting. At the chemical intervention level, the controller can analyze the main causes of increased risk. For example, when high conductivity is detected as the dominant factor, the scale inhibitor is preferentially increased; when the increase of micron-sized particles is the dominant factor, both the scale inhibitor and dispersant are increased simultaneously. This dynamic decision-making method for agent ratio ensures the effective use of chemical resources and avoids blind addition. This solution does not simply separate chemical and physical cleaning methods, but pre-treats the scale layer by adding a stripping agent before starting powerful physical cleaning. This chemical-physical synergistic operation process makes subsequent mechanical scraping easier and more effective, improving the overall cleaning efficiency.

[0031] 3. Through proactive prevention and efficient treatment, unplanned or planned downtime for acid washing operations due to severe scaling is effectively avoided, ensuring the continuity of industrial silicon production. At the same time, maintaining the cleanliness of the inner wall of the cooling water system ensures heat exchange efficiency, thereby improving the operational stability of the entire cooling water system. This solution significantly reduces the safety risks associated with chemical handling and the environmental problems caused by waste acid treatment. Attached Figure Description

[0032] The present invention will be further explained below with reference to the accompanying drawings and embodiments:

[0033] Figure 1 This is a schematic diagram of the main body of the reaction vessel;

[0034] Figure 2 This is a schematic diagram of the drug dosing unit;

[0035] Figure 3 This is a schematic diagram of the integrated scraping and sampling robotic arm;

[0036] Figure 4 This is a schematic diagram of the method flow of the present invention.

[0037] In the diagram: 100, main body of the reaction vessel; 110, swirling mixing conduit; 120, multi-channel sensor integrated flange; 130, integrated robotic arm for scraping and sampling; 200, reagent dosing unit; 210, reagent storage container; 220, precision peristaltic pump set. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0039] Example 1

[0040] Please see Figure 1-3 This invention provides an industrial silicon circulating cooling water treatment device, comprising:

[0041] The main body of the reaction vessel is 100.

[0042] A water quality monitoring unit is installed on the main body 100 of the reaction tank to acquire water quality data;

[0043] The reagent dosing unit 200 is connected to the reaction vessel body 100 and is used to add reagents into the reaction vessel body 100.

[0044] A physical cleaning unit is installed on the top of the reaction vessel body 100 and is used to mechanically clean the inner surface of the reaction vessel body 100.

[0045] The controller is electrically connected to the water quality monitoring unit, the chemical dosing unit 200, and the physical cleaning unit, respectively, and is used to control the operation of the chemical dosing unit 200 and the physical cleaning unit according to the water quality data.

[0046] In the industrial silicon production process, the circulating cooling water system is prone to forming hard silica scale on its inner wall due to high water temperature and saturated silicate concentration. During industrial silicon production, amorphous silica particles and high concentrations of silicates inevitably dissolve into the cooling water. Under the combined effects of high temperature and circulating concentration, these dissolved silicates readily undergo polymerization and condensation reactions, while the silica particles become ideal crystal nuclei, ultimately forming a dense, highly adhesive amorphous silica scale. The physical properties of this silica scale are closer to those of glass. Compared with common calcium carbonate scale, it is not only inert to most chemical cleaning agents, but also extremely hard once formed and aged, making mechanical removal extremely difficult. Traditional treatment methods rely on periodic shutdowns for acid washing, which not only affects production continuity but also has limited chemical cleaning effects and poses safety and environmental problems. This embodiment provides an industrial silicon circulating cooling water treatment device. By setting the reaction tank body 100 as the core treatment area, and configuring a water quality monitoring unit, a chemical dosing unit 200, and a physical cleaning unit around it, it aims to solve the aforementioned problems. The water quality monitoring unit functions to perceive the water state in real time, providing a basis for subsequent intervention measures, changing the previous situation of unclear and blind treatment based on water quality conditions. The chemical dosing unit 200 performs chemical pretreatment or inhibition based on the data obtained from the water quality monitoring unit, aiming to intervene in the early stages of scaling. The physical cleaning unit serves as a powerful intervention method to treat deposits that are difficult to handle by chemical methods or that have already formed. The controller organically combines the above units. It receives data from the water quality monitoring unit, processes it through internal algorithms, and issues instructions to the chemical dosing unit 200 and the physical cleaning unit, transforming the entire device from a passive container into a system capable of actively responding to changes in water quality, thereby improving the operational stability of the cooling water system.

[0047] A swirling mixing conduit 110 is provided inside the upper water inlet of the reaction tank body 100. The inner wall of the swirling mixing conduit 110 is machined with a spiral guide groove to make the incoming water flow form a rotating flow field.

[0048] In this embodiment, the swirl mixing conduit 110 is located inside the inlet of the reaction tank body 100 to optimize the water flow pattern entering the reaction tank body 100 and the mixing effect of subsequent reagents. The swirl mixing conduit 110, through spiral guide grooves machined on its inner wall, guides the incoming circulating cooling water tangentially into the tank, thus creating a top-down rotating flow field. This rotating flow field allows the reagents injected by the reagent dosing unit 200 to be rapidly and evenly dispersed throughout the water body by the high-speed rotating water flow. Compared to a simple direct-flow method, this structure utilizes fluid dynamics principles to promote the mixing process, avoiding problems of excessively high or low local concentrations due to uneven reagent mixing, providing a good foundation for the full conduct of subsequent chemical reactions, and improving reagent utilization.

[0049] The water quality monitoring unit includes a multi-channel sensor integrated flange 120 installed on the side wall of the main body 100 of the reaction tank. The flange integrates a turbidity sensor, a conductivity sensor, a pH sensor, a laser scattering probe, and a temperature sensor to collect multi-dimensional water quality data.

[0050] In this embodiment, the water quality monitoring unit is implemented using a multi-channel sensor integrated flange 120. This flange is installed on the side wall of the reaction tank body 100 and integrates various sensors. For example, the turbidity sensor can be the TurbiMaxCUS52D from E+H, the conductivity sensor can be the tecLineCR from JUMO, the pH sensor can be the InPro3250i from Mettler Toledo, the laser scattering probe can be a related probe from Malvern Panaco, and the temperature sensor can be a conventional PT100 type RTD. Integrating these sensors onto a single flange aims to... The system can acquire water quality data synchronously and in real time from multiple dimensions. Turbidity sensors and laser scattering probes are used to obtain the concentration and particle size distribution of suspended particles in the water, which directly reflects the physical amount of scale-forming substances. Conductivity sensors are used to measure the total amount of dissolved ions in the water, which reflects the chemical potential for scaling. pH sensors and temperature sensors are used to obtain key environmental parameters that affect the rate of chemical reactions and the solubility of substances. By collecting this multi-dimensional water quality data, the controller can make a more comprehensive assessment of the scaling risk of the water body, avoiding misjudgments that may be caused by relying on a single parameter, and providing data support for subsequent precise control.

[0051] The reagent dosing unit 200 includes multiple independent reagent storage containers 210 and precision peristaltic pump sets 220 connected to each container respectively. Each peristaltic pump is independently controlled by a controller, and the outlets of all pumps are collected and connected to the reagent injection port of the reaction vessel body 100.

[0052] The chemical dosing unit 200 in this embodiment consists of multiple independent chemical storage containers 210 and a precision peristaltic pump set 220. For example, three storage tanks made of polypropylene can be set up to store scale inhibitors, dispersants, and strippers, respectively. Each storage tank is connected to an independent peristaltic pump driven by a DC motor. The purpose of this design is to achieve precise and independent control of the dosage of different chemicals. The controller can independently adjust the speed of each peristaltic pump according to the water quality analysis results, thereby changing the dosing rate of the corresponding chemical. This ability to control independently is the physical basis for dynamically adjusting the chemical ratio. For example, when the controller determines that the scaling risk is mainly due to excessively high ion concentration, the dosage of scale inhibitor can be increased alone; when it is determined that there is a significant tendency for particulate matter aggregation, the dosage of both scale inhibitor and dispersant can be increased simultaneously. The outlets of all pumps are converged and injected uniformly, ensuring that multiple chemicals can work synergistically. Compared with the traditional single-channel or manual dosing method, this structure makes chemical intervention more targeted and efficient.

[0053] The physical cleaning unit is a robotic arm 130 that integrates scraping and sampling. The robotic arm includes a base that rotates horizontally via a slewing bearing assembly, and a two-stage telescopic arm that extends vertically via a ball screw pair. The end of the telescopic arm is equipped with a replaceable scraper head and a micro sampling pump.

[0054] In this embodiment, the physical cleaning unit is a robotic arm 130 integrating scraping and sampling. The base of this robotic arm is fixed to the top of the reaction vessel body 100. Its horizontal rotation is achieved through a slewing bearing assembly, driven by a stepper motor via a worm gear reducer to achieve 360-degree rotational positioning. Its vertical movement is achieved through a two-stage telescopic arm, with an internal ball screw driven by another stepper motor to control the extension and retraction of the inner and outer arms. This structural design aims to allow the robotic arm's range of motion to cover the entire inner wall of the reaction vessel. A replaceable scraper head, for example made of polytetrafluoroethylene, is installed at the end of the telescopic arm to directly scrape away the silica scale adhering to the wall surface. Simultaneously, a micro-sampling pump integrated at the end extracts water samples from the reaction vessel after the scraping operation. This integrated design not only endows the equipment with powerful physical cleaning capabilities but also provides a means to verify the effectiveness. The controller coordinates the movement of two stepper motors to instruct the robotic arm to scrape the inner wall along a preset trajectory. After scraping, sampling and analysis can be used to evaluate the cleaning effect and provide a basis for subsequent maintenance decisions.

[0055] Example 2

[0056] Please see Figure 4 A method for treating circulating cooling water for industrial silicon includes the following steps:

[0057] Define a water quality characteristic list, which is obtained in real time by the water quality monitoring unit. The list includes real-time water quality parameters and real-time water temperature values.

[0058] The controller calculates and generates a real-time scaling risk index based on a list of water quality characteristics.

[0059] A first risk event is set, the trigger condition of which is that the real-time scaling risk index exceeds a first preset threshold; when the first risk event is triggered, the controller drives the reagent dosing unit 200 to dynamically decide the reagent ratio and dosing rate based on the composition of the real-time scaling risk index.

[0060] A second risk event is set, the trigger condition of which is that the real-time scaling risk index exceeds the second preset threshold; when the second risk event is triggered, the controller starts the physical cleaning unit to mechanically clean the reaction tank body 100.

[0061] This embodiment provides a method for treating industrial silicon circulating cooling water. The method continuously acquires water quality data through a water quality monitoring unit, forming a water quality characteristic list including parameters such as turbidity, conductivity, pH, particulate matter size distribution, and water temperature. Based on this list, the controller calculates a comprehensive real-time scaling risk index, aiming to transform multiple discrete water quality parameters into a single, quantifiable risk indicator. The method further defines two levels of risk events: when the real-time scaling risk index exceeds a lower first preset threshold, a first risk event is triggered, and the controller drives the chemical dosing unit 200 to perform chemical intervention—a preventative and mild control measure. When the index exceeds a higher second preset threshold, a second risk event is triggered, and the controller activates the physical cleaning unit for mechanical cleaning—a powerful intervention measure to address severe scaling risks. Through this hierarchical response mechanism, the method can take appropriate treatment measures according to the severity of the risk, realizing a shift from passive response to proactive management, improving the timeliness of treatment and the efficiency of resource utilization.

[0062] It should be further clarified that the first and second preset thresholds are not fixed universal constants, but rather empirical values ​​that need to be calibrated by those skilled in the art in conjunction with specific application scenarios. The determination method may include: by analyzing the historical operating data and maintenance records of the cooling water system of a specific industrial silicon production line, setting the average risk index corresponding to the historical occurrence of slight scaling as the first preset threshold; and setting the average risk index corresponding to the historical occurrence of scaling affecting heat exchange efficiency and requiring physical or chemical cleaning as the second preset threshold. This calibration method based on historical data and operating experience can ensure the rationality and effectiveness of the threshold setting.

[0063] The calculation steps for the real-time scaling risk index are as follows: First, calculate the basic risk value based on the turbidity, particle size distribution, conductivity and pH value in the real-time water quality parameters; then, calculate the temperature risk gain coefficient based on the difference between the real-time water temperature value and the reference temperature; finally, multiply the basic risk value and the temperature risk gain coefficient to obtain the real-time scaling risk index.

[0064] The purpose of the real-time scaling risk index calculation steps in this embodiment is to establish a mathematical model that can accurately reflect the actual scaling tendency. The calculation process consists of two steps: First, the controller calculates the basic risk value based on turbidity, particulate matter data obtained from the laser scattering probe, conductivity, and pH value. In this calculation, the particulate matter data directly reflects the physical quantity of scaling substances in the water and is the basis for the risk. The conductivity data reflects the concentration of dissolved ions in the water, representing the chemical driving force of scaling, and the controller uses it as a risk amplification factor. At the same time, pH value is a key environmental regulation parameter. When it enters the high-risk range of alkalinity, the controller will increase the weight of the aforementioned data in the calculation. Second, the controller calculates the temperature risk gain coefficient based on the difference between the real-time water temperature and a preset reference temperature. Because the higher the water temperature, the lower the solubility of silicates and the stronger the scaling tendency, this coefficient will increase with the increase of temperature. The calculated basic risk value is multiplied by the temperature risk gain coefficient to obtain the final real-time scaling risk index. The significance of this calculation method lies in the fact that it couples together multiple physical and chemical factors that affect scaling, and in particular, it introduces temperature as a key variable for dynamic correction, making the risk assessment results closer to actual working conditions.

[0065] As one possible, but not limiting, calculation method, the base risk value and temperature risk gain coefficient can be embodied by the following exemplary model;

[0066] The basic risk value can be obtained by weighting and summing the various water quality parameters:

[0067]

[0068] The temperature risk gain coefficient can be calculated using the following linear function:

[0069]

[0070] The real-time scaling risk index is:

[0071]

[0072] in:

[0073] : Represents the final calculated real-time scaling risk index;

[0074] This represents a basic risk value that integrates multiple water quality parameters.

[0075] : These represent empirical weighting coefficients for turbidity, conductivity, particulate matter, and pH, respectively. These coefficients need to be calibrated experimentally based on the on-site water quality characteristics.

[0076] : Represents a processing function that normalizes or transforms the raw readings of each sensor, with the aim of unifying sensor data of different dimensions into a comparable range;

[0077] These represent the real-time turbidity value, conductivity value, particulate matter size distribution data, and pH value obtained by the sensor, respectively.

[0078] : Represents the temperature risk gain coefficient;

[0079] : Represents the temperature effect coefficient, reflecting the degree to which increased temperature exacerbates the risk of scaling, and also needs to be determined through experimental data;

[0080] : Represents the real-time water temperature value obtained by the temperature sensor;

[0081] : Represents a preset reference temperature value, such as the average temperature of the cooling water system under low load and low risk operating conditions;

[0082] Those skilled in the art will understand that the above formula is only an example. In practical applications, more complex nonlinear models can be used, and historical data can be trained using methods such as machine learning to obtain more accurate weights and coefficients.

[0083] The specific steps for dynamically deciding the dosage ratio and dosing rate of the agent are as follows: when the increase in the real-time scaling risk index is mainly contributed by high conductivity, the dosage ratio of scale inhibitor should be increased first; when the increase in the real-time scaling risk index is mainly contributed by the increase in the number of micron-sized particles, the dosage of both scale inhibitor and dispersant should be increased simultaneously.

[0084] The purpose of dynamically deciding on the reagent ratio and dosing rate in this embodiment is to make the addition of chemical reagents more targeted. After triggering the first risk event, the controller does not use a fixed reagent formula, but analyzes the main factors that cause the real-time scaling risk index to increase. For example, when the controller analyzes that the increase in the risk index is mainly contributed by the continuously high conductivity, it indicates that the concentration of dissolved scale-forming ions in the water is too high, which is the main driving force of scaling. At this time, the controller will instruct the reagent dosing unit 200 to prioritize increasing the dosage of scale inhibitor to suppress the precipitation of ions. If the controller analyzes the data from the laser scattering probe and finds that the increase in the risk index is mainly contributed by the sharp increase in the number of micron-sized particles, it indicates that a large number of crystal nuclei have formed in the water and have a tendency to aggregate and grow. At this time, the controller will instruct the reagent dosing unit 200 to simultaneously increase the dosage of scale inhibitor and dispersant. The former is used to inhibit the formation of new crystal nuclei, and the latter is used to coat the existing small particles to prevent them from aggregating and forming larger scale. This method of dynamically adjusting the reagent ratio based on the cause of risk ensures the effective use of chemical resources and improves the accuracy of chemical intervention.

[0085] The triggering conditions for the second risk event also include predictive triggering conditions; predictive triggering conditions are defined as follows: when the controller analyzes historical data and identifies that the time series change rate of the real-time scaling risk index continuously exceeds the historical average change rate in the short term and forms an accelerating trend, the physical cleaning unit is activated in advance.

[0086] The predictive triggering condition for the second risk event in this embodiment aims to achieve early intervention in severe scaling. Besides the direct triggering condition of the real-time scaling risk index exceeding a set second threshold, the controller is also equipped with trend analysis capabilities. The controller continuously records the time-series data of the real-time scaling risk index and calculates and analyzes its rate of change. When the controller detects that the growth rate of the risk index is consistently higher than the average growth rate over a longer period in the short term, and this growth shows an accelerating trend, even if the absolute value of the index has not yet reached the second threshold, the controller will determine in advance that the predictive triggering condition has been met and activate the physical cleaning unit. The significance of this approach is that it allows for intervention before scaling problems become severe and persistent. By identifying the accelerating deterioration trend of the risk, physical scraping can be performed when the scale layer is not yet firmly established. At this stage, the cleaning operation is less difficult and more effective, thus transforming equipment maintenance from a passive, reactive approach to proactive prevention.

[0087] The core logic is that the accelerated rise in the risk index indicates that the scaling process has entered a non-linear rapid growth stage from the linear accumulation stage. At this time, the scale layer is still in a soft state in the early stage of polymerization, which is the best window of opportunity for physical intervention. Intervening at this time can achieve the best cleaning effect with the least mechanical cost and effectively avoid the problem of the scale layer becoming more difficult to remove after further cross-linking and hardening.

[0088] As one possible, but non-limiting, algorithmic implementation, the method for the controller to identify acceleration trends may include: continuously calculating the rate of change of the real-time fouling risk index over two time windows of different lengths, for example, calculating its moving average slope over a shorter time window in the past, such as the most recent hour. And compare it with the slope of the moving average over a longer time window, such as the most recent 24 hours. Comparison; when the controller monitors To multiple consecutive data collection cycles greater than And the difference between the two When the risk index exceeds a preset threshold, it can be determined that the risk index has formed an accelerating deterioration trend, thus meeting the predictive trigger condition. This method provides a specific and actionable quantitative criterion for the concept of an accelerating trend.

[0089] The steps for activating the physical cleaning unit further include: instructing the agent dosing unit 200 to increase the amount of stripping agent added; after a preset delay, activating the robotic arm of the physical cleaning unit so that its end scraper head scrapes away the inner wall deposits along a preset path; after scraping is completed, instructing the micro sampling pump at the end of the robotic arm to extract a water sample for evaluating the cleaning effect.

[0090] The detailed steps for starting the physical cleaning unit in this embodiment are intended to achieve synergistic operation of chemical and physical treatments and to verify the treatment effect. Once the physical cleaning unit is activated, the controller instructs the chemical dosing unit 200 to add a large dose of stripping agent into the reaction tank body 100. This chemical pretreatment softens and loosens the scale layer adhering to the inner wall. After a preset delay to ensure the stripping agent has fully acted, the controller activates the integrated scraping and sampling robotic arm 130. The scraper head of the robotic arm moves along a preset trajectory to mechanically scrape the inner wall. Since the scale layer has been softened, the scraping process is smoother and more thorough. After the scraping operation is completed, the controller instructs the micro sampling pump at the end of the robotic arm to start and extract a mixed water sample from the tank. The purpose of extracting this water sample is to evaluate the effectiveness of the cleaning operation through subsequent laboratory analysis, such as detecting the content of suspended solids removed from the water sample to confirm the cleanliness of the inner wall. This series of steps constitutes a complete chemical softening-physical stripping-sampling verification workflow, ensuring the effectiveness of the cleaning.

[0091] 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.

Claims

1. An industrial silicon circulating cooling water treatment device, characterized in that, include: Reactor body (100); A water quality monitoring unit is installed on the main body (100) of the reaction tank and is used to acquire water quality data; A reagent dosing unit (200) is connected to the reaction vessel body (100) and is used to add reagents into the reaction vessel body (100); A physical cleaning unit is installed on the top of the reaction vessel body (100) for mechanical cleaning of the inner surface of the reaction vessel body (100); The controller is electrically connected to the water quality monitoring unit, the chemical dosing unit (200), and the physical cleaning unit, respectively, and is used to control the operation of the chemical dosing unit (200) and the physical cleaning unit according to the water quality data.

2. The industrial silicon circulating cooling water treatment equipment according to claim 1, characterized in that, The upper inlet of the reaction tank body (100) is provided with a swirling mixing conduit (110), and the inner wall of the swirling mixing conduit (110) is processed with a spiral guide groove to make the incoming water flow form a rotating flow field.

3. The industrial silicon circulating cooling water treatment equipment according to claim 1, characterized in that, The water quality monitoring unit includes a multi-channel sensor integrated flange (120) installed on the side wall of the reaction tank body (100). The flange integrates a turbidity sensor, a conductivity sensor, a pH sensor, a laser scattering probe, and a temperature sensor for collecting multi-dimensional water quality data.

4. The industrial silicon circulating cooling water treatment equipment according to claim 1, characterized in that, The reagent dosing unit (200) includes multiple independent reagent storage containers (210) and precision peristaltic pump sets (220) connected to each container respectively. Each peristaltic pump is independently controlled by the controller, and the outlets of all pumps are combined and connected to the reagent injection port of the reaction vessel body (100).

5. The industrial silicon circulating cooling water treatment equipment according to claim 1, characterized in that, The physical cleaning unit is an integrated scraping and sampling robotic arm (130). The robotic arm includes a base that rotates horizontally via a slewing bearing assembly, and a two-stage telescopic arm that extends vertically via a ball screw pair. The end of the telescopic arm is equipped with a replaceable scraper head and a micro sampling pump.

6. A method for treating circulating cooling water in industrial silicon, applied to an industrial silicon circulating cooling water treatment device according to any one of claims 1 to 5, characterized in that, Includes the following steps: Define a water quality characteristic list, which is acquired in real time by the water quality monitoring unit and includes real-time water quality parameters and real-time water temperature values. The controller calculates and generates a real-time scaling risk index based on the water quality characteristic list; A first risk event is defined, the trigger condition of which is that the real-time scaling risk index exceeds a first preset threshold. When the first risk event is triggered, the controller drives the agent dosing unit (200) to dynamically decide the agent ratio and dosing rate based on the composition of the real-time scaling risk index. A second risk event is set, the trigger condition of which is that the real-time scaling risk index exceeds a second preset threshold. When the second risk event is triggered, the controller activates the physical cleaning unit to perform mechanical cleaning on the reaction vessel body (100).

7. The method for treating industrial silicon circulating cooling water according to claim 6, characterized in that, The calculation steps for the real-time scaling risk index are as follows: First, the basic risk value is calculated based on the turbidity, particulate matter size distribution, conductivity and pH value in the real-time water quality parameters. Then, the temperature risk gain coefficient is calculated based on the difference between the real-time water temperature value and the reference temperature; finally, the real-time scaling risk index is obtained by multiplying the basic risk value by the temperature risk gain coefficient.

8. The method for treating industrial silicon circulating cooling water according to claim 6, characterized in that, The specific steps for dynamically determining the reagent ratio and dosage acceleration rate are as follows: when the increase in the real-time scaling risk index is mainly contributed by high conductivity, the dosage ratio of scale inhibitor is increased first; when the increase in the real-time scaling risk index is mainly contributed by the increase in the number of micron-sized particles, the dosage of both scale inhibitor and dispersant is increased simultaneously.

9. The method for treating industrial silicon circulating cooling water according to claim 6, characterized in that, The triggering conditions for the second risk event also include predictive triggering conditions; the predictive triggering conditions are defined as follows: when the controller analyzes historical data and identifies that the time series change rate of the real-time scaling risk index continuously exceeds the historical average change rate in the short term and forms an accelerating trend, the physical cleaning unit is activated in advance.

10. The method for treating industrial silicon circulating cooling water according to claim 9, characterized in that, The step of activating the physical cleaning unit further includes: instructing the agent dosing unit (200) to increase the amount of stripping agent added; after a preset delay, activating the robotic arm of the physical cleaning unit so that its end scraper head scrapes off the inner wall deposits along a preset path; after scraping is completed, instructing the micro sampling pump at the end of the robotic arm to extract a water sample for evaluating the cleaning effect.

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