Analysis method suitable for online turbidity of circulating water

Abstract

The invention focuses on the field of online turbidity analysis of industrial circulating water, and provides an innovative analysis method. According to the method, a two-stage defoaming and dynamic calibration collaborative strategy is adopted to solve the problem that a traditional online turbidity meter is easily interfered by bubbles and temperature fluctuation in a low-turbidity environment, so that the measurement error is large. Primary defoaming is completed by arranging a porous bubble adsorption layer in a flow cell, and secondary defoaming is realized by virtue of centrifugal force of rotating blades of a centrifugal degassing unit; double light paths (infrared light and visible light) are used for cross validation of turbidity signals, and the light path sensitivity is dynamically adjusted according to the water turbidity; and constructing a temperature-turbidity correlation model to correct the temperature drift influence in real time, and constructing a historical data trend library to predict the turbidity change. Through application of a chemical plant circulating water system, the error in a low-turbidity scene is remarkably reduced, and the stability is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the field of industrial circulating water quality monitoring. Specifically, it relates to a method for accurately analyzing the turbidity of circulating water by means of on-line detection. In modern industrial production systems, industrial circulating water systems are widely used in many industries such as chemical industry, power, and steel to achieve efficient recycling of water resources, reduce energy consumption and production costs. The turbidity of circulating water, as a core indicator reflecting the cleanliness of the system water quality, its accurate monitoring is of irreplaceable significance for maintaining the stable and efficient operation of the circulating water system, preventing failures such as corrosion and blockage caused by dirt accumulation on equipment, optimizing water treatment process parameters, and ensuring the smooth progress of the production process. Background Art

[0002] In an industrial circulating water system, turbidity represents the degree of obstruction to the transmission of light by suspended particles in water and is one of the key parameters for measuring water quality. Once the turbidity of the circulating water exceeds the reasonable range, the suspended particles in the water will gradually deposit on the surfaces of equipment such as pipelines, heat exchangers, and cooling towers, forming a dirt layer. This dirt layer will not only significantly reduce the heat transfer efficiency of the equipment, resulting in a sharp increase in energy consumption, but may also cause local corrosion, and in severe cases, even cause equipment perforation and leakage, forcing the production to stop and bringing huge economic losses. Most traditional on-line turbidity meters operate based on the principle of light scattering. Its working mechanism is as follows: When light of a specific wavelength irradiates the suspended particles in water, the particles will cause the light to scatter. The turbidity meter accurately detects the intensity of the scattered light and, based on a pre-established calibration curve, converts it to obtain the turbidity value of the water. However, in the complex and changeable operating environment of actual industrial circulating water, especially under the condition of low turbidity (<10 NTU), such turbidity meters based on the principle of light scattering expose a series of intractable problems. First of all, during the operation of the circulating water system, due to various factors such as the pump sucking in air, water flow impact, and aeration, a certain amount of air bubbles will inevitably be mixed in. The light scattering characteristics of air bubbles and suspended particles are very similar. When the turbidity meter detects the intensity of the scattered light, it is difficult to effectively distinguish whether the signal comes from suspended particles or air bubbles, thus introducing significant measurement errors. For example, if there are a small number of air bubbles in the water, their scattered light may be misjudged as the scattered light of suspended particles, resulting in a falsely high measured turbidity value and being unable to truly reflect the water quality status. Secondly, the temperature of industrial circulating water is not constant. Instead, it will change significantly due to factors such as adjustments in production processes, seasonal changes, and fluctuations in environmental temperature. The change in temperature will have a direct impact on the physical properties of water, such as density, refractive index, etc., and indirectly interfere with the light scattering process in water. Taking the increase in temperature as an example, when the water temperature rises, the density of water decreases, and the volume fraction of the same mass of suspended particles in water relatively increases. According to the light scattering theory, this will lead to an increase in the detected scattered light intensity, and ultimately result in a higher turbidity value measured, deviating from the true value. Many attempts have been made in the prior art to overcome these problems. Taking the "online low turbidity analysis system" of Shanghai Zeming as an example, this system adopts a two-stage defoaming technology in an attempt to improve the measurement accuracy in a low turbidity environment. In its primary defoaming stage, physical methods are used, such as intercepting through a filter screen, a gas-liquid separation device, etc., to initially remove the larger-sized bubbles in the water sample; the secondary defoaming then uses more refined treatment means, such as ultrasonic defoaming, chemical defoaming agents, etc., to further process the remaining tiny bubbles. However, this technical solution still has obvious limitations when facing dynamic water quality conditions. The water quality of industrial circulating water is not static, and the types, concentrations, particle size distributions of suspended particles, as well as parameters such as water temperature, pH value, and water flow velocity are constantly changing dynamically. It is difficult for the prior art to monitor and respond to these complex and variable parameters in real time and accurately, and it is unable to compensate and correct the measurement results in a timely and effective manner, resulting in the continuous accumulation of measurement errors over time and making it difficult to meet the strict requirements of the industrial circulating water system for long-term stable and high-precision turbidity monitoring. Summary of the Invention

[0003] The core objective of the present invention is to develop an online turbidity analysis method integrating two-stage defoaming and dynamic calibration technologies, aiming to completely overcome the technical problems that traditional online turbidimeters have large measurement errors due to interference from bubbles and temperature fluctuations in low turbidity scenarios, and poor long-term stability under dynamic water quality conditions. Primary defoaming: Inside the flow cell of the turbidity detection system, a porous bubble adsorption layer is carefully set up. This adsorption layer is made of materials with high surface energy characteristics, such as silica gel, activated carbon fiber, etc. Its internal microstructure presents a large number of tiny and interconnected pores, and the pore diameter is usually controlled within the micron range. When the circulating water sample containing bubbles flows into the flow cell and slowly passes through the porous bubble adsorption layer, according to the surface tension theory, an adsorption force will be generated between the bubble and the surface of the adsorption layer material. The magnitude of this adsorption force is closely related to the bubble radius, the surface tension coefficients of the adsorption layer material and water, and the contact angle between the bubble and the adsorption layer material. Its mathematical expression can be approximately expressed as F = 2πrγcosθ (where F is the adsorption force, r is the bubble radius, γ is the surface tension coefficient, and θ is the contact angle). By precisely screening the adsorption layer materials and accurately designing the pore size and distribution, it can be ensured that within the common bubble size range of the circulating water, a sufficiently strong adsorption force is generated to stably adsorb the bubbles on the pore surface, thus efficiently achieving the preliminary removal of most bubbles in the water sample. Secondary defoaming: On the basis of primary defoaming, a centrifugal degassing unit is added. This unit mainly consists of a high-speed rotating blade and a sealed housing. When the water sample after primary defoaming treatment flows into the centrifugal degassing unit, the rotating blade rotates at a specific speed at a high speed, forming a strong centrifugal force field inside the unit. According to the centrifugal force formula F = mrω² (where m is the mass of the bubbles in the water sample, r is the distance from the bubble to the rotation axis, and ω is the angular velocity of the rotating blade), under the action of this centrifugal force, the bubbles with relatively small density will quickly move in the opposite direction of the rotation center and be effectively separated from the water sample. The separated bubbles are discharged from the unit through a specially set exhaust port, while the degassed water sample continues the subsequent turbidity detection process. By flexibly adjusting the structural parameters such as the rotation speed of the rotating blade, the blade shape and quantity, the magnitude and distribution of the centrifugal force can be finely controlled, so as to ensure the efficient removal of the residual bubbles and provide a purer water sample for the subsequent turbidity detection. Dual - optical - path design: The present invention innovatively adopts a dual - optical - path detection architecture, that is, simultaneously using infrared light and visible light to detect the turbidity signal of the water sample. Infrared light (usually with a wavelength of about 850 nm) has strong penetration ability and unique absorption and scattering characteristics for various suspended particles in water. Most suspended particles will produce an obvious scattering effect on the infrared light of this wavelength, enabling the infrared light sensor to accurately capture the overall content information of the suspended particles, providing key data support for turbidity calculation. The propagation characteristics of visible light (such as a wavelength of 680 nm) in water are significantly different from those of infrared light, and its interference by bubbles is more prominent. However, it is precisely by using this characteristic that by cross - comparing and analyzing the turbidity signals detected by infrared light and visible light, the interference of bubbles on the turbidity measurement results can be keenly identified and effectively excluded. Specifically, when there are bubbles in the water sample, the scattered light signals detected by infrared light and visible light will show obvious differences in characteristics such as intensity and spectrum. Through in - depth excavation and intelligent analysis of these difference characteristics, the system can accurately judge the bubble interference components in the signal and eliminate them, thus significantly improving the accuracy of turbidity measurement. Dynamic adjustment of optical - path sensitivity: To further adapt to the complex and changeable circulating water quality conditions, the present invention constructs an advanced dynamic adjustment mechanism for optical - path sensitivity. The system automatically and accurately adjusts the detection sensitivity of the optical path by real - time monitoring the turbidity value of the circulating water and based on the pre - established correlation model between turbidity and optical - path sensitivity. When the detected turbidity value is at a relatively low level (such as <5 NTU), at this time the scattered light signal is relatively weak, and the system will automatically increase the sensitivity of the optical path, which can be achieved by enhancing the luminous intensity of the light source, increasing the gain of the detector, etc. For example, for a system using a light - emitting diode (LED) as the light source, the luminous brightness of the LED can be enhanced by precisely controlling the magnitude of the driving current, thereby increasing the intensity of the scattered light signal for the detector to capture more clearly. On the contrary, when the turbidity value is relatively high (such as >10 NTU), to prevent the detector from being saturated due to the over - strong signal, the system will appropriately reduce the optical - path sensitivity to ensure that the measurement results are always within the accurate and reliable range. Temperature - Turbidity Correlation Model: To effectively eliminate the influence of temperature fluctuations on turbidity measurement results, the present invention has conducted a large number of rigorous experimental studies and collected rich turbidity measurement data under different temperature conditions. Based on these experimental data, advanced data fitting and modeling techniques have been used to successfully construct a high - precision temperature - turbidity correlation model. For example, through data analysis and model optimization, an empirical model such as turbidity = K×scattering intensity / (1 + 0.1×ΔT) has been obtained (where K is the model constant and ΔT is the difference between the current temperature and the standard reference temperature). During the actual operation process, the system uses a high - precision temperature sensor to continuously monitor the water temperature of the circulating water and transmits the temperature data to the data processing unit in real - time. The data processing unit immediately and accurately corrects the turbidity measurement data according to this temperature - turbidity correlation model, thereby effectively compensating for the interference of temperature changes on turbidity measurement results and ensuring the accuracy and stability of the measurement results. Establishment and Application of Historical Data Trend Library: To achieve long - term and dynamic monitoring and prediction of the turbidity change of circulating water, the present invention has designed and established a powerful historical data trend library. The system continuously records the historical measurement data of the turbidity of circulating water and systematically arranges and deeply analyzes these data according to the time series. Advanced data mining algorithms and machine learning techniques, such as the autoregressive integrated moving average model (ARIMA) in time series analysis, neural network algorithms, etc., are used to accurately extract the trend characteristics and laws of turbidity changes from a large amount of historical data. Based on the established historical data trend library, the system can scientifically predict the turbidity change in a future period according to the currently measured real - time turbidity data and the historical change trend. When there is a large deviation between the actual measured value and the predicted trend, the system will immediately activate the self - calibration and adjustment mechanism, and optimize and correct the measurement parameters, algorithm models, etc., to ensure that the measurement results always maintain a high - precision and high - stability level. Specific Embodiment

[0004] Example 1: Taking the monitoring project of the circulating water system in a large chemical plant as an example, the actual application process and remarkable effects of the method of the present invention are elaborated in detail. Water Sample Flow Rate: After a large number of preliminary experimental tests and simulation analyses, the flow rate of the water sample in the detection system is accurately set to 0.5 m / s. This flow rate setting can not only ensure that the water sample flows fully and evenly in key components such as the flow - through cell and the centrifugal degassing unit, so that the measurement results can truly and comprehensively reflect the overall water quality of the circulating water, but also will not have an adverse impact on key treatment processes such as bubble adsorption and degassing due to too fast a flow rate, ensuring the stability of the system operation and the accuracy of the measurement results. Rotation speed of the defoaming mechanism: For the rotation speed of the rotating blades of the centrifugal degassing unit, after multiple rounds of optimization and debugging, it was finally determined to be 2000 rpm. At this rotation speed, the centrifugal degassing unit can generate just the right centrifugal force to effectively separate the tiny bubbles remaining after primary defoaming, while avoiding excessive disturbance to the suspended particles in the water sample due to excessive centrifugal force, which affects the accuracy of turbidity measurement. Optical path wavelength: In the dual optical path design, the infrared light wavelength is selected as 850 nm. This wavelength of infrared light has extremely high detection sensitivity and specificity for suspended particles in the circulating water quality detection, and can accurately capture the scattered light signal of the suspended particles in the water, providing a reliable basis for turbidity calculation. The visible light wavelength is selected as 680 nm. At this wavelength, the response characteristics of visible light and infrared light to bubbles and suspended particles are the most significant, which is convenient for the system to efficiently exclude bubble interference through signal cross-verification and analysis, and improve the turbidity measurement accuracy. The circulating water sample smoothly flows into the flow cell of the turbidity detection system through a specially designed inlet hole. Inside the flow cell, the water sample first comes into full contact with the primary defoaming layer (made of high-quality silica gel porous structure). Under the action of surface tension, the bubbles in the water sample are quickly adsorbed on the pore surface of the silica gel porous structure, achieving efficient preliminary defoaming. In this process, the adsorption of bubbles on the surface of the silica gel material follows the surface tension theory. Through the carefully designed pore size and distribution, the effective adsorption of bubbles of different sizes is ensured, greatly reducing the bubble content in the water sample. The water sample after primary defoaming treatment then flows into the secondary centrifugal degassing unit. In the strong centrifugal force field generated by the high-speed rotating blades, the remaining bubbles quickly move in the opposite direction of the rotation center and are completely separated from the water sample. The separated bubbles are discharged from the unit through a specially set exhaust port, while the degassed pure water sample continues to enter the subsequent detection process. By precisely controlling the rotation speed and structural parameters of the rotating blades, the efficient removal of the remaining bubbles by the centrifugal degassing unit is ensured, providing high-quality water sample conditions for subsequent turbidity detection. The dual optical path sensors are started synchronously to collect the scattered light signals of the water sample at the same time. Among them, the infrared light sensor focuses on detecting the scattered light generated by the total suspended matter in the water. With its high sensitivity and specificity to suspended particles, it provides the main reference data for turbidity calculation. The visible light sensor uses the difference in its response to bubbles and suspended particles from infrared light to collect scattered light signals for cross-comparison analysis with the infrared light signals, and effectively identifies and excludes the interference of bubbles on turbidity measurement through intelligent algorithms, further improving the accuracy of the measurement results. The high-precision temperature sensor monitors the water temperature of the circulating water in real time and transmits the temperature data to the data processing unit immediately. The data processing unit corrects the turbidity measurement data in real time and accurately according to the pre-established temperature-turbidity correlation model (such as turbidity = K×scattering intensity / (1 + 0.1×ΔT)). This process effectively compensates for the influence of temperature fluctuations on the turbidity measurement results, ensuring that the measurement results always accurately reflect the true turbidity of the circulating water. The corrected and processed turbidity data is uploaded to the central control center of the factory through the high-speed communication module. Once the detected turbidity value exceeds the preset threshold (such as 5 NTU), the system immediately triggers the alarm mechanism, sending a warning message to the relevant staff to remind them to check and process the circulating water system in time to ensure the stable operation of the system. Experimental verification: To comprehensively evaluate the performance advantages of the method of the present invention, a comparative experiment was carried out with the traditional turbidity measurement method under the same measurement conditions (each group of experiments was repeated 20 times, n = 20). The experimental results show that in the harsh scenario of low turbidity (1 NTU), the measurement error of the method of the present invention is ≤0.1 NTU, and the measurement accuracy has been significantly improved compared with the traditional method. Through the long-term stability monitoring for one month, the fluctuation of the measurement data was statistically analyzed, and the results show that the stability of the method of the present invention has been improved by 70% compared with the traditional method, effectively solving the problem of poor long-term stability of the traditional method under dynamic water quality conditions, and providing a reliable and accurate technical means for the turbidity monitoring of industrial circulating water systems. It can be clearly seen from the above embodiments that the online turbidity analysis method combining two-stage defoaming and dynamic calibration proposed by the present invention shows excellent performance advantages in practical industrial applications, can significantly improve the accuracy and long-term stability of circulating water turbidity measurement, and has broad market application prospects and great economic value.

Claims

1. The analysis method applicable to the online turbidity of circulating water according to claim 1, characterized in that, The double-stage defoaming technology includes: arranging a porous bubble adsorption layer in the flow cell for primary defoaming. The porous bubble adsorption layer is made of a high surface energy material and adsorbs bubbles in the water sample relying on surface tension. A centrifugal degassing unit is set up for secondary defoaming. The centrifugal degassing unit generates centrifugal force by the rotation of the rotating blades to separate the residual bubbles.

2. The analysis method applicable to the on-line turbidity of circulating water according to claim 2, characterized in that, The pore size and selected material of the porous bubble adsorption layer are specifically designed according to the common bubble size range of circulating water, aiming to ensure efficient adsorption of bubbles.

3. The analysis method applicable to the on-line turbidity of circulating water according to claim 2, characterized in that The rotation speed of the rotating blades and the structural parameters of the centrifugal degassing unit can be flexibly adjusted according to the actual characteristics of the water sample, so as to optimize the magnitude and distribution of the centrifugal force.

4. The analysis method applicable to on-line turbidity of circulating water according to claim 1, characterized in that, The optical path adaptive adjustment includes: adopting a double optical path design, and using infrared light and visible light simultaneously for turbidity signal detection, and excluding bubble interference through signal cross-verification; dynamically adjusting the optical path sensitivity in real time according to the water quality turbidity, increasing the sensitivity when the turbidity is low and decreasing the sensitivity when the turbidity is high.

5. The analysis method applicable to the on-line turbidity of circulating water according to claim 5, characterized in that, The dynamic adjustment of the optical path sensitivity is achieved by controlling the light emission intensity of the light source and the gain of the detector.

6. The analysis method applicable to the on-line turbidity of circulating water according to claim 1, characterized in that, The data compensation algorithm includes: constructing a temperature-turbidity correlation model, using a temperature sensor to measure the water temperature in real time and correcting the turbidity measurement data in real time; establishing a historical data trend library, using data mining and machine learning algorithms to predict the turbidity change trend, and then calibrating and adjusting the measurement results.

7. The analysis method applicable to the on-line turbidity of circulating water according to claim 7, characterized in that, The temperature-turbidity correlation model is generated by fitting a large amount of experimental data and is continuously updated and optimized according to the actual application situation.