A steam condensate water recovery system with automatic cleaning function

Abstract

The present application relates to the technical field of industrial water treatment, and discloses a steam condensate water recovery system with automatic cleaning function. The condensate water collecting unit separates solid particles and suspended solids in the condensate water through a multi-stage filtering structure to generate preliminary purified condensate water; the water quality monitoring unit generates a water quality parameter set by collecting turbidity, pH value and ion concentration data in real time based on an optical sensor array and a conductivity detection device; the cleaning triggering unit generates a cleaning instruction signal according to a pollution accumulation index calculated based on a turbidity threshold and an ion concentration change rate; the self-cleaning execution unit starts a high-pressure flushing of a rotating nozzle array and activates an ultrasonic oscillator to decompose sediments, and generates cleaning state feedback data; and the recovered water treatment unit removes dissolved impurities through an ion exchange resin bed and an activated carbon adsorption layer to generate reusable industrial water. The system realizes automatic cleaning and efficient recovery of condensate water, and improves water resource utilization.

Description

Technical Field

[0001] This invention relates to the field of industrial water treatment technology, specifically to a steam condensate recovery system with automated cleaning function. Background Technology

[0002] In industrial production, steam, as a highly efficient heat energy carrier, is widely used in various industries such as chemical, textile, and food processing. After completing heat transfer, steam condenses into condensate, which not only contains significant residual heat but is also relatively pure, making it valuable for recycling and reuse. However, current steam condensate recovery systems used in industrial applications still face many problems that urgently need to be addressed during actual operation.

[0003] Most existing condensate recovery systems lack effective pretreatment. Steam condensate generated during industrial production often contains metal debris from pipe corrosion, solid particles from raw materials, and various suspended solids. If these impurities are not removed promptly and enter the recovery system directly, they will not only deposit on the inner walls of pipes and the surfaces of critical components such as pump impellers, leading to pipe blockages and reduced pump efficiency, but also accelerate the wear and tear on subsequent treatment equipment, shortening its lifespan. Furthermore, while some systems may have simple filtration devices, their filtration precision is low, making it difficult to completely separate fine particulate impurities and failing to meet the basic water quality requirements for subsequent recycling and reuse.

[0004] In terms of water quality monitoring, traditional recycling systems typically obtain water quality parameters through periodic sampling and laboratory testing. This monitoring method has a significant lag and cannot reflect the dynamic changes in condensate water quality in real time. When condensate water quality becomes abnormal, such as pH deviating from the normal range or a sharp increase in ion concentration, the system cannot detect it in time and take corresponding measures. This results in substandard condensate entering subsequent treatment stages, which not only increases the difficulty and cost of subsequent treatment but may also cause corrosion to reuse equipment and affect the stability of the production process. In addition, some systems with online monitoring functions monitor only a few parameters, such as turbidity or pH, and cannot comprehensively assess the degree of condensate pollution, making it difficult to provide a comprehensive and accurate basis for system operation and control.

[0005] Regarding system cleaning, existing recycling systems largely rely on periodic manual cleaning. Manual cleaning not only requires stopping system operation, disrupting production continuity and increasing downtime losses, but it is also time-consuming and labor-intensive. The cleaning effectiveness is highly dependent on the operator's experience and sense of responsibility, making it difficult to guarantee thorough cleaning. For hard-to-reach areas such as internal pipes and the inner walls of collection tanks, manual cleaning often fails to effectively remove attached deposits. Long-term accumulation leads to reduced system heat exchange efficiency, further impacting the quality and efficiency of condensate recovery. Furthermore, frequent manual cleaning increases labor costs, raising the company's operating costs.

[0006] In the deep treatment and reuse of condensate, existing systems employ relatively simple processes, mostly relying on filtration or adsorption. These methods are insufficient to effectively remove dissolved impurities such as various ions and organic pollutants from the condensate. The treated condensate often fails to meet industrial reuse standards, resulting in low-quality water use or even direct discharge. This not only leads to significant water waste but also increases wastewater discharge costs for businesses, failing to meet current industrial requirements for energy conservation, emission reduction, and green development. Summary of the Invention

[0007] The purpose of this invention is to provide a steam condensate recovery system with automated cleaning function to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides a steam condensate recovery system with automated cleaning function, the system comprising:

[0009] The condensate collection unit is used to receive and store steam condensate generated during industrial production. It separates solid particles and suspended matter in the condensate through a multi-stage filtration structure to generate pre-purified condensate.

[0010] The water quality monitoring unit, based on an optical sensor array and a conductivity detection device, collects data on turbidity, pH, and ion concentration of the pre-purified condensate in real time, and generates a set of water quality parameters.

[0011] The cleaning triggering unit dynamically calculates the condensate pollution accumulation index based on the turbidity threshold and ion concentration change rate in the water quality parameter set, and generates a cleaning instruction signal based on the condensate pollution accumulation index.

[0012] The self-cleaning actuator, in response to the cleaning command signal, starts the rotating nozzle array to perform high-pressure rinsing on the inner wall of the condensate collection unit, while activating the ultrasonic oscillator to decompose the attached deposits and generate cleaning status feedback data.

[0013] The water recycling unit receives cleaned condensate and further removes dissolved impurities through an ion exchange resin bed and activated carbon adsorption layer to generate reusable industrial water.

[0014] Preferably, the preliminary purified condensate generation step is as follows:

[0015] When steam condensate flows into the collection chamber, the water is guided to pass through a series of stainless steel screens with decreasing apertures in sequence to intercept solid particles of different sizes.

[0016] A centrifugal separator is used to apply a swirling force to the condensate that has passed through a screen, causing suspended solids with a density higher than that of water to settle to the bottom of the separation chamber.

[0017] The separated upper liquid is introduced into a multi-layer fiber filter medium to capture residual micron-sized particles and output pre-purified condensate.

[0018] Preferably, the steps for generating the water quality parameter set are as follows:

[0019] Distributed optical sensors were deployed along the flow path of condensate water to measure changes in light scattering intensity and transmittance in different sections of the water body.

[0020] A ring electrode assembly was installed at the final outlet to detect the real-time conductivity and temperature compensation value of the condensate.

[0021] By integrating optical and electrochemical data, and labeling the turbidity gradient, pH shift, and metal ion concentration of sampling points according to time series, a set of water quality parameters is constructed.

[0022] Preferably, the calculation steps for the condensate pollution accumulation index are as follows:

[0023] Extract the turbidity rise rate and ion concentration fluctuation range for three consecutive sampling periods from the water quality parameter set;

[0024] By comparing the current period data with the historical average, the pollution level deviation coefficient is obtained.

[0025] The adhesion tendency index of pollutants is calculated by combining the cumulative operating time on the inner wall of the collection unit;

[0026] The cumulative contamination index of condensate is output based on the nonlinear combination of the deviation coefficient and the adhesion tendency index.

[0027] Preferably, the step of generating the cleaning instruction signal is as follows:

[0028] The cumulative pollution index of condensate water is input into a pre-trained classification decision tree model to match the corresponding cleanliness level label.

[0029] Select the high-pressure flushing pressure value, ultrasonic frequency range, and duration of action according to the cleanliness level label;

[0030] The above parameters are encapsulated into standardized control commands to generate cleaning command signals.

[0031] Preferably, the step of generating the cleaning status feedback data is as follows:

[0032] During the high-pressure flushing process, the volume change curve of the discharged wastewater per unit time is recorded by a flow meter;

[0033] Vibration sensors were used to monitor the peeling strength of deposits on the inner wall under ultrasonic waves.

[0034] By analyzing the slope of the curve and the characteristics of the vibration spectrum, the cleaning coverage and the thickness of the residue are determined, and cleaning status feedback data is generated.

[0035] Preferably, the steps for generating the reusable industrial water are as follows:

[0036] The cleaned condensate is passed through a columnar container filled with mixed ion exchange resin in a laminar flow state to replace calcium and magnesium ions in the water.

[0037] The effluent is guided into activated carbon adsorption towers arranged in series to adsorb organic impurities and chlorine compounds;

[0038] A nanometer-scale membrane filter is installed at the final outlet to trap any remaining colloidal substances, resulting in reusable industrial water.

[0039] Preferably, the regeneration step of the ion exchange resin is as follows:

[0040] Monitor the ion adsorption saturation of the resin bed and trigger the regeneration program when the conductivity of the effluent exceeds the set threshold.

[0041] The resin layer is rinsed with a counter-current sodium chloride solution to release the adsorbed metal ions;

[0042] Collect the recycled waste liquid and introduce it into a neutralization reaction tank. After adjusting the pH, it is discharged.

[0043] Preferably, the system further includes:

[0044] The energy recovery unit captures the waste heat from the high-temperature wastewater generated by the self-cleaning execution unit and preheats the newly entering steam condensate through a plate heat exchanger;

[0045] The low-temperature wastewater after heat exchange is introduced into a sedimentation tank for solid-liquid separation, and the separated dry solids are compressed into harmless waste blocks.

[0046] Preferably, the optimized steps for waste heat recovery are as follows:

[0047] Real-time monitoring of the fluid temperature difference and flow ratio on both sides of the heat exchanger, and dynamic adjustment of the sewage flow rate to maintain optimal heat transfer efficiency.

[0048] When scale buildup is detected on the heat exchanger surface, the system automatically switches to the backup flow path and initiates the pulse backwash mode.

[0049] Record the energy conversion rate of each heat exchange to generate a heat exchange performance degradation curve for predicting maintenance cycles.

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] This automated steam condensate recovery system effectively receives and pre-purifies industrial steam condensate through a condensate collection unit. The unit employs a multi-stage filtration structure that separates solid particles and suspended matter from the condensate layer by layer, reducing impurities from entering subsequent treatment stages. This prevents impurities from accumulating within the system, lowering the risk of pipe blockage and equipment wear, and helping to maintain stable operation of all system components, thus extending equipment lifespan. Simultaneously, the pre-purified condensate lays a solid foundation for subsequent water quality monitoring and advanced treatment, reducing interference from impurities in later processes and improving overall treatment efficiency.

[0052] The water quality monitoring unit, based on an optical sensor array and conductivity detection device, can collect multiple key water quality parameters of condensate in real time, such as turbidity, pH, and ion concentration, and generate a complete set of water quality parameters. This multi-parameter real-time monitoring mode, compared to traditional periodic sampling and single-parameter monitoring, can more comprehensively and accurately reflect the dynamic changes in condensate water quality. It allows the system to promptly capture abnormal water quality signals, providing precise basis for subsequent cleaning triggering and treatment process adjustments. This avoids problems such as untimely treatment and poor treatment effects caused by lagging water quality monitoring or incomplete parameters, ensuring the stability and reliability of the condensate recovery and treatment process.

[0053] The cleaning trigger unit dynamically calculates the condensate contamination accumulation index based on the turbidity threshold and ion concentration change rate in the water quality parameter set, and generates a cleaning command signal based on this index, thus achieving intelligent judgment of the cleaning timing. This dynamic calculation and intelligent triggering method eliminates the subjectivity and lag of traditional manual judgment of cleaning timing, and can accurately start the cleaning program according to the actual contamination of the condensate, avoiding energy waste caused by premature cleaning and excessive impurity deposition caused by excessive cleaning. By reasonably controlling the cleaning frequency and timing, the system's cleaning effect is ensured while minimizing the impact of the cleaning process on the normal operation of the system, maintaining the continuity of production.

[0054] The self-cleaning unit responds to cleaning command signals, activating the rotating nozzle array for high-pressure rinsing and engaging the ultrasonic oscillator to break down attached deposits, creating a highly efficient and thorough cleaning mode. The rotating nozzle array provides comprehensive, thorough high-pressure rinsing of the inner wall of the condensate collection unit, effectively removing attached impurities. The ultrasonic oscillator uses high-frequency vibration to break down stubborn deposits, solving the cleaning challenges of areas difficult to reach manually. This automated cleaning method eliminates the need to stop system operation, avoiding downtime losses associated with manual cleaning, while ensuring consistent and thorough cleaning results, reducing labor costs, and improving the overall operating efficiency of the system.

[0055] The recycled water treatment unit utilizes the synergistic effect of an ion exchange resin bed and an activated carbon adsorption layer to deeply treat the cleaned condensate, effectively removing dissolved impurities. The condensate treated by this unit meets industrial reuse standards, achieving water resource recycling, reducing fresh water consumption, and lowering water costs for enterprises. Simultaneously, water recycling reduces wastewater discharge and environmental pollution, aligning with current industrial trends of energy conservation, emission reduction, and green development. This helps enterprises improve their environmental protection standards and establish a positive social image. Furthermore, the coordinated operation of the various units within the system forms a complete process from condensate collection, preliminary purification, real-time monitoring, intelligent cleaning to deep treatment and reuse, comprehensively improving the recycling rate and treatment quality of steam condensate, providing strong support for enterprises to achieve efficient resource utilization and sustainable development. Attached Figure Description

[0056] Figure 1 This is a schematic diagram illustrating the working principle of the steam condensate recovery system with automated cleaning function described in this invention.

[0057] Figure 2 A flowchart for the initial purification of condensate;

[0058] Figure 3 A flowchart generated from a set of water quality parameters. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0060] Please see Figure 1This invention provides a steam condensate recovery system with automated cleaning function, comprising multiple units working collaboratively. A condensate collection unit receives steam condensate generated during industrial production. The condensate undergoes partial processing within a collection chamber, with a multi-stage filtration structure consisting of filter layers with different pore sizes. Solid particles and suspended matter are separated through physical interception, and the preliminarily purified condensate enters a temporary storage area. A water quality monitoring unit is deployed at key nodes along the condensate flow path. An optical sensor array collects changes in the optical properties of the water, and a conductivity detection device measures ionic conductivity. Real-time data is aggregated into a set of water quality parameters. A cleaning trigger unit analyzes dynamic indicators in the water quality parameter set, using turbidity threshold and ion concentration change rate as input variables. A calculation engine executes a contamination accumulation algorithm, outputting a condensate contamination accumulation index. When the index exceeds a set threshold, a cleaning command signal is triggered. Upon receiving the cleaning command signal, the self-cleaning execution unit activates a high-pressure flushing module. A rotating nozzle array covers the inner wall surface of the condensate collection unit, and an ultrasonic oscillator generates high-frequency vibration waves to decompose stubborn deposits. Cleaning status feedback data is generated in real-time through a sensor network. The recycled water treatment unit receives cleaned condensate, an ion exchange resin bed removes dissolved ions, an activated carbon adsorption layer captures organic impurities, and the final stage produces reusable industrial water through fine filtration.

[0061] Example 1: See Figure 2The condensate collection unit of the steam condensate recovery system relies on a multi-stage filtration structure to achieve preliminary purification of condensate. Steam condensate flows from the industrial equipment into the inlet pipe of the collection chamber, which is equipped with a buffer device to reduce water flow impact. The volume of the collection chamber is designed according to the system's processing capacity. The first stage of the multi-stage filtration structure uses a 100-micron stainless steel screen, installed at an angle to form a filter bed. Water flows through the screen by gravity, and solid particles larger than 100 microns are intercepted on the screen surface. A vibrating motor is connected to the back of the screen, operating intermittently to prevent screen clogging. The intercepted solid particles are discharged into a waste collection tank with the flushing water. The condensate after primary filtration flows into the second stage of filtration due to the liquid level difference. The second stage consists of a 50-micron stainless steel screen with a twill weave to enhance mechanical strength, creating turbulence as water flows through it. Turbulence causes some suspended solids to aggregate into larger flocs. A guide plate below the stainless steel screen changes the water flow direction, distributing the water evenly across the entire filter surface. Cleaning of the stainless steel screen uses a backwash water circulation system. Backwash water is injected from the bottom of the screen to impact residual particles, and the backwash water pressure is automatically adjusted based on the pressure difference across the screen. The condensate then enters the centrifugal separator. The inlet tangential design of the centrifugal separator generates a swirling force field, the intensity of which is adjusted by a frequency converter, maintaining a speed range of 1500-3000 rpm. Suspended solids with a density higher than water move towards the separation chamber wall under centrifugal force. The separation chamber wall is designed with a conical structure to facilitate particle settling, and the settled particles slide along the conical wall into the bottom sludge hopper. The sludge hopper is equipped with a level sensor to control the opening and closing of the sludge discharge valve, which uses a pneumatic diaphragm structure to prevent jamming. The supernatant is discharged from the overflow port at the top of the centrifugal separator.

[0062] The centrifuged liquid is introduced into a multi-layer fiber filter medium, which fills a vertical pressure vessel. The pressure vessel is divided into three compartments by a perforated plate. The first compartment is filled with a coarse fiber filter layer to intercept particles larger than 20 micrometers; the second compartment is filled with a medium-density fiber layer to capture particles of 10-20 micrometers; and the third compartment is filled with a fine fiber layer to remove particles of 5-10 micrometers. The fiber material of the multi-layer fiber filter medium is hydrophilically treated, and capillary action occurs as water flows through, enhancing adsorption capacity. Filtration resistance is monitored in real time by a differential pressure transmitter. An ultraviolet disinfection module is installed in the output pipe of the pre-purified condensate. The lamp wavelength of the ultraviolet disinfection module is set to 254 nanometers, and the irradiation dose is automatically calculated based on the water flow rate. A sampling valve is installed at the outlet for quality inspection. The sampling valve uses a double-sealed structure to prevent leakage. All indicators of the pre-purified condensate meet the inlet requirements of subsequent treatment units. The stainless steel screen assembly is made of 316L stainless steel to ensure corrosion resistance. The screen frame is laser-welded to ensure dimensional accuracy, and the installation angle is designed at a 60-degree tilt angle to optimize filtration efficiency. The excitation force of the vibratory motor is adjusted via an eccentric block. The vibration frequency is offset from the natural frequency of the screen to avoid resonance, and the vibration amplitude is set within the range of 0.5-2 mm according to the particle characteristics. The impeller of the centrifugal separator adopts an open design with 6 blades and a backward bend angle of 30 degrees. The impeller is made of duplex stainless steel to resist cavitation. The cone angle of the separation chamber is designed at 60 degrees to promote particle slippage. The inside of the cone is polished to reduce the coefficient of friction, and the bearing system uses a circulating lubricating oil cooling method.

[0063] The fiber diameter of the multi-layer fiber filter media decreases from 50 micrometers to 5 micrometers, and the compaction density of the fiber layers gradually increases along the water flow direction. The working pressure of the pressure vessel is maintained within the range of 0.3-0.6 MPa. The replacement cycle of the fiber layers is determined by differential pressure data; a replacement prompt is triggered when the differential pressure exceeds 0.1 MPa. The fiber material is recyclable polyester. The entire filtration system is controlled by a PLC program. The PLC receives pressure, flow, and level signals from various sensors and controls the valve opening and pump speed. The human-machine interface displays real-time operating parameters, and historical data is stored in a flash memory for trend analysis. The fault diagnosis program issues alarms based on abnormal patterns. The residence time of steam condensate in the collection chamber is regulated by a level control pump. The level sensor uses a hydrostatic measurement principle, and the measurement signal is temperature-compensated. A vent pipe is designed at the bottom of the collection chamber for system maintenance, and the vent pipe connects to the wastewater treatment system. The inside of the chamber is coated with an epoxy anti-corrosion coating. The backwashing process of the multi-stage filtration structure is triggered by time or pressure difference. Backwash water is drawn from the clean water tank, and the backwashing intensity is 1.5 times the normal flow rate. The backwash wastewater is discharged into the sludge thickening tank, and the supernatant in the sludge thickening tank is returned to the treatment system. The thickened sludge is dewatered and then transported off-site.

[0064] The centrifugal separator's vibration-damping foundation uses rubber vibration isolators, whose natural frequency is less than one-third of the equipment's rotational speed. Flexible joints are installed on the inlet and outlet pipes to reduce vibration transmission. The gearbox lubricating oil temperature is controlled by a cooler; the cooler's heat exchange area is calculated based on the heat load, and temperature sensors monitor oil quality changes. Replacement of the multi-layer fiber filter media is performed using specialized tools that mechanically compress and seal the fiber layers. The sealing material is food-grade rubber to ensure water quality safety. Filter media performance is tested using a particle counter, which measures the distribution of particulate matter in the water; the data is recorded in the quality archive. The system piping layout considers thermal expansion compensation; compensators use a corrugated pipe structure to absorb displacement, and the support spacing is calculated based on fluid weight. Rock wool insulation is used to reduce heat loss; the insulation layer thickness is designed based on the medium temperature, and the outer protective layer is an aluminum alloy plate to enhance durability. The electrical control system complies with explosion-proof zone requirements; the explosion-proof junction box has an IP65 protection rating, and the cable tray uses galvanized steel plate for corrosion protection. The motor power is selected based on the processing capacity with a margin of safety. The frequency converter uses vector control for soft starting, and power consumption is metered by a smart meter. The entire condensate collection unit is installed on a concrete platform with a concrete grade that meets the equipment's dynamic load requirements. Anchor bolts are pre-embedded for positioning. During the equipment commissioning phase, leveling is performed, with a levelness error of less than 0.5 mm / m. Coupling alignment data is recorded in the installation report. The operation and maintenance manual includes daily inspection items, covering indicators such as vibration, temperature, and abnormal noise. The spare parts list specifies the models and replacement cycles of key components.

[0065] Example 2: See Figure 3The optical sensor array of the water quality monitoring unit is deployed in a distributed architecture at key locations along the condensate flow path. Each measurement node in the optical sensor array includes a light source emitter and a photodetector. The light source emitter uses an 860 nm infrared LED to ensure penetration, and the photodetector uses a silicon photodiode to detect the intensity of scattered light. Measurement nodes are installed at the inlet, middle, and outlet sections of the collection chamber. The inlet node monitors the turbidity baseline of the raw condensate, the middle node captures water quality changes during filtration, and the outlet node verifies the final effluent quality. The sampling frequency of the optical sensor array is set to collect data 10 times per second. The photoelectric signal is processed by a current-to-voltage conversion circuit, and the voltage value is digitized by an analog-to-digital converter. The optical sensor array is calibrated using a standard turbidity solution with a concentration gradient covering the range of 0-100 NTU. The calibration curve is stored in non-volatile memory. During on-site measurement, light scattering intensity and transmittance data are collected simultaneously. Light scattering intensity data reflects the concentration characteristics of suspended particles, while transmittance changes reflect the color and transparency characteristics of the water body. The optical sensor array's housing has an IP68 protection rating, with sapphire crystal for scratch protection and fluororubber for high-temperature hydrolysis as the sealing material. At the final outlet, a ring-shaped electrode assembly is coaxially embedded in the pipe wall. These platinum-plated electrodes are precisely spaced to create a uniform electric field. A multi-frequency AC signal (1kHz-10kHz) is applied to the ring electrode assembly, with the voltage amplitude controlled within a safe range. Polarization effects on the electrode surface are eliminated through frequency switching. Conductivity measurements are obtained by extracting the effective component using a phase detection circuit. A PT100 platinum resistance temperature sensor is mounted close to the electrodes, and the temperature compensation algorithm is based on polynomial fitting to correct the conductivity value.

[0066] Optical and conductivity data are transmitted to the central processing unit (CPU) via a fieldbus. The CPU's data fusion module performs timestamp alignment. Water quality parameters at each sampling point include turbidity gradient, pH offset, and metal ion concentration. The turbidity gradient is calculated using the light scattering intensity difference between three consecutive sampling points. pH is measured using a glass electrode to measure hydrogen ion activity. Metal ion concentration is derived from the correlation between conductivity and ion type. The metal ions detected in this system are common in industrial steam condensate: calcium, magnesium, iron, and copper ions. These ions are characteristic ions introduced during corrosion and circulation processes in steam pipelines and industrial heat exchange equipment. For these characteristic ions, the correlation between conductivity and ion type is achieved through ion characteristic response calibration. Specifically, during the initialization phase of the water quality monitoring unit, the system performs single-ion conductivity calibration on the target ions in the condensate, acquiring the single-ion conductivity response characteristics of calcium, magnesium, iron, and copper ions in pure water. The conductivity signals of each ion are free from cross-interference and can be transmitted via the multi-frequency AC signal of the conductivity detection device. The system uses a 1kHz-10kHz frequency band to distinguish signals from different ions. During actual detection, the total conductivity of the condensate detected by the ring electrode group is the sum of the conductivity values ​​of the aforementioned characteristic ions. Based on pre-stored single-ion conductivity response characteristics, the system decouples the total conductivity signal and derives the concentrations of calcium, magnesium, iron, and copper ions. The correspondence between conductivity and ion type is adapted to the industrial steam condensate water quality scenario processed by this system. The system can update the pre-stored single-ion conductivity response characteristics in the central processing unit according to the actual industrial production conditions, achieving adaptive detection of characteristic metal ions under different conditions. The water quality parameter set data structure uses JSON format for storage, and a time-series database records the historical trend of each parameter. Data compression algorithms reduce storage space usage. The generation of the water quality parameter set triggers the calculation process of the condensate pollution accumulation index. The calculation engine extracts datasets from the water quality parameter set for three consecutive sampling periods. The turbidity rise rate was fitted to a time series curve using the least squares method, with the curve slope serving as a quantitative indicator of turbidity change. Ion concentration fluctuation was calculated as the standard deviation of the sampled data, reflecting the dispersion of ion concentration. The historical mean was taken from 30 days of baseline data during normal system operation; the comparison between the current period data and the historical mean yielded a relative percentage deviation. The cumulative runtime of the collection unit's inner wall was read from the equipment's operating timer and converted to hours for calculation. The pollution degree deviation coefficient was obtained by multiplying the deviation percentage by a weighting factor, which was set according to the importance classification of water quality parameters. The adhesion tendency index was calculated based on the cumulative runtime and material characteristics, with the material characteristic coefficient considering the roughness factor of the stainless steel surface.The pollution degree deviation coefficient and the adhesion tendency index are input into a nonlinear combination function. The nonlinear combination function is processed using the Sigmoid activation function, and the output result is normalized to the condensate pollution accumulation index in the range of 0-100.

[0067] The maintenance cycle of the optical sensor array is set according to the operating environment. The optical window is cleaned using an automatic scraping device with PTFE (polytetrafluoroethylene) scrapers. Polarization issues in the ring electrode assembly are mitigated using current reversal technology, with the current reversal frequency switching synchronously with the measurement frequency. The central processing unit's algorithm updates support online upgrades; upgrade files are digitally signed for security verification, and the system log records all parameter modifications. The temperature compensation coefficient of the conductivity detection device can be configured on-site, adjusted according to actual water quality. The configuration interface offers expert and wizard modes. Data communication uses the industrial Ethernet protocol with a star network topology, and the switch equipment supports redundant ring network functionality. Access permissions for water quality parameter sets are hierarchically managed: operators can only view real-time data, engineers can modify alarm thresholds, and administrators have parameter calibration permissions. The calculation frequency of the pollution accumulation index is synchronized with the sampling cycle. Each sampling cycle generates a new condensate pollution accumulation index, and the index value is displayed on the interface using color coding. Green indicates a normal state, yellow indicates an observation state, and red triggers a cleaning command. The historical data trend analysis function supports multi-period comparison, and the comparison charts show the index change patterns in different time periods. The report generation module outputs statistical summaries.

[0068] The installation location of the optical sensor array is optimized through fluid simulation, avoiding dead zones and eddy current areas. The sensor probe insertion depth is one-third of the pipe diameter. The cable shielding of the ring electrode assembly adopts a double-layer braided mesh design, with single-point grounding of the shielding layer to eliminate ground loop interference. The signal conditioning circuit includes a common-mode rejection module. The central processing unit's cabinet meets electromagnetic compatibility standards and is equipped with a temperature control device; the cooling fan speed automatically adjusts with temperature. The data backup strategy for the water quality parameter dataset includes local backup and cloud synchronization. Local backup is stored on a solid-state drive, while cloud synchronization uses differential transmission to save bandwidth. Data integrity is ensured through cyclic redundancy check (CR). An error detection mechanism automatically retransmits abnormal data, and data is cached in local storage during network interruptions. The system clock is synchronized via a network time protocol, with timestamp accuracy down to the millisecond level. Event logs include operator ID and operation time. Fault diagnosis of the optical sensor array is based on a self-test program, which runs LED tests and receiver sensitivity tests, with fault codes displayed on status indicator lights. Electrode wear monitoring of the ring electrode assembly is achieved by measuring the inter-electrode resistance; when the inter-electrode resistance exceeds a threshold, electrode replacement is prompted. The central processing unit's watchdog circuit monitors the program's running status. If the program crashes, it automatically resets the processor, and the reset event is recorded in the system log.

[0069] The pollution accumulation index calculation model supports offline training, using supervised learning on historical datasets, with model parameters optimized via gradient descent. Online learning allows for model fine-tuning, requiring administrator authorization. Model version management records each change. Validation of calculation results is achieved by comparing with laboratory analysis data, which can be imported into Excel format with customizable data mapping. Calibration data for the optical sensor array is stored in a calibration coefficient table, including temperature compensation coefficients and nonlinear correction parameters. The calibration cycle is set based on usage frequency. Electrolyte contamination of the ring electrode assembly is addressed through ultrasonic cleaning. The ultrasonic cleaner's transducer frequency is 40kHz, and the cleaning cycle is set based on water hardness. Central processing unit memory allocation uses a static allocation method, with memory leak detection tools periodically scanning and memory fragmentation handled through compression algorithms. The water quality parameter set display interface supports multilingual switching, with language packs including Chinese and English versions and adaptive font size. Data export formats include PDF and CSV. PDF reports include company logos and watermarks, while CSV files include data units and annotations. Alarm notifications include audible and visual alarms and SMS alerts. Alarm priorities are divided into normal alarms and emergency alarms, and operator confirmation requires inputting their employee ID. The pollution accumulation index calculation is parallelized, leveraging the advantages of multi-core processors. The computational task is decomposed into multiple threads, with thread priorities set according to real-time requirements. Intermediate results are stored in a cache using a first-in-first-out (FIFO) management strategy; data is transferred when the cache overflows. Computational resource monitoring is achieved through performance counters, displaying CPU and memory utilization in real time. A load balancing mechanism is activated when resources are overloaded.

[0070] Example 3: The generation mechanism of the cleaning instruction signal relies on a pre-trained classification decision tree model. The input variable of the classification decision tree model is the condensate contamination accumulation index, which is a dimensionless value ranging from 0 to 100. The classification decision tree model divides the input space into multiple regions using a recursive splitting method, with each region corresponding to a cleaning level label. The cleaning level labels are divided into three categories: low-level, medium-level, and high-level. The decision rules of the classification decision tree model are trained based on historical operating data. The training data contains thousands of labeled samples, with the sample features being the condensate contamination accumulation index and its corresponding optimal cleaning level label. The classification decision tree model uses Gini impurity as the splitting criterion. The structure of the classification decision tree model includes a root node, internal nodes, and leaf nodes. The root node corresponds to the entire input space, internal nodes perform conditional tests, and leaf nodes store cleaning level labels. The conditional test takes the form of a threshold comparison of the condensate contamination accumulation index, and the threshold parameter is optimized through the training process. The depth of the classification decision tree model is limited to 5 layers to prevent overfitting. Pruning techniques are used to simplify the model structure, and the model accuracy is evaluated through cross-validation.

[0071] Cleanliness level labels are mapped to specific operating parameters. High-pressure flushing pressure ranges from 5 MPa to 15 MPa. Low-pressure levels correspond to a low-level cleanliness level label set to 5 MPa, medium-pressure levels to a medium-level cleanliness level label set to 10 MPa, and high-pressure levels to a high-level cleanliness level label set to 15 MPa. The ultrasonic frequency range is adjusted according to the cleanliness level label: low-frequency range for loose deposits (20 kHz to 40 kHz) and high-frequency range for hardened scale (40 kHz to 60 kHz). The duration of action is associated with the cleanliness level label: short-time cleaning for routine maintenance is set to 10 minutes, medium-time cleaning to 20 minutes, and long-time cleaning for deep treatment to 30 minutes. Standardized control commands are encapsulated using data structures and communication protocols. The data structure includes field identifiers, parameter values, and checksums. Field identifiers distinguish parameters such as high-pressure flushing pressure, ultrasonic frequency range, and duration of action. Parameter values ​​are stored in floating-point format, and the checksum uses a cyclic redundancy check algorithm to ensure data integrity. The communication protocol is based on the Industrial Ethernet standard, and the data frame includes a preamble, destination address, source address, data payload, and frame check sequence. Cleaning command signals are transmitted to the self-cleaning actuator via a digital input / output module, with transmission delay controlled at the millisecond level.

[0072] The self-cleaning actuator's startup process sequentially activates the rotary nozzle array and the ultrasonic oscillator. The rotary nozzle array's drive motor uses a stepper motor for precise positioning, with a step angle of 1.8 degrees. The nozzle layout of the rotary nozzle array is optimized through computational fluid dynamics simulation, ensuring the nozzle spray angle covers the entire surface of the condensate collection unit's inner wall. A high-pressure water pump provides the required pressurized water flow; the pump's plunger is made of ceramic to resist wear, and a pressure regulating valve maintains stable output. The ultrasonic oscillator's transducer converts electrical energy into mechanical vibration; the transducer's piezoelectric ceramic element deforms under an alternating electric field. The vibration frequency is precisely controlled by a function generator with a frequency resolution of 0.1Hz. The ultrasonic oscillator's power amplifier uses a Class D amplification architecture for improved efficiency, and a heat sink ensures long-term operational stability. Ultrasonic waves propagate in the liquid, generating cavitation; the collapsing cavitation bubbles release energy to decompose deposits. Cleanliness status feedback data is acquired based on multi-sensor fusion; a flow meter installed on the sewage pipe measures the volume of sewage discharged per unit time. The flow meter uses an electromagnetic measurement principle, achieving a measurement accuracy of 0.5% of full scale. The volume change curves are recorded once per second, and the curve data is stored in a circular buffer. Vibration sensors, which are accelerometers, are installed at key locations on the inner wall to monitor the vibration response under ultrasonic waves, with a frequency response range covering 10Hz to 10kHz.

[0073] Clean coverage is calculated by analyzing the slope characteristics of the volume change curve. The calculation of clean coverage is based on the following relationship:

[0074]

[0075] in: Indicates cleaning coverage. The base of the natural logarithm. These are system characteristic constants. It is the rate of change of volume. The vibration spectrum characteristics are represented by time. The vibration spectrum characteristics are transformed from the time domain to the frequency domain using a Fast Fourier Transform, with the spectral peaks corresponding to the natural frequencies of the sediment. The residue thickness is derived from the attenuation rate of the vibration signal; the attenuation rate is inversely proportional to the residue thickness.

[0076] The cleaning status feedback data structure includes fields such as timestamp, cleaning coverage, and residue thickness, with the timestamp synchronized to a network time protocol server. Data transmission uses a publish-subscribe model, with subscribers including the central control system and the log recording system. An anomaly detection algorithm analyzes the cleaning status feedback data in real time, triggering an alarm when deviations exceed a threshold. Historical data is used to optimize cleaning parameters, and machine learning algorithms identify the optimal cleaning strategy. The control algorithm for the rotating nozzle array implements path planning, ensuring that the nozzle trajectory covers the entire inner wall surface. The nozzle movement speed is adjusted according to the cleaning level label, with a smooth speed change curve to avoid impact. The ultrasonic oscillator's frequency scanning mode covers multiple resonant points, and the frequency scanning rate is adaptively adjusted according to the type of deposit. An impedance matching network ensures efficient transmission of ultrasonic energy, and the matching network parameters can be dynamically configured. The visualization interface for the cleaning status feedback data displays real-time curves and historical trends, and operators can set areas of interest for magnified display. The reporting function generates cleaning efficiency statistical reports, including indicators such as cleaning cycle duration and energy consumption data. The data export interface supports standard formats, and third-party analysis tools can further process the data. The system maintenance module predicts component lifespan, and replacement reminders are generated based on actual operating time.

[0077] Example 4: The generation of reusable industrial water begins in the ion exchange resin bed treatment stage. The ion exchange resin bed is filled with a mixed ion exchange resin, which is a combination of strong acidic cation exchange resin and strong basic anion exchange resin in a specific ratio. The cleaned condensate flows through a columnar container in a laminar flow state, achieved by controlling the flow velocity to be below 0.5 m / s and maintaining a Reynolds number below 2000 to ensure stable flow. The functional groups of the mixed ion exchange resin undergo exchange reactions with ions in the water; sulfonic acid groups capture calcium and magnesium ions, while quaternary ammonium groups adsorb chloride and sulfate ions. The columnar container is designed with a height-to-diameter ratio of 3:1 to optimize contact efficiency. The resin bed height is fixed by upper and lower sieve plates, and a pressure drop sensor monitors the bed resistance. Saturation of the ion exchange resin bed is determined based on the outlet water conductivity value. A conductivity sensor is installed in the outlet pipe of the columnar container, and a threshold of 50 μS / cm is set to trigger the regeneration program. The resin adsorption capacity is related to the influent ion concentration, and the operating cycle is predicted by the cumulative treated water volume. A safety factor of 1.2 is used to ensure reliability. When the regeneration process starts, the system automatically switches to the standby ion exchange resin bed, which is in standby mode to ensure continuous operation.

[0078] The regeneration process uses a counter-flowing sodium chloride solution, with the sodium chloride concentration controlled within the range of 8%-10%, and the regeneration solution temperature maintained at 40℃ to improve efficiency. The counter-flow method involves the resin bed entering from the bottom and exiting from the top, with a flow rate controlled at 2-4 m / h. A regeneration solution distributor ensures uniform flow. The regeneration waste liquid contains a high concentration of metal ions; it is introduced into a neutralization reaction tank and mixed with alkaline solution. The pH is adjusted to the neutral range before discharge. An activated carbon adsorption tower is connected in series after the ion exchange resin bed. The activated carbon adsorption tower is filled with coconut shell-based activated carbon with an iodine value of not less than 1000 mg / g to ensure adsorption capacity. The activated carbon adsorption tower is designed as a dual-tower structure for continuous operation. The switching valve uses a pneumatic actuator, and the water flow direction inside the tower is bottom in and top out. Organic impurities and chloride compounds are adsorbed by the pores of the activated carbon. The empty bed contact time is designed to be 10 minutes, and the pressure vessel is made of 316L stainless steel. A nanoscale membrane filter serves as the final purification unit. The membrane material of the nanoscale membrane filter is polyvinylidene fluoride, with a pore size distribution of 0.1-0.2 micrometers. The membrane filter employs a dead-end filtration mode, with transmembrane pressure differential controlled by a variable frequency pump, and membrane fouling index monitored in real time. Backwashing cycles are triggered by increases in pressure differential; sodium hypochlorite is added to the backwash water to inhibit biofouling, and membrane flux recovery rate is verified using a flow meter. Refer to Table 1; the regeneration efficiency of the ion exchange resin is evaluated using a parameter table.

[0079] Table 1: Regeneration Performance Parameters of Ion Exchange Resins

[0080]

[0081] The replacement index for the activated carbon adsorption tower is based on adsorption capacity decay; the replacement procedure is triggered when the total organic carbon removal rate falls below 80%. Activated carbon regeneration employs a thermal regeneration method, restoring activity at a regeneration temperature of 800℃, with a loss rate of approximately 5% per cycle. The integrity test of the nanoscale membrane filter uses a pressure decay method, with the test pressure set at 0.2 MPa and the decay rate standard set at no more than 5% per minute. The control logic of the entire treatment system is implemented based on a programmable logic controller (PLC), which collects data from various sensors and executes sequential control. The human-machine interface displays the process flow diagram, with a real-time data refresh cycle of 1 second and a historical data storage cycle of 30 days. The alarm management system provides tiered management of abnormal conditions, with early warning levels indicating attention and alarm levels requiring immediate action. Data communication uses the PROFIBUS / USDP protocol with a transmission rate of 12 Mbps and single-point grounding of the cable shield.

[0082] The chemical cleaning procedure for the ion exchange resin bed is performed regularly, using alternating cleaning with hydrochloric acid and sodium hydroxide, with a cleaning cycle of 6 months. Chemical cleaning wastewater is collected and treated separately. The neutralization tank is equipped with a stirrer to promote mixing, and a pH probe is used for continuous monitoring. Bacterial control of the activated carbon adsorption tower is achieved through ultraviolet disinfection at a dose of 40 mJ / cm², and the quartz sleeve is wiped regularly. The nanoscale membrane filter is chemically cleaned using a citric acid solution with a concentration controlled at 2%, and a soaking time of 2 hours. Quality monitoring of reusable industrial water includes online instruments and offline sampling. Online instruments monitor parameters such as turbidity, conductivity, and pH. Offline samples are fully analyzed daily, including heavy metal content, total organic carbon, and total bacterial count. A check valve is installed on the effluent pipeline to prevent backflow, and the safety relief valve is set to 1.5 times the working pressure. The transfer pump uses a mechanical seal structure, and a leak detection sensor is installed at the bottom of the pump chamber, transmitting alarm signals to the control room. The packing density of the ion exchange resin bed is ensured through vibration packing, and a 30% backwashing depth is provided for resin bed expansion. The water distribution system employs a perforated plate with water caps, with 0.2 mm gaps in the water caps to prevent resin leakage. The support layer of the activated carbon adsorption tower is composed of quartz sand, the gradation of which was determined through sieving tests, and the support layer height is 400 mm. The nanoscale membrane filter uses a spiral wound structure for its membrane elements, with the membrane area calculated based on the treatment capacity, and the membrane shell material is glass fiber reinforced plastic. The automated control of the regeneration system includes metering pumps and flow meters, with the metering pump achieving an accuracy of ±1% and the flow meters using electromagnetic measurement. The regenerated liquid storage tank is equipped with a level gauge and a concentration meter, with the concentration meter using conductivity conversion and automatic temperature compensation. The stirrer in the neutralization reaction tank has an adjustable speed range of 50-300 rpm, and the impeller is a turbine type. The online monitoring instrument at the discharge outlet is connected to the environmental protection department's network, uploading data in real time and automatically alarming if standards are exceeded.

[0083] The material selection for the system piping is determined based on the characteristics of the medium. UPVC pipes are used for the ion exchange system, stainless steel pipes for the activated carbon system, and sanitary stainless steel for the membrane system. Sampling and cleaning ports are reserved in the piping layout, and the slope design ensures thorough drainage. Support spacing meets specifications. Electrical equipment protection reaches IP55, explosion-proof electrical appliances are used in explosion-proof areas, and cable trays have anti-corrosion coatings. Energy consumption of the entire water treatment system is measured by smart meters, and energy consumption data is used in efficiency calculations, with efficiency indicators displayed on the monitoring interface. Maintenance plans are based on operating time, and preventative maintenance includes component replacement and lubrication. Maintenance records are stored electronically. A spare parts management system tracks inventory status, with safety stock levels set according to the procurement cycle, and emergency procurement processes are standardized. The final quality of reusable industrial water meets the standards for production process water. The effluent pipes are connected to the recycled water network, and the network pressure is maintained by a pressure stabilizing tank. Metering instruments are installed at the user end to count the reuse volume; the data is used for water-saving benefit analysis, and the reporting system automatically generates periodic reports. System operating costs include chemical and electricity consumption. The cost accounting module calculates the unit water treatment cost, and optimization algorithms suggest energy-saving operating schemes.

[0084] Example 5: The energy recovery unit is integrated into the final treatment stage of the steam condensate recovery system. The core component of the energy recovery unit, the plate heat exchanger, is made of 316L stainless steel, with a herringbone corrugated plate shape to enhance turbulence. High-temperature wastewater discharged from the self-cleaning unit enters the hot-side channel of the plate heat exchanger tangentially. The inlet temperature of the high-temperature wastewater is maintained within the range of 75-85℃, and the flow rate is controlled by a variable frequency pump within ±5% of the rated flow rate. Newly entering steam condensate flows counter-currently from the cold-side channel of the plate heat exchanger. The cold-side inlet temperature is approximately 20-25℃ of the ambient temperature. The logarithmic mean temperature difference of the plate heat exchanger is maximized through optimized channel layout. The sealing system of the plate heat exchanger uses EPDM rubber gaskets, with the gasket compression rate controlled at 25%-30% to ensure sealing performance. The clamping plate applies uniform pressure through a hydraulic bolt assembly. Heat transfer calculations are based on dynamic adjustment of the heat transfer coefficient K, with the K value set within the range of 2000-3000 W / m²·K. The fouling coefficient is periodically corrected according to the water hardness. After heat exchange in the plate heat exchanger, the temperature of the high-temperature wastewater drops to 40-45℃. The cooled wastewater then flows into the sedimentation tank by gravity. The sedimentation tank is designed as a horizontal flow structure with a length-to-width ratio greater than 4:1.

[0085] The sedimentation tank features a distribution wall at the inlet to evenly distribute water flow. The opening ratio of the distribution wall is determined through hydraulic calculations. A sawtooth overflow weir controls the liquid level at the outlet. Solid particles settle within the sedimentation tank at a velocity described by Stokes' law. This settling velocity is optimized by adding flocculant, with the flocculant dosage automatically adjusted based on turbidity. A sludge scraper installed at the bottom of the sedimentation tank continuously collects sludge. The scraper's operating speed is matched to the sludge production. The collected sludge enters a dewatering system for processing. The dewatering system consists of a centrifugal dewatering machine and a thermal dryer. The centrifugal dewatering machine's separation factor is set within the range of 2000-3000G, reducing the moisture content of the dewatered sludge to 75%-80%. The thermal dryer uses indirect heating, with the heat medium temperature controlled at 120-150℃. The dried solid particles have a moisture content of less than 10%. A molding device compresses the dried solids into uniformly sized, harmless waste blocks. The optimized control of the energy recovery unit relies on a real-time monitoring network. A PT100 platinum resistance temperature sensor measures the temperature difference between the fluids on both sides of the plate heat exchanger, with a measurement accuracy of ±0.1℃. An electromagnetic flowmeter detects the instantaneous flow rate of the hot and cold fluids, and the flow ratio is dynamically adjusted by a PID controller, with a pneumatic regulating valve as the actuator. Heat transfer efficiency is calculated based on the heat balance equation; the efficiency value is displayed on the human-machine interface and recorded in a historical database. A declining efficiency trend triggers an early warning signal.

[0086] When the scaling detection sensor detects a 10% decrease in the surface heat transfer coefficient of the plate heat exchanger, the system automatically switches to the backup flow channel, which has the same structural parameters as the main flow channel. The pulse backwash mode uses a water-air mixed flushing method, with a flushing pressure of 1.5 times the operating pressure and a pulse frequency of 2Hz for 3 minutes. Backwash wastewater is discharged into the wastewater treatment system, and the flushing effect is verified by pressure drop changes. The heat transfer efficiency is recalculated after production resumes. The energy conversion rate of the heat exchange is recorded every 15 minutes. The energy conversion rate data is used to generate a heat exchange performance decay curve, and the mathematical model of the decay curve is fitted using an exponential decay function. Predictive maintenance cycles are based on the inflection point of the decay curve. Maintenance plans are generated 24 hours in advance, and spare parts preparation is carried out simultaneously with maintenance work. Pressure loss monitoring of the plate heat exchanger is achieved through a differential pressure transmitter with a range covering 0-100 kPa. Increased pressure loss is positively correlated with the degree of scaling. The solids flux parameters of the sedimentation tank are controlled below 120 kg / m²·d. The solids flux is calculated by multiplying the sludge concentration and settling velocity, and monitoring data ensures that the sedimentation tank operates under optimal conditions. A sludge return system returns a portion of the settled sludge to the inlet, with the return ratio controlled at 30%-50% to enhance flocculation. The amount of excess sludge discharged is determined based on the sludge age. The molding pressure of the harmless waste blocks is set at 20 MPa, the mold size is 100 mm × 100 mm × 50 mm, and the compression cycle is 30 seconds per cycle. The bulk density of the waste blocks reaches 1.2 g / cm³ for easy transportation and storage. Leaching toxicity tests meet the hazardous waste identification standards, and resource utilization pathways include building material additives and roadbed materials.

[0087] The heat recovery efficiency of the energy recovery unit was verified through heat balance calculations. The difference between the heat brought in by high-temperature wastewater and the heat absorbed by newly entering steam condensate was less than 5%, and the system heat loss was minimized through optimization of the insulation layer thickness. Rock wool products were selected as the insulation material, and the insulation layer thickness was determined based on calculations of the medium temperature and ambient temperature. The surface temperature was required to be no higher than the ambient temperature by 10°C. The control system adopted a modular programming structure. The temperature regulation module, flow control module, and cleaning control module worked relatively independently yet collaboratively. The communication protocol used Modbus TCP for data exchange. The operator station displayed the real-time operating parameters of the energy recovery unit, and the trend curve supported multi-variable coaxial display. The alarm management system classified and handled abnormal conditions according to priority. The performance testing of the energy recovery unit included thermal and mechanical tests. Thermal tests measured the ratio of actual heat exchange to theoretical heat exchange, while mechanical tests verified the operational reliability of the pump and valve equipment. The test report served as the basis for system acceptance. The operation and maintenance manual included daily inspection items and periodic maintenance content, and training materials enabled operators to master the system characteristics and processing procedures. Spare parts management for plate heat exchangers utilizes a barcode traceability system. Barcodes contain information such as equipment number, commissioning date, and maintenance records; scanning the equipment retrieves its entire lifecycle data. Settling efficiency in the sedimentation tank is monitored using an online turbidity meter installed in the effluent channel to continuously measure water quality. Data is transmitted to the central control room for process control. The energy recovery unit's linkage with pre- and post-treatment units is achieved through process interlocks. When a downstream unit shuts down, the energy recovery unit automatically adjusts its operating parameters, and system protection functions prevent equipment damage. Energy consumption statistics include electricity and chemical consumption, with energy consumption indicators calculated based on treated water volume. Benchmarking management identifies areas for improvement and continuously optimizes system performance.

[0088] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0089] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A steam condensate recovery system with automated cleaning function, characterized in that, include: The condensate collection unit is used to receive and store steam condensate generated during industrial production. It separates solid particles and suspended matter in the condensate through a multi-stage filtration structure to generate pre-purified condensate. The water quality monitoring unit, based on an optical sensor array and a conductivity detection device, collects data on turbidity, pH, and ion concentration of the pre-purified condensate in real time, and generates a set of water quality parameters. The cleaning triggering unit dynamically calculates the condensate pollution accumulation index based on the turbidity threshold and ion concentration change rate in the water quality parameter set, and generates a cleaning instruction signal based on the condensate pollution accumulation index. The self-cleaning actuator, in response to the cleaning command signal, starts the rotating nozzle array to perform high-pressure rinsing on the inner wall of the condensate collection unit, while activating the ultrasonic oscillator to decompose the attached deposits and generate cleaning status feedback data. The recycled water treatment unit receives the cleaned condensate and further removes dissolved impurities through an ion exchange resin bed and an activated carbon adsorption layer to generate reusable industrial water. The calculation steps for the condensate pollution accumulation index are as follows: Extract the turbidity rise rate and ion concentration fluctuation range for three consecutive sampling periods from the water quality parameter set; By comparing the current period data with the historical average, the pollution level deviation coefficient is obtained. The adhesion tendency index of pollutants is calculated by combining the cumulative operating time on the inner wall of the collection unit; The cumulative contamination index of condensate is output based on the nonlinear combination of the deviation coefficient and the adhesion tendency index.

2. The steam condensate recovery system according to claim 1, characterized in that, The steps for generating the preliminary purified condensate are as follows: When steam condensate flows into the collection chamber, the water is guided to pass through a series of stainless steel screens with decreasing apertures in sequence to intercept solid particles of different sizes. A centrifugal separator is used to apply a swirling force to the condensate that has passed through a screen, causing suspended solids with a density higher than that of water to settle to the bottom of the separation chamber. The separated upper liquid is introduced into a multi-layer fiber filter medium to capture residual micron-sized particles and output pre-purified condensate.

3. The steam condensate recovery system according to claim 1, characterized in that, The steps for generating the set of water quality parameters are as follows: Distributed optical sensors were deployed along the flow path of condensate water to measure changes in light scattering intensity and transmittance in different sections of the water body. A ring electrode assembly was installed at the final outlet to detect the real-time conductivity and temperature compensation value of the condensate. By integrating optical and electrochemical data, and labeling the turbidity gradient, pH shift, and metal ion concentration of sampling points according to time series, a set of water quality parameters is constructed.

4. The steam condensate recovery system according to claim 1, characterized in that, The steps for generating the cleaning instruction signal are as follows: The cumulative pollution index of condensate water is input into a pre-trained classification decision tree model to match the corresponding cleanliness level label. Select the high-pressure flushing pressure value, ultrasonic frequency range, and duration of action according to the cleanliness level label; The above parameters are encapsulated into standardized control commands to generate cleaning command signals.

5. The steam condensate recovery system according to claim 1, characterized in that, The steps for generating the cleaning status feedback data are as follows: During the high-pressure flushing process, the volume change curve of the discharged wastewater per unit time is recorded by a flow meter; Vibration sensors were used to monitor the peeling strength of deposits on the inner wall under ultrasonic waves. By analyzing the slope of the curve and the characteristics of the vibration spectrum, the cleaning coverage and the thickness of the residue are determined, and cleaning status feedback data is generated.

6. The steam condensate recovery system according to claim 1, characterized in that, The steps for generating the reusable industrial water are as follows: The cleaned condensate is passed through a columnar container filled with mixed ion exchange resin in a laminar flow state to replace calcium and magnesium ions in the water. The effluent is guided into activated carbon adsorption towers arranged in series to adsorb organic impurities and chlorine compounds; A nanometer-scale membrane filter is installed at the final outlet to trap any remaining colloidal substances, resulting in reusable industrial water.

7. The steam condensate recovery system according to claim 6, characterized in that, The regeneration step of the ion exchange resin is as follows: Monitor the ion adsorption saturation of the resin bed and trigger the regeneration program when the conductivity of the effluent exceeds the set threshold. The resin layer is rinsed with a counter-current sodium chloride solution to release the adsorbed metal ions; Collect the recycled waste liquid and introduce it into a neutralization reaction tank. After adjusting the pH, it is discharged.

8. The steam condensate recovery system according to claim 1, characterized in that, Also includes: The energy recovery unit captures the waste heat from the high-temperature wastewater generated by the self-cleaning execution unit and preheats the newly entering steam condensate through a plate heat exchanger; The low-temperature wastewater after heat exchange is introduced into a sedimentation tank for solid-liquid separation, and the separated dry solids are compressed into harmless waste blocks.

9. The steam condensate recovery system according to claim 8, characterized in that, The optimization steps for waste heat recovery are as follows: Real-time monitoring of the fluid temperature difference and flow ratio on both sides of the heat exchanger, and dynamic adjustment of the sewage flow rate to maintain optimal heat transfer efficiency. When scale buildup is detected on the heat exchanger surface, the system automatically switches to the backup flow path and initiates the pulse backwash mode. Record the energy conversion rate of each heat exchange to generate a heat exchange performance degradation curve for predicting maintenance cycles.

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