International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 09 | Sep 2024 www.irjet.net p-ISSN:2395-0072
BOILER
PERFORMANCE WITH RESPECTIVE CHEMICAL
SCALE FORMATION BY USING AI TECHNOLOGY
1Sanjay Thangamalar,2Santhosh Anbalagan,3A C Mariappan,4G Peter pakiyaraj
1Final year B.E Marine Cadet, Department Of Marine Engineering, PSNCET , Tirunelveli , Tamilnadu
2Final year B.E Marine Cadet, , Department Of Marine Engineering, PSNCET, Tirunelveli ,Tamilnadu
3Assistant Professor, Deptment Of Marine Engineering, PSNCET, Tirunelveli ,Tamilnadu
4Assistant Professor, Department Of Marine Engineering, PSNCET, Tirunelveli ,Tamilnadu
ABSTRACT:
Boiler water treatment uses chemicals to condition and treat boiler feed water. Some common chemicals used in boiler water treatment include:
Oxygen scavengers: Remove dissolved oxygen from boiler water to prevent corrosion.
Alkalinity builders: Raise the pH of boiler water to protect the boiler from corrosion and scale buildup.
Scale inhibitors: Prevent scale from forming on the inside of the boiler by coating the metal surfaces.
Corrosion inhibitors: Protect the boiler from corrosion.
Phosphates-dispersants: Neutralize the hardness of water by forming tri calcium phosphate.
Natural and synthetic dispersants: Increase the dispersive properties of the conditioning products.
Sequestering agents: Act as inhibitors and implement a threshold effect
Keywords:ACCDM,WSB,ML,RTM
1.INTROTUCTION:
ScaleformationusingAItechnologyinvolves:
1.1 Data Collection: Gathering data on boiler operating conditions, water quality, and performance metrics.
1.2 Machine Learning (ML) Model Development: Machine learning in boilers refers to the application of advanced data analysis and modeling techniques to predict, detect, and optimize boiler operations.
1.3 Pattern Recognition: Pattern recognition in boilers involves using algorithms to identify and interpret meaningful patterns in data generated by various sensors andmonitoringsystems.
1.4 Predictive Analytics: Predicting when a boiler component is likely to Fail, allowing for proactive maintenance.
1.5 Real-time Monitoring: Real-time monitoring on boilersinvolvescontinuouslytrackingandanalyzingdata from various sensors and systems to ensure safe, efficient,andreliableoperation.
1.6 Optimization: achieve maximum efficiency, reliability, and safety while minimizing energy consumption,emissions,andmaintenancecosts.
2. AI technologies used:
2.1 Neural Networks: A neural network on a boiler is a machine learning model that uses artificial neural networks to predict, monitor, and optimize boiler performance.
2.2 Decision Trees: Decision Trees on a boiler are a machinelearning model thatusesa tree-likestructure to predict, classify, or optimize boiler performance.
2.3 Clustering: Clustering on a boiler is a machine learning technique that groups similar data points or operatingconditionsintoclusters
Regression Analysis: For predicting scale formation and boilerperformance.
2.4 Benefits:
1.ImprovedBoilerEfficiency
2.ReducedMaintenanceCosts
3.ExtendedEquipmentLife
4.EnhancedSafety
By leveraging AI technology, boiler operators can proactively address chemical scale formation, ensuring optimalperformanceandminimizingdowntime.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 09 | Sep 2024 www.irjet.net
3.Chemical test for boiler water:
4. Different types of sensors used on boiler:
Figure-1 types of sensor Thesearethevarioussensorsusedonboiler.
4.1PH Detector:
A pH detector on a ship's boiler measures the acidity or alkalinity of the water, ensuring it remains within a safe rangetopreventcorrosion.
4.2Alkalinity detector:
The alkalinity detector measures the concentration of alkaline substances (such as hydroxide, carbonate, and bicarbonate ions) in the boiler water. This ensures the waterremainswithinasafeph.
4.3 Phosphate Detector:
A phosphate detector on a ship's boiler measures the concentration of phosphate ions in the boiler water.
4.4Chlorate Detector:
A chlorate detector on a ship's boiler measures the concentration of chlorate ions in the boiler water.
4.5Conductivity test Detector:
p-ISSN:2395-0072
Aconductivitytestdetectoronashipmeasurestheability of the boiler water to conduct electricity, indicating the presenceofdissolvedsolidsandcontaminants.
Figure-2: Chemical Level
5. AUTOMATED CHEMICAL CONTEND DETECTING MACHINE:
Figure: Automated chemical content
Chemical Content Detecting Machine (CCDM) is an automated system that continuously monitors and controlsthechemicalcontentinaboiler'swater,ensuring optimallevelsforefficientandsafeoperation.
5.1Usage:
 Water sampling: CCDM takes a continuous water sample from the boiler.
 Chemical analysis: The system analyzes the sample for various chemical parameters like pH, conductivity,alkalinity,andoxygenlevels.
 Comparison with set points: CCDM compares the analyzedvalueswithpre-setlimits.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 09 | Sep 2024 www.irjet.net
 Alarm and correction: Ifvaluesexceedlimits,CCDM triggers an alarm and automatically adjustschemical dosingtorestoreoptimallevels.
 Data logging and reporting: CCDM records and reports data for maintenance, troubleshooting, and compliance.
5.2Benefit:
 Real-time monitoring: Continuous monitoring ensurespromptresponsetochanges.
 Accurate control: Automateddosingensuresprecise chemicallevels.
 Reduced manual errors: Minimizes human error in samplingandanalysis.
 Improved efficiency: Optimized chemical levels enhanceboilerperformance.
 Compliance: Meets regulatory requirements and industrystandards.
5.3 Commonly detected chemicals:
 PH
 Conductivity
 Alkalinity
 Oxygenlevels
 Hydrazine
 Phosphate
 Chloride
 Sulfite
CCDM ensures reliable and efficient boiler operation, reducingdowntime,andmaintenancecosts
6. Water softening in boiler:
Ideal process for water softening in boilers
 Pre-treatment:Removesuspendedsolids,sediment, and other impurities from the feed water using physicalmethodslikefiltrationorsedimentation.
 Softening: Use ion exchange resins to remove calcium and magnesium ions, replacing them with sodiumorpotassiumions.
 Re-mineralization: Add back beneficial minerals to the water to maintain a stable pH and prevent corrosion.
 PH adjustment: Adjust the pH to the optimal range (usually8.5-9.5)topreventcorrosionandscaling.
 Monitoring: Continuously monitor water quality, includinghardness,pH,andconductivity.
 Regeneration: Periodically regenerate the ion exchangeresinstomaintaintheireffectiveness.
 Blow down: Regularly blow down the boiler to removeaccumulatedimpuritiesandmaintain water quality.
 Chemical treatment: Add chemicals as needed to preventscaling,corrosion,andfoaming.
 Water testing: Regularlytestthewatertoensureit meetstherequiredstandards.
 Maintenance: Regularly maintain and inspect the water softening equipment to ensure optimal performance.
 By following this process, you can ensure effective water softening, preventing scaling and corrosion, andmaintainingefficientboileroperation.
Figure-4: Graph
Figure-5
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 09 | Sep 2024 www.irjet.net p-ISSN:2395-0072
7. Conclusion:
 In conclusion, the use of AI technology in analyzing boiler performance and preventing chemical scale formationoffersnumerousbenefits,including:
 Predictivemaintenanceandreal-timemonitoring.
 Optimized chemical treatment and automated control.
 Improvedefficiencyandreducedmaintenance.
 Extended equipment life and cost savings.
 Data-driveninsightsforinformeddecision-making.
ProjectGuidecumAssistant Professor
PSN College ofEngineering &Technology, Tirunelveli, Tamil Nadu. Also having 15 years’ experience in Oil and Gas industries. Specializationin NDT and worked varies GulfCountries.
Project Guide cum Assistant Professor
PSN College ofEngineering&Technology, Tirunelveli, Tamil Nadu. MEO Class-IV Marine Engineer and worked varies Countries.
aintenance costs. The integration of AI technology in boiler water treatment is a significant step forward in main
By harnessing the power of AI, boiler operators can ensure optimal performance, minimize downtime, and reduce m taining efficient and reliable boiler operations.
REFERENCE:
[1] Treatmentofsteamboilerwater ByJ.PaulGuyerP.E.,
R.A
[2] The chemical treatment of boiler water by James McCoy
[3] PracticalboilerwatertreatmentbyN.Manivasakam
BIOGRAPHIES:
I am pursuing B.E final year Marine Engineering cadet at PSN College of Engineering & Technology, Tirunelveli, Tamil Nadu
I am pursuing B.E final year Marine Engineering cadet at PSN College of Engineering & Technology, Tirunelveli,TamilNadu.