Smart Boiler: System Analyzer Using iot and Sensing Faults

. Parameters to be monitored are given below:    1. Temperature    3. Boiler water level    4. Pressure    5. Thermal Imaging for material deterioration   After acquiring all data, we will

2025-06-28 16:29:07 - Adil Khan

Project Title

Smart Boiler: System Analyzer Using iot and Sensing Faults

Project Area of Specialization Electrical/Electronic EngineeringProject Summary Project Objectives

. Parameters to be monitored are given below:
   1. Temperature
   3. Boiler water level
   4. Pressure

   5. Thermal Imaging for material deterioration

After acquiring all data, we will send the data on cloud which can be accessed by all authorized persons around the globe. The best feature is that we will also be sending the data to manufacturing company as a feedback, which they can check for improving their products by learning from flaws. After all this we will be using Machine Learning for predictive maintenance.

Project Implementation Method

In today’s world, everything especially those things which are related to security of people and equipment are shifted towards automation to reduce error and accidents. In food industry, fertilizer industry and in many other industries boilers are currently in use. They provide huge mass production at one time reducing the time consumption and labor. We came up with a brilliant idea to do faults analysis using IOT solution to increase efficiency, reliability and to reduce downtime of boilers present in industries / factories.

In case, if these parameters are not controlled then there will be an occurrence of fault in the boiler. In order for the safety of the boiler, these parameter values have to be controlled. Therefore, a smart way of control could be done by internet of things.

By creating the webpage and the control operation can be done through the internet of things.[3] The major problem in boiler control is the monitoring and controlling of water level in a boiler drum. Controlling its level is critical because if the level becomes too low, the boiler can run dry resulting in mechanical damage of the drum and boiler piping. If the level becomes too high, water can be carried over into the steam pipework, possibly damaging downstream equipment. [4]
If temperature of steam increases boiler tubes will be puncture. Therefore, monitoring of temperature is important to avoid the problem in power plant. Measurement of water vapor content in atmosphere and surface provides the details about physical, chemical and exobiological process in the surface. Parameters to be monitored are given below:
   1. Temperature
   3. Boiler water level
   4. Pressure

    5. Thermal Imaging for material deterioration

After acquiring all data, we will send the data on cloud which can be accessed by all authorized persons around the globe. The best feature is that we will also be sending the data to manufacturing company as a feedback, which they can check for improving their products by learning from flaws. After all this we will be using Machine Learning for predictive maintenance.

It has following salient features:

  1. Practical Aspects: We will approach industries having boilers, collect their problems and try to incorporate their solutions in our project.
  2. Predictive Maintenance: The outstanding part of our project is that we will be using ML for predictive maintenance. Thus, we will be able to detect faults in advance. [5]

  

Benefits of the Project

•Preventive maintenance

•2. Accessible from all over the world

•3. Reduce cost of maintenance

•4. The company has past data as well which help in multiple purpose i.e 

•Purchasing new equipment

•Diagnostic issues

•Selling that data to researchers

Technical Details of Final Deliverable

In today’s world, everything especially those things which are related to security of people and equipment are shifted towards automation to reduce error and accidents. In food industry, fertilizer industry and in many other industries boilers are currently in use. They provide huge mass production at one time reducing the time consumption and labor. We came up with a brilliant idea to do faults analysis using IOT solution to increase efficiency, reliability and to reduce downtime of boilers present in industries / factories.

In case, if these parameters are not controlled then there will be an occurrence of fault in the boiler. In order for the safety of the boiler, these parameter values have to be controlled. Therefore, a smart way of control could be done by internet of things.

By creating the webpage and the control operation can be done through the internet of things.[3] The major problem in boiler control is the monitoring and controlling of water level in a boiler drum. Controlling its level is critical because if the level becomes too low, the boiler can run dry resulting in mechanical damage of the drum and boiler piping. If the level becomes too high, water can be carried over into the steam pipework, possibly damaging downstream equipment. [4]
If temperature of steam increases boiler tubes will be puncture. Therefore, monitoring of temperature is important to avoid the problem in power plant. Measurement of water vapor content in atmosphere and surface provides the details about physical, chemical and exobiological process in the surface. Parameters to be monitored are given below:
   1. Temperature
   3. Boiler water level
   4. Pressure

    5. Thermal Imaging for material deterioration

After acquiring all data, we will send the data on cloud which can be accessed by all authorized persons around the globe. The best feature is that we will also be sending the data to manufacturing company as a feedback, which they can check for improving their products by learning from flaws. After all this we will be using Machine Learning for predictive maintenance.

It has following salient features:

  1. Practical Aspects: We will approach industries having boilers, collect their problems and try to incorporate their solutions in our project.
  2. Predictive Maintenance: The outstanding part of our project is that we will be using ML for predictive maintenance. Thus, we will be able to detect faults in advance. [5]

  

Final Deliverable of the Project HW/SW integrated systemCore Industry ManufacturingOther Industries Petroleum , Agriculture , Food , Energy , Others Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Industry, Innovation and Infrastructure, Responsible Consumption and ProductionRequired Resources
Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Total in (Rs) 25000
Gas tank Equipment120002000
aurdino Equipment110001000
water level Equipment160006000
pressure sensor Equipment170007000
temperature sensor Equipment120002000
wires, vero board etc Miscellaneous 170007000

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