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

Project Title

Smart Boiler: System Analyzer Using iot and Sensing Faults

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

• Boilers are an integral part of every major industry. Their role in facilitating our life's is enormous, they make industrial process easy. Boilers applications are not only limited to power generation plants, factories but also present in food chain restaurants as well. [1]
• If left unchecked / unmonitored; they can cause damages ranging from downtime which leads to decrease in efficiency and increase in prices of product, to even blow up the whole factory which often cost human lives and infrastructure.
• Involve 3rd Party maintenance
• Maintenance cost anywhere from $150 to $1,000 or even more [2]
• Require more manpower; minimum 2 hours to even days
• Company has no previous data base
• Repeated maintenance decrease efficiency

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 system

Core Industry

Manufacturing

Other 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 Production

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com