Virtual Sensor- A Technology Marvel
The power of Gas turbines is unmatched! The rotating compressor and rotor running at 14 RPM, is a key component for efficient power generation.
Flawless Functioning of Components with enhanced safety and efficiency, A Challenge? A daunting task for gas turbine engineers!
The small but mighty strain sensors in rotary elements play a critical role in measuring strain and detecting potential issues
A massive expenditure to maintain and test the machines. Losing just one sensor can cost millions and set back testing for an entire year with significant data loss.
Introducing Virtual Sensors for multi-sensor failure prediction in jet engines, potentially saving the industry billions and countless hours of maintenance and testing
Maximizing Oil Pump Performance with
Digital Twin Technology
Real-time monitoring of the pump’s operation, allowing for the identification of potential issues before they become critical
Enhancing Turbojet Efficiency with Virtual Sensor Technology
Data Acquisition System records the strain signals from turbojet engines . The raw data from the sensors used in the engine may contain discrepancies in its sampling rate. This is cleaned using statistical methods such as limit check, interquartile range, detection of point anomalies and redundant sensors and their removal. IVA’s virtual sensor tool acts as a pipeline of data pre-processing Machine learning algorithms are introduced to detect and predict failed sensor values. When a sensor fails, IVA’s tool gets activated and predicts the failed sensor values. This method can efficiently detect and isolate single or multiple sensor failures within this dynamic environment.
Reliable Data Starts with Validated Sensors
Our team of experts utilizes the latest methods to validate sensor performance in real-world conditions and provide assurance in the data they generate. As a manufacturer or end-user, our validation services offer a guarantee of the quality and dependability of your sensor systems. We understand the importance of reliable sensor data for a wide range of applications, including automotive, industrial, medical, and aerospace. Therefore, we provide comprehensive validation services that cover all aspects of sensor technology, from the initial design to final testing. Our validation process includes thorough testing of the sensors under various environmental conditions, analyzing the generated data, and providing feedback on sensor performance and accuracy.
Revving up jet engine performance by handling high frequency synchronization challenges
Accurate and reliable data synchronization is crucial for ensuring the safety of jet engines. By leveraging machine learning, potential issues and anomalies can be detected in real-time, enabling preventive measures to be taken to avoid catastrophic failures. This can automate the data synchronization process, reducing the time and effort required for manual synchronization, and improving the efficiency of jet engines.
Unparalleled insights into your engine's performance through expert interpretation of waterfall diagrams
Advanced analysis of correlation maps among different runs can be performed using image processing techniques. Interpreting waterfall diagrams created from engine strain data using deep learning involves using neural networks to analyze the complex patterns and relationships within the data. Deep learning algorithms can be trained on large datasets of waterfall diagrams to recognize specific patterns or anomalies that may be indicative of faults or performance issues within the engine.
Detect and diagnose resonating frequencies with accurate order mapping analysis
Detection of resonating frequency using order mapping involves analyzing vibration signals from jet engines, to identify the specific frequency at which the system is resonating. This is done by mapping the signals onto orders or multiples of the fundamental rotational frequency of the engine and then identifying the specific order in which the resonance is occurring.