The estimated number of flights per day in the world is 176,000. Each of these flights involves a huge amount of technology to operate and maintain its highest operating status to move millions of passengers flying to various destinations around the world.

According to the recent NASA Ames Research Center paper, “the occurrence of defects in an aircraft could affect not only the ‘health’ of that particular aircraft but also the surrounding airspace in certain cases.

The Aircraft Health Management (AHM) market is projected to increase from USD 6.3 billion in 2023 to USD 8.6 Billion by 2028, with a projected CAGR of 6.5 percent between 2023 and 2028, according to Markets and Markets Studies estimate.

What is AHMS/ ACMS (Aircraft Health/ Control Monitoring System)?

Aircraft Health Monitoring Systems (AHMS) uses real-time data from multiple sensors that are integrated into aircraft components/parts to increase aircraft safety and reliability. With thousands of passenger aircraft flying daily, these systems help maintain operational safety in modern aircraft. AHMS consists of hardware and software instruments, solutions, and techniques that conduct remote surveillance of aircraft to learn their present or potential serviceability.

Aircraft health control services are a crucial component of aircraft operations (AHMS). These systems make use of sensor-captured data in real-time and transfer data to the ground station team via Wi-Fi, GSM, or SatCom to improve reliability and safety and cope with potential concerns as soon as possible.

These systems greatly decrease inspection time as they replace visual checks, X-rays, and traditional control methods with AHMS system procedures. AHMS is combined with machine learning, IoT-enabled sensor technologies, and other sophisticated data processing systems. In the aviation sector, the AHMS market is estimated to grow at a CAGR of 7.1% from 2025 to 2034.

The aircraft health monitoring system consists primarily of two components: The Airborne health monitoring subsystem (AHMS), the Ground Health Diagnostics Subsystem (GHMS).

Various factors increase the need for aircraft industry health surveillance systems. Some of them are-

• Increased need to enhance the aircraft’s safety, efficiency, and operational effectiveness.
• Increased demand for a system for real-time aircraft data monitoring
• Another significant factor contributing to the growth of demand for aircraft health monitoring systems is the increased adoption of connected aircraft solutions.
• The need to decrease MRO (Maintenance, Repair, and Overhaul) costs is another aspect impacting the implementation of sophisticated aircraft health management systems.
• Efficient decision making due to real-time information.

What AHMS/ ACMS Monitors?

AHMS/ACMS is an aircraft condition monitoring system for real time monitoring of aircraft systems and critical systems using sensor data, flight data, and other operational data.

Use of Aircraft Health Monitoring System/ Condition Monitoring System

• Monitoring of gas turbine engines, including cool engine fan trim balance (CFTB)
• Analysis of vibration of the airframe structure
• Analysis of Gearbox and bearing
• Monitoring of an auxiliary power unit
• Improvement of combustion in gas turbines
• Combustion chamber roar monitoring
• System use, health monitoring, diagnostic features, and engine parameters tracking in the case of incidents.
• Monitoring of oil spoilage, etc.

Let’s look at how the Aircraft Health Monitoring System is transforming aviation by anticipating future problems.

• Constant Monitoring: The Aircraft Health Monitoring System (AHMS) collects real-time operational data from a variety of onboard sensors and systems. It thoroughly evaluates components such as engine performance, structural integrity, avionics operation, and other factors, using data collected in flight and during ground operations to support flight data monitoring and give aviation operators an overall picture of aircraft health across the entire fleet and day-to-day fleet operations.
• Predictive analytics: AHMS examines the acquired data using predictive analytics, applying algorithms and machine learning models to discover trends and irregularities. It combines engine data, flight data, and historical data to identify anomalies and potential failures, including issues tied to maintenance requirements, by evaluating past information and real-time inputs through engine health monitoring systems, enabling early issue detection that helps enhance operational safety and improve operational efficiency.
• Preventive Maintenance and Early Identification: The basis of AHMS is early detection. The system warns maintenance teams or flight crews about problems or wear-and-tear by detecting tiny deviations from typical operating parameters, helping enhance safety and improved safety while allowing prompt remedial operations that reduce maintenance costs, reduce costs, and prevent unplanned maintenance, unscheduled maintenance, unscheduled maintenance events, unplanned downtime, and minimizing downtime caused by maintenance issues.
• Data-Informed Decision-Making: AHMS provides actionable insights to aircraft operators and maintenance workers based on data analysis. This supports informed maintenance decisions before the aircraft arrives, helping maintenance teams coordinate ground operations, plan interventions for airline operations, and improve operational efficiency, operational efficiency, aircraft availability, and operational safety while also helping reduce operational costs and deliver cost savings.
• Increased safety and Dependability: The use of an Aircraft health monitoring system significantly enhances aircraft safety and reliability. It decreases the chance of in-flight mishaps or unplanned repairs by proactively identifying and addressing any problems, which helps enhance operational safety, supports critical aircraft components, and strengthens overall dependability for passengers and crew.
• The Development of AHMS Technology: The Aircraft Health Monitoring System is evolving with technology. Sensor technologies, artificial intelligence, and networking developments will dramatically boost the system’s capabilities, enabling more precise predictive analysis and more preventive actions for aircraft availability and smoother fleet operations.

Key Technology

The aircraft’s health monitoring system is extremely complex, which incorporates various core technologies, e.g., fault diagnostics system, artificial intelligence, wireless sensor network, high-speed communication, etc.

The following are the few technologies involved in the aircraft health/condition monitoring system which helps in transmitting data to the ground station on aircraft failure or malfunction in real-time.

1. Fault Diagnostics System

Fault diagnostics system consists of a database, an information base, a man-machine interface, and an inference engine. In a health monitoring system for aircraft, the aircraft condition monitoring system combines data acquisition, data analytics, and real time monitoring across aircraft systems and critical aircraft components. The database stores configuration parameters, the condition parameters of onboard systems, historical data, flight data, engine data, and other operational data. The inference engine uses the data collected to identify anomalies, assess health status, flag potential failures, and define maintenance requirements before they turn into broader maintenance issues.

This supports aircraft maintenance by helping maintenance teams make informed maintenance decisions, align work with condition based maintenance practices, and prioritize action on components that affect aircraft performance. It can also support dispatch decisions against the minimum equipment list while accounting for regulatory requirements.

Cloud based platforms can support predictive maintenance by processing sensor data and operational data from the aircraft and ground operations.

Digital twins can be layered onto this stack to model aircraft performance and health status.

2. Artificial Intelligence

Artificial Intelligence will interpret and coordinate data from sensors and submit data in a report that can be interpreted. In real-time, Artificial Intelligence uses historical data and sensor data from critical aircraft components, along with flight data and engine data, to identify anomalies, track health status, and flag potential failures while detecting and updating on possible faults and arranging correct repair timelines. This data analytics approach supports predictive maintenance, early issue detection, and engine health monitoring systems that enhance safety, improve operational efficiency, and deliver improved safety while helping reduce costs, avoid unnecessary maintenance costs, address maintenance issues, and create cost savings and stronger operational efficiency. Artificial intelligence technology is used specifically to validate the system’s malfunction deduction process, and these diagnostics can also support dispatch authorization decisions under the Minimum Equipment List.

Closed-Loop Maintenance Integration synchronizes logged faults with maintenance systems to support maintenance teams, maintenance requirements, and informed maintenance decisions.

3. Wireless sensor network

The nodes of these sensors combine the transducer, data processing unit, and a communication module connected via a wireless channel, creating an organized network framework. The sensor node monitors the hot, ultraviolet sonar, radar, and trembling signal of the local atmosphere with the assistance of various informative sensors.

Aircraft malfunction often has certain causes, such as abruptness, haphazardness, indecision, etc.

How eInfochips can help

eInfochips is a product engineering company with over 25 years of expertise in Device Engineering, Digital Engineering, Quality Engineering, and Silicon Engineering. With in-depth aerospace knowledge and end-to-end technical expertise and processes (DO-254, DO-178B, DO-178C, DO-160, and ARP-4754) knowledge, eInfochips has designed and developed an Android-based Engine Health Monitoring system for one of the industry leader.

DO-254 FPGA verification and DO-178C device verification have been supported for next-generation communication and navigation systems by eInfochips. We also provide hardware, software, systems, and mechanical engineering services for Avionics.

Contact our experts to find out more about how eInfochips will help the aerospace industry.