Products

Sensors

The Analatom Inc. micro-machined LPR corrosion sensor is part of the company's structural health monitoring system. The sensor is built on well-established Linear Polarization Resistor (LPR) technology and it outputs an exact corrosion rate for material of the structure on which it is placed. The device is fabricated using semiconductor production techniques that allow for a high quality product that is low cost and robust. Analatom has relationships with many materials suppliers ensuring that sensors are available for most metals.

LPR Sensors

• Two-electrode corrosion sensor
• Two-electrode time-of-wetness and salinity sensor

Other Sensors

• Strain-gauge sensors
• Temperature / relative humidity sensors

SHM Systems

Analatom has developed a structural health monitoring system (SHMS) platform consisting of sensors, low profile, ruggedized packaging, data acquisition electronics, microcontroller (MCU), wireless communication and data analysis software. Embedded software within the MCU further enables intelligent data acquisition, processing, and decision making based on sensor data. Furthermore, the Analatom data acquisition system is open ended, and is capable of receiving data from most any sensor.

• AN110 DAQ module
• Corrosion Monitoring and Assessment Software (CMAS)

Automated Visual Inspection

Visual nondestructive inspections (NDI) for defects are critical for many maintenance, repair, and overhaul (MRO) operations and are often the most economical method of detecting surface defects before they reach dangerous sizes. These inspections are conducted in a multitude of industries, including aerospace, infrastructure, and maritime. While technologies such as robotic borescopes and aerial drones have increased number and quality of available inspection data, humans remain the primary decision makers on the acceptability of a part or surface. This manual process is often costly, time-consuming, and subject to human errors that arise from mental fatigue or boredom. Computer vision (CV) and artificial intelligence (AI) algorithms have been shown to excel at image analysis tasks and have the potential to provide accurate and reliable defect recognition for automated visual inspection systems that can significantly reduce maintenance costs and improve inspection efficiency

• Automated Inspection with Deep Learning (AIDL)