The aim of Nanoprecise Sci Corp is to provide an IoT based condition monitoring system that acts like a machine doctor.
Nanoprecise has created a “unique” patent-pending solution (hardware + software) called “RotationLF” that combines physics, material science, and data analytics to diagnose issues with physical assets such as machinery and predicts the “Remaining Time to Failure.” RotationLF sensors extract RPM, vibration, sound, temperature & humidity information all from one sensor.
RotationLF software is built on Al algorithms that are only limited to research papers until now and has been proven to be really accurate with solid customer case studies.
A wireless hardware consist consists of two unique modules, the housing and the sensor.The housing is IP68 Certified dust and water proof. The housing contains an air vent for air flow, which helps in maintaining the inside temperature and allows the sensor to monitor the humidity. Furthermore, the housing has a strong magnet installed at the bottom which allows easy 1- min non-invasive mounting. The sensor created by Nanoprecise is the only sensor in the world that can sense five different variables through one sensor.
All in One Sensor
A high-performance, multiaxis accelerometers based on MEMS technology measuring, displaying, and analyzing linear velocity, displacement and acceleration.
Specially designed for applications such as equipment noise analysis. Key to successful predictive maintenance by rapid signal interpretation.
Measure revolution-per-minute(RPM), the rotation speed of the shaft and provide the reference signal for order based vibration analysis.
Sensor to measure the surface temperature of the equipment not just surrounding ambient temperature with high accuracy
Measure the environmental humidity. A capacitive humidity sensor used in a wide range of industrial applications.
Variety of Equipments
The sensors can be deployed cost-effectively and utilized on the —70% of machinery that is not monitored today because it has not been economically viable, until now. Since Nanoprecise was founded in 2017, it’s customers are spanning across Oil & Gas, Mining, Utilities, HVAC & Infrastructure sectors.
Our software is a hybrid between edge and cloud computing. The sensor has an inbuilt FFT processing capability to diagnose mechanical failures such as shaft unbalance, misalignment, looseness, and inner race, outer race, cage and ball bearing failures along with gear failures. Furthermore, the data is transferred to our AWS Cloud where data is processed, plotted and stored. Nanoprecise uses very complex Artificial Intelligence algorithm for signal decomposition on our cloud for predictive analytics. Furthermore, as we utilize the Amazon Web Services for our cloud computing, we can implement scalable architecture to support growing business needs.
Our online portal allows the customer to login with their credentials to the dashboard where they can access all the data and graphs on a real time basis. Furthermore, this data can be downloaded in pdf and csv format for in house analytics.
Simplified. Secured. Scalable
The RotionLF is a fully wireless device. It uses WiFi to send sensed data to the cloud over secured connection.
Battery Powered & Electrical Powered
RotationLF can be powered by mains supply or a standard CR123A battery. Easy replacable batteries with life of 1-3 years depending on data uploading rate
Quick & Easy Installation
The housing of the sensor has a strong magnet installed at the bottom which allows easy 1- min non-invasive mounting.
The RotationLF is suitable for indoor and outdoor use. It is certified as IP68 and ATEX Zone 0 for use in Class 1 Div 2 environments. The device is certified with FCC certification, Industrial Canada(IC) certification, UL746 Plastic Testing certification and ASME certified.
RotationLF sends data to cloud through platforms with UL 2900-2-2 certifications and connects to the network using TLS 1.2 over a TCP connection.
RotationLF software technology is based on advanced techniques for data extraction, transformation and analysis. Based on big data and machine learning, it is robust and scalable in the truest sense.
Deploy Automated Predictive Maintenance Solution in just 4 weeks