Packages, Parts and Tools

Internal structure of the elevator smart maintenance system; image courtesy of N2 Infotech
Internal structure of the elevator smart maintenance system; image courtesy of N2 Infotech

Offerings for North America and beyond

Incremental Encoder

St. Catherines, Ontario, Canada-based Global Encoder Systems introduces the new RH695, a redundant/dual incremental hollow shaft encoder engineered for maximum reliability, performance and safety for applications including elevators and lift systems where uptime and precision are critical. With robust construction, an IP65 protection class and operating temperatures from -20˚C to 100˚C, the RH965 meets numerous challenges. It is also ideal for applications in industries such as cranes and hoists, wind turbines, machine tools, robotics, automated production lines and more. Key features include:

  • Size of 96.5 mm (3.8 in.)
  • Shaft mounting for easy integration into existing systems
  • Shaft bore diameter of 12.7- to 25.4 mm (1/2 in. and 1 in.)
  • Electrically isolated redundant reading system
  • Resolution of 1 to 2,500 PPR (pulses per revolution)
  • Voltage range of 5 volts direct current (VDC), 4.75-30 VDC, 8-30 VDC input-5 VDC output

globalencoder.com

RH695

Torque Sensor

Saelig Co., Inc., headquartered in Fairport, NY, introduces Sensor Technology SGR523, a digital rotary torque sensor that suits a wide range of industrial purposes including measuring torque in elevator motors. Featuring a built-in incremental angle encoder, SGR523’s design simplifies system architecture by combining torque and angle measurement into a single unit, reducing component count and enhancing system reliability. This innovative addition to the TorqSense SGR series adds a new capability for precision in torque and angular position monitoring across various industrial applications. The SGR523 employs non-contact strain gauge technology, eliminating the need for traditional slip rings and enhancing reliability. Its high-resolution angle encoder delivers up to 10,000 pulses per revolution with a remarkable resolution of 0.0009 deg, making it ideal for applications requiring meticulous torque-angle analysis such as mechanical testing, automated assembly and process control. Key features include:

  • Torque measurement ranges from 175 mNm to 20 Nm
  • Accuracy of ± 0.1%
  • High mechanical overload capacity of 400%
  • Overrange reading capability of 250%
  • High digital sample rate of 4,000 samples per second
  • Digital outputs: RS232 and USB (standard); CANbus and Ethernet (optional)
  • Bi-directional angle and rotation count
  • Speed measurement up to 9,000 rpm
  • Compatible with TorqView Advanced Torque Monitoring Software
  • Lifetime Warranty

saelig.com

Sensor Technology SGR523

AI-Based Predictive-Maintenance Solution

South Korea’s N2 Infotech has developed and commercialized a smart maintenance system that collects real-time elevator operation data and predicts component replacement cycles using AI technology. Unlike traditional maintenance practices that rely on human experience, N2 Infotech’s solution predicts component wear based on actual usage data, identifying optimal replacement timing. This maximizes maintenance efficiency, reduces unnecessary replacements, lowers costs and enhances public safety and operational reliability. N2 Infotech has chosen public institutions as its primary market target with plans to enter the private and overseas markets later. Public elevators are widely used, have pre-allocated budgets, require periodic maintenance by law and demand safety and efficiency.

The company plans to initially target Europe and North America as Europe has a high ratio of elevators more than 20 years old and North America is known for strict elevator safety standards and smart building adoption. The system comprises real-time elevator operation data collected via sensors, AI-powered analysis algorithms and user-friendly web and mobile platforms.

Smart maintenance system

This solution shifts away from fixed maintenance intervals (monthly or annually) to “usage-based maintenance” determined by actual operation. AI enables accurate wear prediction, allowing preventive maintenance before failures occur. It also detects potential malfunctions early based on real-time data, eliminating maintenance gaps. This solution is expected to go beyond efficient maintenance to improve the quality of public services and serve as a core technology for smart city and public infrastructure development.
n2infotech.com

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