Product Type:Dual Channel Vibration Monitor
Model Number:6622LS
Brand:Entek
Channel Capacity:Dual
Operating Temperature Range:-40°C to +85°C
Input Signal Range:2 mV/g to 100 mV/g
Output Signal:4-20 mA or 0-10 V
Accuracy:+/- 1% F.S.
Resolution:0.1% F.S.
Power Supply:12 VDC
Current Consumption:≤ 25 mA
Size:90 x 72 x 20 mm
Weight:0.2 kg
The Entek 6622LS is engineered with precision in mind, featuring high accuracy and wide operating range, making it suitable for a variety of industrial applications where vibration monitoring is critical. It utilizes state-of-the-art sensor technology to continuously analyze and report vibration levels in real-time, allowing for proactive maintenance scheduling and reducing unexpected downtime.
With its robust design and ability to operate in extreme temperatures ranging from -40°C to +85°C, the Entek 6622LS ensures reliable performance across diverse manufacturing environments. Its low power consumption of less than 5W makes it energy-efficient, even in continuous operation scenarios.
The device is equipped with an RS-485 interface, enabling seamless integration with existing industrial control systems, thus facilitating quick installation and setup without the need for extensive wiring or complex configurations. This feature not only saves time but also reduces the potential for errors during setup.
Crafted from high-quality materials, the Entek 6622LS is built to withstand harsh industrial conditions, ensuring longevity and minimizing the need for frequent replacements. The compact size (100mm x 75mm x 40mm) and lightweight design (0.5kg) make it easy to install and maintain, even in tight spaces.
Incorporating the Entek 6622LS into your industrial operations can significantly improve equipment health monitoring, leading to enhanced operational efficiency, reduced maintenance costs, and extended equipment lifespan. With its user-friendly interface and comprehensive data reporting capabilities, the Entek 6622LS empowers you to make informed decisions regarding maintenance strategies and predictive analytics.
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