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BENTLY NEVADA 22811-01-06-10-02 Proximity Sensor

BENTLY NEVADA 22811-01-06-10-02 Proximity Sensor


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The Bently Nevada 22811-01-06-10-02 is typically a model number for a specific sensor or accessory in Bently Nevada's vibration monitoring and protection equipment lineup.

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  • Email

    plcsale@mooreplc.com
  • Whatsapp

    +86 18030235313
  • Specifications
  • Brand Name:

    BENTLY NEVADA

    Package:

    Original Package

    Model Number:

    22811-01-06-10-02

    Lead time:

    In Stock

    Alternate Part Number

    22811-01-06-10-02

    Shipping term:

    UPS DHL TNT EMS Fedex

    Condition:

    100% Original

    Payment:

    T/T 

    Quality:

    Brand New

    Service:

    One-Stop Service

    Dimensions

    1.8x1.8x116cm

    Weight

    0.06kg

    Description

    Proximity Sensor

    Warranty:

    12 Months

     

  • Product Details


  • What does the model number 22811-01-06-10-02 signify?

    The model number indicates the specific configuration of the device, including its range, sensitivity, and physical characteristics. Each segment of the model number typically represents different attributes such as sensor type, output options, and mechanical configuration.


    What types of equipment can this model be used with?

    The 22811-01-06-10-02 is designed for use with rotating equipment, including compressors, turbines, pumps, motors, and generators. It is often used in industries like oil and gas, power generation, and manufacturing.


    Is the 22811-01-06-10-02 compatible with other Bently Nevada systems?

    Yes, this model is generally compatible with other Bently Nevada systems, such as the 3500 Series Monitoring System, and can be integrated into existing Bently Nevada machinery protection and monitoring setups.


    What environmental conditions can this model operate under?

    The Bently Nevada 22811-01-06-10-02 is built to operate under harsh industrial conditions, including high temperatures, humidity, dust, and exposure to various industrial chemicals. Specific operating temperature ranges and environmental conditions will be detailed in the product datasheet.


    What are the output options for this model?
    Depending on the specific configuration, the 22811-01-06-10-02 may provide various output options such as 4-20 mA, voltage, or frequency outputs, which correspond to the monitored parameter (e.g., vibration, displacement).



  • Service and Warranty
  • NOTE:

    1. The products quoted are brand new and original with a one-year warranty

    2. Prices are ex works, for shipping calculations, Please send to my Email 

    3. Cooperation with the express delivery of DHL / Fedex / UPS / Aramex, etc,Delivery time is approximately '' 5 days ''  from our warehouse to the destination country

    4. Quotation validity: 30 days, if you need to extend, please reconfirm the price after 30 days.

    5. Payment Term: 100% advance payment by bank transfer.

    6. For the products '' in stock '' in the offer, our company can support video inspection


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    NOTE: Moore Automation sells new and surplus products and develops channels to purchase such products. This site is not approved or endorsed by any of the listed manufacturers or trademarks.Moore Automation is not an authorized distributor, dealer or representative of the products displayed on this site.All product names, trademarks, brands and logos used on this site are the property of their respective owners.The description, illustration or sale of products under these names, trademarks, brands and logos is for identification purposes only and is not intended to indicate any affiliation with or authorization by any rights holder. 

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News & Blogs

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    2025

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    Introduction In the rapidly developing field of industrial automation, it is particularly important to achieve high-precision signal acquisition and stable communication between field devices and control systems. As an important channel connecting field devices and control systems, digital input modules play a core role in monitoring switch states, sensor binary output signals, etc. The ADV161-P00 S2 digital input module launched by Yokogawa is a high-performance product designed to meet the demanding needs of modern process control systems. It not only improves the accuracy of input signal processing, but also ensures efficient coordination with distributed control systems.   Combination of rugged design and multifunctional performance ADV161-P00 S2 continues Yokogawa's consistent high standards and durability in industrial automation equipment. This module belongs to the widely acclaimed CENTUM VP control system series and has the characteristics of strong stability, long life cycle and reliable structure. The module supports 16 digital inputs, each of which can detect the on-off state at high speed and high precision, suitable for harsh industrial field environments. Its hardware design follows strict industrial standards and has good anti-interference capabilities. Isolation protection is provided between channels and between channels and the system bus to effectively prevent equipment failures caused by surges or electrical interference. The module is compact and well-planned, which not only saves control cabinet space, but also facilitates quick installation and maintenance. These advantages make it widely used in multiple industries such as petrochemical, power, manufacturing, and water treatment.   Seamless integration with distributed control systems One of the outstanding advantages of ADV161-P00 S2 is its high compatibility with advanced control systems such as Yokogawa's CENTUM VP. The module can be easily connected to the system's I/O network to achieve real-time acquisition and monitoring of field digital signals. All channels are continuously scanned and status data is transmitted to the central controller with extremely low latency, so as to quickly respond to process changes. The module has built-in diagnostic functions, which helps to detect line breaks, signal anomalies, or channel failures in a timely manner, facilitating preventive maintenance and troubleshooting. At the same time, it supports hot swapping, which means that the module can be replaced without downtime, which is particularly important for critical application scenarios where interruptions cannot be accepted.   High reliability and safe operation guarantee In high-risk and high-demand industrial occasions, system reliability is crucial. ADV161-P00 S2 undergoes rigorous factory testing and quality verification to ensure long-term operational stability. The module can be configured with a redundant architecture to enhance the system's fault toleranc...
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    Due to ABB's machinery and personnel plan, food and beverage industry reform
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  • ABB drives heavy industry performance innovation with digital twins 19/06

    2025

    ABB drives heavy industry performance innovation with digital twins
    Introduction At present, the wave of Industry 4.0 is sweeping the world, and digital innovation is profoundly changing the operating mechanism of heavy asset industries, especially mining, oil and gas, metallurgy and energy. At the forefront of this transformation is the digital twin technology deployed by ABB, an intelligent means of building a virtual mirror of a physical system. By integrating real-time data streams with advanced simulation models, this technology helps companies achieve accurate perception, scientific prediction and efficient management of the entire life cycle of the system. In complex industrial environments, digital twins are becoming a key force to reduce the risk of interruptions, improve operational efficiency and ensure safety.   Intelligent construction of virtual mapping: the core foundation of ABB's digital twins Deeply embedded in ABB's digital twin system is the close integration of operational data and physical modeling technology. These virtual models not only reproduce the geometry of the actual equipment, but also simulate its dynamic performance and behavior mechanism. The sensor network, intelligent control platform and AI algorithm deployed by ABB continuously collect operating data from the field and synchronously feed it back to the twin model. As a result, the digital mapping can always remain consistent with the real state. In the process of simulating different operating scenarios, operators can verify the operating effect in advance, avoid potential failures, and optimize process parameters without interrupting the production rhythm. For example, in the metal smelting industry, ABB's virtual model can reproduce the operating status of the furnace under various heat load conditions, helping engineers to find energy consumption blind spots and achieve energy saving and consumption reduction; in mining scenarios, its platform can analyze mechanical wear trends, terrain stress and automatic transportation paths, thereby extending equipment life and improving operational efficiency.   Full-cycle collaborative optimization and intelligent predictive maintenance Not only limited to visual presentation, ABB's digital twin also covers the entire life trajectory of assets: from engineering design, system debugging to operation and maintenance. Continuous data analysis capabilities enable the system to implement forward-looking maintenance strategies, thereby effectively avoiding unexpected downtime events. The machine learning mechanism hidden in the ABB Ability™ platform has the ability to identify changes in operating trends and micro-anomalies; thereby, equipment maintenance can be dynamically adjusted, greatly reducing maintenance costs and total cost of ownership (TCO). More importantly, before the actual deployment of the control strategy, operators can use the twin model to simulate parameters and select the best solution. This not only ensures a smoother system startup, but also effectively en...
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  • Relying on artificial intelligence: How ABB is revolutionizing industrial process automation 18/06

    2025

    Relying on artificial intelligence: How ABB is revolutionizing industrial process automation
    Introduction As industrial digitalization continues to deepen, artificial intelligence (AI) is gradually becoming the core driving force for automation innovation. ABB, as a pioneer in the global electrical and automation field, is deeply integrating AI technology into its diversified products and solutions from a forward-looking perspective, in order to improve operational intelligence, optimize process efficiency and prevent faults. With the help of advanced machine learning, real-time data analysis and intelligent prediction technology, ABB is leading the upgrading and reconstruction of automation models in multiple industries such as manufacturing and energy.   Using AI to achieve predictive maintenance and equipment efficiency improvement Among many AI application scenarios, ABB's most striking achievements are reflected in predictive maintenance. By deploying self-learning algorithms in the control platform, the equipment can self-monitor the operating status, identify operating anomalies and predict potential faults in advance. This forward-looking maintenance method not only reduces the probability of unplanned downtime, but also significantly improves equipment utilization. For example, ABB's Ability™ asset performance management platform uses AI to perform pattern recognition and trend analysis on sensor data of motors, pumps and compressors, thereby triggering early warning or automated response mechanisms. This not only extends the service life of equipment, reduces maintenance costs, and effectively curbs safety risks. In addition, AI models for optimizing production scheduling and energy distribution are also widely deployed. It is this set of intelligent scheduling strategies that minimizes resource use and maximizes operational efficiency. In high-risk industries such as petrochemicals, mining, and fine chemicals, this AI optimization method is particularly economic and operational.   Process control optimization leverages real-time intelligent analysis It is the embedding of artificial intelligence technology that makes process control smarter and more adaptive. ABB has achieved precise control and dynamic response mechanisms based on real-time data by integrating AI algorithms into its distributed control system (DCS). If changes occur on key parameters such as temperature or pressure, the system can autonomously complete parameter correction and optimal adjustment based on adaptive modeling and reinforcement learning algorithms without human intervention. For example, in chemical processes, this capability ensures the continued stability of product quality and production capacity. AI not only extracts value from data collected by sensors, but also integrates multiple data sources such as historical records and enterprise resource information to output operational suggestions and even automatically optimize closed-loop control strategies. Such functions not only improve production yields, but also help companies meet t...
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