EM-W110® Motor Condition Monitoring System

Electric motors are the primary driving force for industrial equipment, and their normal operation directly impacts the reliability and availability of production equipment and systems, as well as the energy efficiency of factories. Motor condition monitoring and fault diagnosis allow for early detection and comprehensive analysis of electrical and mechanical issues in equipment systems. By implementing effective predictive maintenance strategies, it is possible to avoid production losses and high maintenance costs caused by unplanned downtime. This is one of the key technologies for enterprise digital transformation and efficient operations.

Based on the application and data accumulation of the previous generation of products, combined with the development of the Internet of Things, Zunxiang has launched a new generation of EM-W110® motor monitoring and diagnostic system by adopting optimized and innovative algorithms. The EM-W110 motor condition monitoring module collects three-phase current and voltage signals, and can also synchronously collect vibration, speed, and analog signals to achieve comprehensive and integrated monitoring. Based on optimized electrical signature analysis (ESA), the signal processing and fault extraction algorithms are more abundant and reliable, and it features intuitive condition assessment display. The optimized ESA covers the power supply, motor, driven machinery, and process of the equipment system, providing comprehensive advantages and applicable to asynchronous motors, variable frequency drive motors, DC motors, synchronous motors, generators, and other equipment.

The EM-W110 motor condition monitoring module monitors one motor per unit and can be installed in the MCC. It can be networked wirelessly via Wi-Fi through an RJ45 network interface, or utilize Cat.1 communication to achieve IoT and cloud intelligent monitoring. Monitoring data and collected waveforms are regularly uploaded to the EM-W110® motor condition monitoring database and software platform for fault warning, trend analysis, condition evaluation reports, expert diagnosis, alarm notifications, etc. Additionally, the EM-W110 can be connected to an LCD display via an RS232 interface for local display of monitoring parameters and status information, or transmit parameters and status information to other system interfaces such as PLCs via an RS485 interface for display.

Key features of EM-W110® motor diagnosis:

·Optimized Electrical Signature Analysis (ESA) technology

·Connect three-phase current and voltage to MCC without additional sensors

The diagnosis covers power supplies, electric motors, driven equipment, and processes

·Integrated monitoring of electrical, vibration, and other parameters

· Intuitive diagnostic conclusions, comprehensive state evaluation charts

·Rotor electrical health status

·Rotor and shafting mechanical status

·Static and dynamic eccentricity states of air gap

·Winding impedance, evaluation of inter-turn short circuit

·Evaluation of winding looseness

·Electrical equilibrium state

Power output, power factor, motor efficiency

·Power harmonic analysis

·Driven machinery and dynamic load analysis, auxiliary diagnostic model

·Bearing failure analysis, rolling bearing database

"Suitable for AC asynchronous, variable frequency drive motors, synchronous motors, generators, and DC motors."

·Flexible architecture: local or cloud server deployment, remote diagnostic support. Integration of offline and online monitoring, information system integration support.

EMonitor Pro-V2.0 Motor Condition Monitoring System Software

EMonitor Pro-V2.0 is a platform software for electrical engineers. The software converts monitoring data into equipment status information, evaluates the performance and operating status of electric motors, identifies potential faults, and determines the severity of faults, thereby guiding equipment operation, maintenance, and repair actions. The software features optimized electrical characteristic analysis technology and empirical algorithms, enabling automatic diagnosis, providing status evaluation and fault diagnosis conclusions, and offering a rich set of electrical characteristic analysis charts and reports, facilitating in-depth analysis and verification of faults by professional engineers.

The EMonitor Pro-V2.0 software provides reports including comprehensive reports on motor condition assessment and automatic diagnosis, electric energy parameter measurement data sheets, and harmonic analysis data sheets, which can be converted to PDF or Word formats. As a monitoring and tracking tool, it provides trend charts (long-term and short-term trends) and alarm indicators for key electric energy parameters and diagnostic parameters. The diagnostic spectrum includes low-frequency waveforms and spectra of three-phase current and voltage, effective value demodulation waveforms and spectra, high-frequency waveforms and spectra of three-phase current and voltage, three-phase comparison, and waterfall display. You can inspect the automatically identified characteristic frequency annotations on the spectra, utilize cursors for difference frequency, harmonic frequency, and sideband frequency, or perform detailed display operations to facilitate the analysis and verification of fault characteristics.

The EMonitor Pro-V2.0 software supports the EM-W110 condition monitoring module, EM-W100 online data acquisition station, and other hardware components to form a motor condition monitoring and intelligent diagnosis network system. Through network communication, it enables hardware system configuration, monitoring settings, data acquisition and transmission, database storage, and firmware program updates for the hardware.

The EMonitor Pro-V2.0 motor monitoring software platform is a B/S structure, facilitating easy installation and maintenance. User permissions are divided into administrators, analysts, and viewers, allowing for extensive information browsing. Additionally, the software meets the needs of different information system integrations through standard data interfaces such as API and OPC.