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ETa

Early Failure Diagnostic System

An early failure diagnostic system based on NVH analysis, ETa features data acquisition, real-time monitoring, self-learnt thresholding and alarm protection, helping you to validate prototypes quicker with greater precision.

ETa

Durability and Reliability Testing

ETa specializes in durability testing and early failure detection. Though collecting vibration, noise, and speed signals of the test object, it self-learns to generate limit values.

Around-the-Clock Monitoring

Around-the-Clock Monitoring

A professional system dedicated to durability testing and early failure detection, ETa supports 24/7 continuous monitoring of the test object and detects failure throughout. The system analyzes the NVH performance of the test object in real-time, providing engineers with objective and reliable continuous sampling.

ETa work process

Multi-dimensional Indicator Monitoring

Multi-dimensional Indicator Monitoring

For each sensor, ETa supports time domain indicators such as root mean square, crest factor, and kurtosis; as well as angular domain indicators such as order spectrum and order cut. The multi-dimensional indicators makes comprehensive monitoring of the various components possible.

自学习模式

Self-learning Mode

The ETa system can generate corresponding alarm threshold values through self-learning based on operating conditions, and determine whether the test object triggers an alarm based on these threshold values.
Reliable Alarm System

Reliable Alarm System

The alarm system monitors the condition of the test object and evaluates a multitude of domains every 0.1 second for any signs of exceeded threshold. The global amplitude module of ETa effectively covers the gap when the alarm threshold values are not fully formed in the initial stages of the tests. The rigorous alarm logic not only ensures the veracity of the alarm, but at the same time, improves the efficiency of the bench.
历史数据趋势分析

Historical Data Trend Analysis

ETa has a powerful database reading capability, which allows for quick retrieval and utilization of historical data for trend analysis, accurately diagnoses the root causes of failures and their evolution.
Figure 1: Monitoring Indicators and Conditions

Figure 1: Monitoring Indicators and Conditions

Figure 2: Order Color Map in 3D

Figure 2: Order Color Map in 3D