Technology

From waveforms to engineering context.

Signal processing, machine learning, and asset baselines, designed around the reality of industrial sound.

The analytical approach

Understand the signal before interpreting the change.

A useful acoustic model needs more than a recording. Signal quality, operating state, and representative evaluation shape what the result can tell you.

Capture and assess
Evaluate suitable acoustic sources. Check noise, clipping, silence, missing samples, and installation consistency.
Represent the sound
Apply suitable filtering, segmentation, and normalization. Explore time and frequency features, spectrograms, and learned audio representations.
Model the reference
Compare relevant machine states. Account for changing loads, speeds, recording conditions, and maintenance events.
Detect and review
Identify deviations and inspect the supporting evidence. Evaluate event classification only where representative labels support it.
Learn from outcomes
Record qualified review, false alerts, drift, and operating changes. Use those findings to assess model quality.

Deployment design

Fit the analysis to the environment.

At the edge

Assess local processing for bandwidth, connectivity, latency, and data handling requirements.

In a shared workspace

Connect events, features, asset context, and engineering review through an agreed application design.

With the engineer

Keep observations, uncertainty, and supporting evidence visible. Qualified people make consequential decisions.

This describes EchoStrata’s technical approach. Specific sensors, models, latency, deployment architecture, and classification coverage are established through a scoped evaluation.

Start with a conversation

Your machines have a story.
Let’s listen.

Bring an asset, a process, or a question.
We’ll explore what acoustic intelligence can add.

Book a demo

ONE USE CASE. A CLEAR FIRST STEP.

From waveforms to engineering context.

Understand the signal before interpreting the change.

Capture and assess

Represent the sound

Model the reference

Detect and review

Learn from outcomes

Fit the analysis to the environment.

At the edge

In a shared workspace

With the engineer

Your machines have a story.Let’s listen.

From waveforms to engineering context.

Understand the signal before interpreting the change.

Capture and assess

Represent the sound

Model the reference

Detect and review

Learn from outcomes

Fit the analysis to the environment.

At the edge

In a shared workspace

With the engineer

Your machines have a story.Let’s listen.

Your machines have a story.
Let’s listen.

Your machines have a story.
Let’s listen.