Deployment · wireless

No conduit. No downtime. Still your data.

LoRaWAN VibraSens sensors report to a ChirpStack network server running on your own Beckhoff IPC — with real raw-waveform capture and edge AI, just duty-cycled. One host runs the wireless stack, never both.

LoRaWAN Sensor Network → Beckhoff Edge Gateway
Digital I/O in · SCADA, cloud & local HMI out
1 gateway · N endpoints
TANK LEVEL
45 m · line of sight
1
PRESSURE
140 m · 1 wall
VIBRATION
60 m · line of sight
2
TEMP — BASEMENT
310 m · 2 walls
3
FLOW — REMOTE BLDG
820 m · 3 walls
DOOR CONTACT
35 m · line of sight
BECKHOFF IPC
LoRaWAN gateway · 1 unit
SCADA
Plant-floor control system
CUSTOM CLOUD
Historian · analytics · alerts
LOCAL HMI
Runs right on the IPC
LoRaWAN uplink (sensor → gateway)
Wall crossed — signal attenuated, not blocked
Uplink to SCADA / cloud / HMI

A host runs the wired stack or the wireless stack — one logic set per IPC. Mixed plants run one host of each; both publish into the same HMI and the same northbound protocols.

What dropping the cable buys you

Retrofit coverage across assets that were never worth trenching for — with the same edge intelligence.

No cabling

Mount the sensor, pair it with the gateway, done — retrofit without shutting the line.

LoRaWAN

Long-range ChirpStack network server running on your own edge host.

Raw waveform

VibraSens wireless sensors still capture raw data — duty-cycled, fewer points per capture.

Lowest cost/point

No acquisition card per channel, so more assets fit the same budget.

The wireless signal chain

Sensor to plant system, with the network server inside your own plant.

01

VibraSens sensors

Battery-powered wireless accelerometers, magnet or stud mounted on the asset.

02

LoRaWAN gateway

Long-range radio link across the plant — no home-run cabling, no conduit work.

03

ChirpStack on the IPC

The network server runs on your edge host, so payloads never transit a vendor cloud.

04

Beckhoff IPC

Same Linux stack: alarms, DSP, AI scoring, storage and egress. Physical I/O optional.

Let the AI find it. Then prove it with the data.

The autoencoder runs on every reporting interval; when it flags an asset, pull the logged captures and diagnose with the full post-processing suite.

Edge HMI showing a Machine Stress Index breach with warning and danger counters
The AI raises the flag first — the HMI marks the event and pins the surrounding captures.

Long-horizon logging on the node — compression-first storage keeps months of history, so the evidence is still there when the AI points at it.

01

Configure the AI

Point it at the machine. The autoencoder learns that asset's own normal — no expert spectra setup.

02

The AI flags it

Machine Stress Index climbs out of band. Watch → Warning → Danger, locally, in under a second.

03

Then you investigate

Open the captures around the event and run the post-processing that answers why.

Post-processing toolkit — on demand, on the recorded data

  • FFT spectrum

    harmonics, BPFO / BPFI lines

  • STFT waterfall

    how the spectrum evolved

  • Power spectral density

    broadband energy

  • Demodulation

    envelope, early bearing defects

  • Cepstrum

    sideband families, gear mesh

  • Spectral kurtosis

    where the impulsiveness lives

  • Time domain

    the raw waveform itself

Six capabilities on a wireless host

Identical services to a wired node — the difference is data density, not features.

Core

Metrics & alarms

RMS, Peak and Kurtosis per reporting interval, checked against ISO 10816-3 bands at the edge.

Add-on

High-speed DSP

FFT, STFT, power density, envelope demodulation and spectral kurtosis on duty-cycled raw captures — fewer points than wired, same tools.

Add-on

Edge AI

The same autoencoder Machine Stress Index (0–100) with Watch / Warning / Danger stages, trained on the IPC.

Core

Storage & egress

Local time-series database, outage buffering, and northbound OPC UA, MQTT, Modbus TCP or HTTPS.

Core

HMI & operations

Same HTTPS web HMI, RBAC, edge health, live logs and offline update with rollback.

Optional

Fleet dashboards

Optional Azure aggregation — $24 per sensor per year, and entirely optional.

Honest limits

Wireless is not a lesser product — it is a different data budget.

  • Raw waveform

    Yes — duty-cycled captures on demand or on schedule

  • Deep DSP

    Yes — fewer points per capture than a wired channel

  • Continuous streaming

    No — reporting intervals, not a permanent stream

  • Physical I/O reaction

    Optional, slower than the sub-second wired path

  • Acquisition hardware

    Gateway only — no per-channel DAQ card

Wireless capacity — CX9240 to C6030

A wireless sensor costs about half the compute of a wired channel, so the same IPC covers twice the assets.

Sensor capacity per IPC — each add-on costs 20% of it
  • CX92402948 wireless · 1424 wired
  • C60155796 wireless · 2948 wired
  • C602586144 wireless · 4372 wired
  • C6030114192 wireless · 5796 wired

with DSP + AI metrics only

Wireless sensor capacity per Beckhoff IPC
IPCMetrics onlyDSP + AIRole
CX92404829Compact DIN-rail embedded PC
C60159657Ultra-compact industrial PC
C602514486Modular industrial PC
C6030192114High-performance industrial PC
Need continuous, full-rate capture on a critical asset? See the wired EtherCAT deployment.