HZ-WL-15A Natural Gas Well Gas Leak Acoustic Fingerprint Intelligent Monitoring Device is an edge‑computing acoustic monitor designed by HERTZINNO for wellheads and high‑pressure natural gas pipelines. Its core technology path is acoustic fingerprint recognition + edge computing. Equipped with an embedded deep learning algorithm chip, it performs AI inference directly on the device without relying on cloud connectivity.

Analysis Mode

Gas Leak Analysis

Frequency Range

20 Hz ~ 80 kHz

Sensor Type

MEMS Acoustic Sensor Array

Distance

20m

Protocols

HTTP, Modbus TCP

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Description
Specifications
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HZ-WL-15A Natural Gas Well Gas Leak Acoustic Fingerprint Intelligent Monitoring Device is an edge‑computing acoustic monitor designed by HERTZINNO for wellheads and high‑pressure natural gas pipelines. Its core technology path is acoustic fingerprint recognition + edge computing. Equipped with an embedded deep learning algorithm chip, it performs AI inference directly on the device without relying on cloud connectivity.

The device integrates a 9‑channel MEMS acoustic sensor array with a frequency response range of 20Hz – 80kHz, capable of capturing the turbulent noise and pipe wall stress waves generated by high‑pressure gas jets. It automatically filters out environmental interference such as wind, rain, and vehicle sounds, accurately extracting the unique acoustic fingerprint of gas leaks.

The main unit features an aluminum alloy enclosure with IP51 protection and Ex ib IIC T6 Gb intrinsically safe explosion‑proof certification. Operating temperature range is -30°C to +60°C, suitable for harsh outdoor environments. It supports 4G (full network compatibility) and Ethernet communication, with onboard 32GB storage (expandable up to 2TB). Standard industrial protocols (HTTP, Modbus TCP) enable seamless integration into existing monitoring platforms or SCADA systems.

Typical applications:

Real‑time gas leak warning at natural gas wellheads
Unattended monitoring of flanges and valves on high‑pressure pipelines
24/7 intelligent inspection of remote well sites

HZ-WL-15A upgrades leak detection from “periodic manual patrol” to proactive intelligent listening, significantly reducing false alarm rates and improving safety and operational reliability at oil & gas facilities.

Model	HZ-WL-15A
Industrial Specifications
Power Supply	DC 12V (Support DC 9V~15V, φ5.5mm barrel connector) PoE: 802.3at, Class4
Network Interface	1 x RJ45 10/100/1000 Mbps Adaptive Ethernet port
4G Communication	Supports full network (China Mobile, Unicom, Telecom)
Power Consumption	< 4W
Protection	Overvoltage protection / Overcurrent protection
Protection	IP51
Explosion-proof Rating	Ex ib IIC T6 Gb
Operating Temperature	-30°C ~ 60°C (Humidity <90% non-condensing)
Sensor Specifications
Sensor Type	MEMS Acoustic Sensor Array
Number of Sensors	9 MEMS
SNR	65 dB
Frequency Range	20 Hz ~ 80 kHz
Sensitivity	-36 dBV/Pa
Power Consumption	< 0.5W
Protection	IP65
Weight	100g
Sensor Dimensions	74 × 73 × 22.5 mm (mounting bracket excluded)

Physical Specifications
Sensor Channels	2
Interface Type	RJ45 / Analog signal(Sensor)
Sensor Interface	Aviation connector
Indicator Lights	Power / Signal / Fault
Internal Storage	32 GB
Storage Expansion	Micro SD card (up to 2 TB)
Enclosure Material	Aluminum alloy
Mounting Method	Bracket / Rail mounting
Main Unit Dimensions	178 × 110 × 40 mm
Main Unit Weight	0.75kg
Functional Features
Sampling Rate	48 kHz
Sampling Mode	Simultaneous sampling
Hardware Reset	Supported
RTC	Supported
Chassis Grounding	Supported
Network Protocols	HTTP, TCP, WebSocket, NTP, LTE
Configuration	Built-in web interface
Firmware Upgrade	Supported
Algorithm Upgrade	Supported
User Management	Single user, password change supported
Typical Applications	Gas well leak acoustic monitoring

Gas Well Site Videos

Long-Distance Gas Leak Simulation

Leak Detection in Gas Gathering Trees

Time-frequency spectrum under non-leakage conditions

Time-frequency spectrum in the event of a gas leak

Core Technology & Working Principle

The system operates on the principle of jet turbulence noise generation. When pressurized natural gas escapes through a crack or pinhole leak, it generates a distinct acoustic signature across the 20Hz–80kHz spectrum.

1. High-Fidelity Acquisition

A9-element MEMS array acoustic sensorcaptures sound signals 24/7 at the wellhead area, delivering reliable performance even in extreme outdoor temperatures ranging from -30°C to +60°C.

2. AI Noise Filtering & Feature Extraction

The built-inedge computing chipruns proprietary deep learning algorithms trained on a library ofover 5 million industrial acoustic signatures . The AI automatically suppresses environmental interference (wind, rain, vehicle traffic) and isolates the specific "acoustic fingerprint" of a high-pressure gas jet.

3. On-Device Inference & Real-Time Alerts

All analysis occurslocally at the edge , eliminating cloud latency. Upon confirming a leak signature, the device instantly transmits an alarm via 4G or Ethernet, enabling immediate response.

Superior False Alarm Rejection:Unlike conventional point detectors, the acoustic fingerprint algorithm accurately distinguishes real gas leaks from environmental noise, reducing false alarms byover 90%.