Quantum Magnetometers for Infrastructure Inspection and Monitoring

TL;DR

This review compares optically pumped atomic magnetometers and nitrogen-vacancy diamond magnetometers for infrastructure inspection, emphasizing their integration into measurement chains and practical deployment considerations.

Contribution

It provides a comprehensive comparison of quantum magnetometer platforms within real measurement chains for infrastructure monitoring applications.

Findings

OPMs excel in low-frequency, phase-referenced induction measurements.

NV sensors are optimal for near-surface field mapping and differential current sensing.

Deployment success depends on bandwidth, dynamic range, background rejection, and calibration.

Abstract

Damage in infrastructure is often hidden until it becomes costly or dangerous. Common examples include corrosion under insulation, early fatigue damage in steel, corrosion of embedded reinforcement, and abnormal current flow in batteries and power equipment. Magnetic methods are attractive because they can sense through coatings, insulation, and concrete cover without couplants, but field performance is often limited by lift-off, low-frequency drift, background magnetic noise, and the weak low-frequency response of pickup coils. This review examines two room-temperature quantum receiver platforms: optically pumped atomic magnetometers (OPMs) and nitrogen-vacancy (NV) diamond magnetometers. Rather than treating them as stand-alone sensors, we compare them as parts of a full measurement chain that includes source physics, geometry, readout, calibration, and interpretation. The literature is organized into four magnetic signal classes: driven induction responses, leakage fields in magnetic flux leakage inspection, passive self-fields linked to stress or corrosion, and fields produced by operational currents. OPMs are strongest for low-frequency, phase-referenced induction measurements, while NV sensors are strongest for near-surface field mapping, vector or gradient measurements, and differential current sensing in compact solid-state heads. Across all applications, deployment depends less on best-case sensitivity than on usable bandwidth, dynamic range, background rejection, geometry control, calibration, and validation. The clearest path to field use is therefore robust instrument engineering tied to qualification methods that reflect real inspection conditions.