Detailed explanation of Metal Detection (Electromagnetic Wave DSP) technology
Metal detection technology is based on the fusion of electromagnetic waves and digital signal processing (DSP) to achieve non-contact metal recognition. It detects metal objects through the principle of electromagnetic induction and improves sensitivity and anti-interference performance with the help of DSP algorithms. The following introduces the core principles, technology classification, application scenarios, and development trends:
I. Core Principles and Electromagnetic Induction Mechanism
The core of metal detection relies on electromagnetic scattering effects: when an alternating current is passed through a coil, a high-frequency electromagnetic field (typically at a frequency of 200kHz) is generated. After the metal object enters the magnetic field, the eddy current effect disturbs the original field distribution, causing changes in inductance or impedance. For example, in the LDC1000 inductive digital converter, real-time offset of coil impedance (24 bit resolution) and parasitic resistance can accurately locate the position and characteristics of metals. The DSP module analyzes signal phase difference through algorithms such as Fourier transform (FFT), distinguishes metal types (such as ferromagnetic vs. non ferromagnetic), and suppresses environmental noise.
II. Technology Classification and DSP Integration Evolution
Technical Type Working Principle DSP Enhancement Features
VLF uses a phase demodulator to measure the phase shift caused by eddy currents (such as C=C key recognition), and AI adaptive filtering algorithm optimizes metal classification, reducing false alarm rate by 40%
Pulse Induction (PI) emits high-voltage short pulses, captures the difference in attenuation time of reflected pulses (metal extended microsecond level signal), and deeply learns to reconstruct signal waveforms, supporting sub micron resolution
Magnetic memory detection is based on the magnetic field gradient anomaly (such as Hp (y) zero crossing feature) in the stress concentration area monitored by the geomagnetic field. Real time field intensity mapping is combined with edge computing to achieve 1mm level positioning accuracy
Key role of DSP:
Noise suppression: Kalman filter eliminates electromagnetic interference (such as industrial equipment radiation).
Dynamic calibration: MCU (such as MC9S12XS128) controls the scanning strategy, with coarse scanning followed by fine positioning.
III. System composition and typical configuration
Electromagnetic emission unit: A high-frequency oscillator (200kHz) generates a controllable electric field, and a voltage stabilization circuit ensures the stability of the field strength.
Sensing module: Inductive coil or Permalloy probe, with a sensitivity of 0.5 μ H for change detection.
DSP processing core: Integrated ADC and FFT hardware accelerator, real-time conversion of analog signals into digital features (such as 24 bit inductance values).
Output unit: Sound and light alarm system, driven by a power amplifier to drive the speaker.
Example system: LDC1000+MC9S12XS128 platform, supporting synchronous detection of multiple metals in a 500mm × 500mm area.
IV. Application scenarios and performance advantages
Security check field
Handheld detectors for subways/airports: identify knives, weapons, and penetrate non-metallic coverings such as clothing and backpacks.
Millimeter wave imaging assistance: Combining the 30-300GHz frequency band to compensate for pure electromagnetic blind spots and improve the detection rate of hidden objects in the human body.
Industry and Military
Mine detection: PI technology is suitable for soil and gravel environments, with a false alarm rate of less than 5%.
Equipment health monitoring: Magnetic memory technology diagnoses stress cracks in welded joints without the need for surface pre-treatment.
Advantage comparison:
Indicator: Traditional Electromagnetic Detection DSP Enhanced Type
Sensitivity is significantly affected by metal shielding, with sub micron resolution (such as LDC1000)
Anti interference is easily affected by environmental electromagnetic noise interference, adaptive frequency band switching+AI noise reduction
Cost efficiency
V. Future development direction
Multimodal fusion: Combining infrared or acoustic sensing to construct a 3D metal distribution map.
Edge Intelligence: Micro AI chips (such as Cortex-M series) enable real-time decision-making on the end side, reducing power consumption by 50%.
IoT integration: 5G network detection vehicle group, supporting large-scale area scanning (such as mining area security monitoring).
Electromagnetic wave DSP technology is driving the evolution of metal detection towards high precision, low power consumption, and intelligence, with significant potential in the fields of unmanned inspection and smart security.
