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US 12,737,587 B2Granted
Metal detection system
OwnerMatthew Millerinventor
Life of this patent
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Abstract
A system includes a metal detector configured to provide an input signal responsive to being proximate an object; and a processing device configured to: receive the input signal from the metal detector; determine a plurality of features from the input signal; provide the plurality of features as input to a trained machine learning model (MLM); receive output from the trained MLM; and responsive to detection, based on the output, that the object comprises metal, cause output of a notification.
Claims20
A system comprising:
- a pulsed induction (PI) metal detector configured to output a voltage signal responsive to being proximate to an object, wherein the PI metal detector comprises a power supply, a coil, and a waveform generating component;
- and
- a processing device configured to:
- receive the voltage signal outputted from the PI metal detector, wherein the voltage signal comprises a square wave including an on period and an off period;
- determine, based on the voltage signal and position information associated with the PI metal detector, a plurality of features;
- provide the plurality of features as input to a trained machine learning model (MLM);
- receive output from the trained MLM, wherein the output comprises a confidence value associated with a class of a metal, and wherein the confidence value comprises a percentage;
- determine whether the confidence value in the output satisfies a threshold criterion;
- and
- responsive to determining that the confidence value satisfies the threshold criterion, cause output of a notification indicating a detection of the class of the metal in the object,
- wherein determining the plurality of features further comprises:
- selecting data points in the voltage signal satisfying a criterion;
- identifying a first feature of the plurality of features by using a linear regression on the voltage signal;
- identifying a second feature of the plurality of features by comparing predefined data points associated with the voltage signal;
- identifying a third feature of the plurality of features by using a Fast Fourier transform (FFT) on the voltage signal;
- using a proximity to the object of the position information as a fourth feature of the plurality of features;
- using signal intensity information of the voltage signal as a fifth feature of the plurality of features;
- and
- using a heat map representing detection confidence of the voltage signal as a sixth feature of the plurality of features.
16 more elements
A method comprising:
- receiving a voltage signal outputted from a PI metal detector responsive to the PI metal detector being proximate to an object, wherein the PI metal detector comprises a power supply, a coil, and a waveform generating component, wherein the voltage signal comprises a square wave including an on period and an off period;
- determining, based on the voltage signal and position information associated with the PI metal detector, a plurality of features;
- providing the plurality of features as input to a trained machine learning model (MLM);
- receiving output from the trained MLM, wherein the output comprises a confidence value associated with a class of a metal, and wherein the confidence value comprises a percentage;
- determining whether the confidence value in the output satisfies a threshold criterion;
- and
- responsive to determining that the confidence value satisfies the threshold criterion, causing output of a notification indicating a detection of the class of the metal in the object,
- wherein determining the plurality of features further comprises:
- selecting data points in the voltage signal satisfying a criterion;
- identifying a first feature of the plurality of features by using a linear regression on the voltage signal;
- identifying a second feature of the plurality of features by comparing predefined data points associated with the voltage signal;
- identifying a third feature of the plurality of features by using a Fast Fourier transform (FFT) on the voltage signal;
- using a proximity to the object of the position information as a fourth feature of the plurality of features;
- using signal intensity information of the voltage signal as a fifth feature of the plurality of features;
- and
- using a heat map representing detection confidence of the voltage signal as a sixth feature of the plurality of features.
13 more elements
A non-transitory computer-readable medium storing instructions thereon, wherein the instructions, when executed by a processing device, cause the processing device to:
- receive a voltage signal outputted from a pulsed induction (PI) metal detector responsive to the PI metal detector being proximate to an object, wherein the PI metal detector comprises a power supply, a coil, and a waveform generating component, wherein the voltage signal comprises a square wave including an on period and an off period;
- determine, based on the voltage signal and position information associated with the PI metal detector, a plurality of features;
- provide the plurality of features as input to a trained machine learning model (MLM);
- receive output from the trained MLM, wherein the output comprises a confidence value associated with a class of a metal, and wherein the confidence value comprises a percentage;
- determine whether the confidence value in the output satisfies a threshold criterion;
- and
- responsive to determining that the confidence value satisfies the threshold criterion, cause output of a notification indicating a detection of the class of the metal in the object,
- wherein determining the plurality of features further comprises:
- selecting data points in the voltage signal satisfying a criterion;
- identifying a first feature of the plurality of features by using a linear regression on the voltage signal;
- identifying a second feature of the plurality of features by comparing predefined data points associated with the voltage signal;
- identifying a third feature of the plurality of features by using a Fast Fourier transform (FFT) on the voltage signal;
- using a proximity to the object of the position information as a fourth feature of the plurality of features;
- using signal intensity information of the voltage signal as a fifth feature of the plurality of features;
- and
- using a heat map representing detection confidence of the voltage signal as a sixth feature of the plurality of features.
13 more elements
Dependencies are inferred from the claim text.