A test and measurement instrument includes an input for accepting an input signal from a Device Under Test (DUT), acquisition memory for storing a sampled waveform derived from the input signal, an output display, and one or more processors configured to accept a portion of the sampled waveform as a search portion, search the sampled waveform for portions similar to the search portion, and visually indicate, on the output display, portions of the sampled waveform that are similar to the search portion as matched portions. Methods of operation and description of storage media, the operation of which performs the above operations, are also described.

A battery type determination system includes an electric circuit connected to a battery, and a battery type determination device that determines a type of the battery on the basis of a characteristic value of the electric circuit. The electric circuit includes an AC power supply having a variable frequency, and a capacitor circuit. The battery type determination device includes a resonance state detection unit that detects at least one resonance state in response to an AC signal output from the AC power supply, a resonance frequency detection unit that detects a resonance frequency in the resonance state, a resonance characteristic detection unit that uses the resonance frequency as a resonance characteristic of the battery, and a determination unit that determines whether or not the battery is of the same type as a reference battery by comparing the resonance characteristic of the battery with a reference resonance characteristic of the reference battery serving as a reference for the battery.

Systems and methods may be used to measure a frequency of a power delivery system and/or of a supply signal transmitted to a load. A system may record an input waveform, determine a frequency of the input waveform at a present time based at least in part on the input waveform and a derivative of the input waveform, and control an operation of a power delivery system based at least in part on the determined frequency.

An environmental frequency sensing device, includes logic that performs signal strength (SS) level separation on a received band of frequencies to produce SS level separated frequencies. The logic performs frequency grouping on the SS level separated frequencies for each signal strength level to produce magnitude information for each grouping. The logic generates peak data by detecting peaks of the produced magnitude information. The logic generates an edge event indicating a signal edge based on arrival or departure of a given peak and compares, on a frequency basis, generated edges to stored fingerprint data of a signal of interest. Based on the comparison, the logic provides detected signal data indicating current use of a range of frequencies in an environment.

A wireless power transfer system and a control method thereof. The wireless power transfer system includes: a transmitter coil configured to be magnetically coupled to a receiver coil; a power conversion device coupled to the transmitter coil; and a controller including a one-half cycle detection block, wherein the one-half cycle detection block is configured to establish a current sensing time instant, and wherein at the current sensing time instant, a current flowing through the transmitter coil is detected and compared to a predetermined threshold to perform foreign object detection to determine whether a foreign object is coupled to the wireless power transfer system.

The present invention proposes an arc detector having a multi-band frequency detection function, which divides an arc frequency band using multiple band-pass filters and detects whether or not an arc occurs in each of the divided frequency bands, thereby eliminating switching noise or power supply noise that mainly occurs in a certain frequency band, and consequently increasing the accuracy of arc detection. In addition, the arc detector of the present invention may minimize the use of expensive analog-to-digital converters and increase the accuracy of arc detection through overlapping area detection.

A sensor processing system includes a plurality of reduction circuits. The plurality of reduction circuits correspond to a plurality of sensors on a one-to-one basis. Each of the plurality of reduction circuits is electrically connected to an output terminal of a corresponding one of the plurality of sensors to reduce a low-frequency component of a sensor output of the corresponding one of the plurality of sensors.

A method for measuring frequency domain characteristics of a PDN having an output terminal connected to a power supply end of a functional circuit. The method includes: a to-be-measured output interface of the functional circuit is acquired; the to-be-measured output interface is controlled to output a first level signal having a first preset rule; remaining at least one output interface of the functional circuit, other than the to-be-measured output interface, is controlled to output a second level signal having a second preset rule according to a first frequency; changing voltage values corresponding to the first frequency and output by the to-be-measured output interface are acquired; and a characteristic impedance of the PDN at the first frequency is determined based on the changing voltage values corresponding to the first frequency.

A MEMS device may output a signal during operation that may include an in-phase component and a quadrature component. An external signal having a phase that corresponds to the quadrature component may be applied to the MEMS device, such that the MEMS device outputs a signal having a modified in-phase component and a modified quadrature component. A phase error for the MEMS device may be determined based on the modified in-phase component and the modified quadrature component.

Analysis of smart meter and/or similar data based on frequency content is disclosed. In various embodiments, for each of a plurality of resource consumption nodes a time series data including for each of a series of observation times a corresponding resource consumption data associated with that observation time is received. At least a portion of the time series data, for each of at least a subset of the plurality of resource consumption nodes, is transformed into a frequency domain. A feature set based at least in part on the resource consumption data as transformed into the frequency domain is used to detect that resource consumption data associated with a particular resource consumption node is anomalous.