Systems and methods herein provide for sinusoidal signal distortion monitoring and visualization via a Circular Trajectory Approach (CTA). In one embodiment, a system includes a differentiator operable to differentiate an input signal from a sinusoidal signal at substantially a same fundamental frequency of the input signal. The input signal comprising a sinusoidal waveform having distortions. The system also includes a processor operable to calculate a distance index from the input signal to a derivative of the input signal to reveal distortions in the input signal, and a display operable to display the distortions in the input signal.

A measurement module uses harmonic compensation factors to minimize the effects of harmonic distortion in measurements of a source current by a current sensor of the module. The module samples at a first sampling rate, measurements of the source current to generate a first current measurement. The module samples at a second sampling rate higher than the first sampling rate, for an interval of time, measurements of the source current to generate a second current measurement. The module determines a harmonic compensation factor based, at least, on a difference between the first current measurement and the second current measurement. The module determines a reported current computed as a function of at least the first current measurement, the difference between the first current measurement and the second current measurement, and the harmonic compensation factor. The reported current represents a magnitude of the source current adjusted by the harmonic compensation factor.

A measuring assembly for detecting intermodulations which limits the source of the intermodulations includes a first measuring device including a signal generation device and a signal measuring device. The signal generation device is designed to generate test signals and to output the test signals at an output connection, and the signal measuring device is designed to measure signals that are applied at the output connection. The assembly further includes a second measuring device with an input connection and a signal measuring device. The signal measuring device of the second measuring device is designed to measure signals that are applied at the input connection. The assembly further includes a directional coupler coupled to the first measuring device and the second measuring device.

A measuring assembly for detecting intermodulations which limits the source of the intermodulations includes a first measuring device including a signal generation device and a signal measuring device. The signal generation device is designed to generate test signals and to output the test signals at an output connection, and the signal measuring device is designed to measure signals that are applied at the output connection. The assembly further includes a second measuring device with an input connection and a signal measuring device. The signal measuring device of the second measuring device is designed to measure signals that are applied at the input connection. The assembly further includes a directional coupler coupled to the first measuring device and the second measuring device.

An Empirical Mode Decomposition (EMD)-based noise estimation process is disclosed herein that allows for blind estimations of noise power for a given signal under test. The EMD-based noise estimation process is non-parametric and adaptive to a signal, which allows the EMD-based noise estimation process to operate without necessarily having a priori knowledge about the received signal. Existing approaches to spectrum sensing such as Energy Detector (ED) and Maximum Eigenvalue Detector (MED), for example, may be modified to utilize a EMD-based noise estimation process consistent with the present disclosure to shift the same from semi-blind category to fully-blind category.

An Empirical Mode Decomposition (EMD)-based noise estimation process is disclosed herein that allows for blind estimations of noise power for a given signal under test. The EMD-based noise estimation process is non-parametric and adaptive to a signal, which allows the EMD-based noise estimation process to operate without necessarily having a priori knowledge about the received signal. Existing approaches to spectrum sensing such as Energy Detector (ED) and Maximum Eigenvalue Detector (MED), for example, may be modified to utilize a EMD-based noise estimation process consistent with the present disclosure to shift the same from semi-blind category to fully-blind category.

A system for non-invasive sensing of radio-frequency current spectra. In one example, the system comprises a plasma processing chamber, a plasma generator, and a shunt connector having a resistor therein. In one example, the shunt connector is attached across an opening in a ground-return path between the chamber and the generator.

A system for identifying faults in a radio frequency device under test, the system including a passive intermodulation test module, configured to perform passive intermodulation testing of the device under test on at least one test port; and an in-line S-parameter test set, coupled to the passive intermodulation test module and intermediate the passive intermodulation test module and at least one test port, and configured to perform wideband S-parameter testing of the device under test on the at least one test port.

A system includes a signal generator, configured to pass a generated signal, which has two different generated frequencies, through a circuit including an intrabody electrode. The system further includes a processor, configured to identify, while the generated signal is passed through the circuit, a derived frequency, which is derived from the generated frequencies, on the circuit, and to generate, in response to identifying the derived frequency, an output indicating a flaw in the electrode. Other embodiments are also described.

A system (800) for determining frequency spacings to prevent intermodulation distortion signal interference is provided. The system (800) includes a sensor assembly (810) and a meter verification module (820) communicatively coupled to the sensor assembly (810). The meter verification module (820) is configured to determine a frequency of a first signal to be applied to a sensor assembly (810) of a vibratory meter and set a demodulation window about the frequency of the first signal. The meter verification module (800) is also configured to determine a frequency of the second signal to be applied to the sensor assembly such that a frequency of an intermodulation distortion signal generated by the first signal and the second signal is outside the demodulation window.