A sensing system and a sensing signal measuring method thereof are provided. The sensing system includes a signal source, a connecting device, a frequency sweep circuit, and a controller. In the method, the signal source is activated to generate a specific signal. The controller controls the frequency sweep circuit to switch a frequency band of a frequency sweep signal to a first frequency band corresponding to each of a plurality of types of multi-point sensors. The controller receives a sensor signal of each multi-point sensor through the connecting device, where the sensor signal is a variation of a measurement signal output by each multi-point sensor in response to the specific signal and the frequency sweep signal. The controller executes an adaptive algorithm on the sensor signal to construct a correspondence between an eigenvalue of each multi-point sensor and a location of the first frequency band, and records the correspondence.

A sensing system and a sensing signal measuring method thereof are provided. The sensing system includes a signal source, a connecting device, a frequency sweep circuit, and a controller. In the method, the signal source is activated to generate a specific signal. The controller controls the frequency sweep circuit to switch a frequency band of a frequency sweep signal to a first frequency band corresponding to each of a plurality of types of multi-point sensors. The controller receives a sensor signal of each multi-point sensor through the connecting device, where the sensor signal is a variation of a measurement signal output by each multi-point sensor in response to the specific signal and the frequency sweep signal. The controller executes an adaptive algorithm on the sensor signal to construct a correspondence between an eigenvalue of each multi-point sensor and a location of the first frequency band, and records the correspondence.

A method for processing an initial signal includes a useful signal and added noise, which comprises a step of frequency selective analysis providing starting from initial signal a plurality of wideband analysis signals corresponding to one of the analysed frequencies, and comprising the following actions: zero or more complex frequency translations, one or more undersampling operations, computation of the instantaneous Amplitude, of the instantaneous Phase, and of the instantaneous Frequency of the wideband analysis signals. This information then allow to detect modulations of signals included in high levels of noise and to detect with a good probability the presence of a signal in a high level of noise.

A method for processing an initial signal includes a useful signal and added noise, which comprises a step of frequency selective analysis providing starting from initial signal a plurality of wideband analysis signals corresponding to one of the analysed frequencies, and comprising the following actions: zero or more complex frequency translations, one or more undersampling operations, computation of the instantaneous Amplitude, of the instantaneous Phase, and of the instantaneous Frequency of the wideband analysis signals. This information then allow to detect modulations of signals included in high levels of noise and to detect with a good probability the presence of a signal in a high level of noise.

A computer-implemented method and system for Condition Monitoring (CM) for rotating machines. The method and system include continuously receiving samples of the envelope of physical quantity data such as speed, vibration, or current, updating in real-time accumulator variables, computing in real-time spectral features based on the accumulator variables and supplemental variables, and determining a condition based on the real-time spectral features. The spectral features, exemplary as amplitudes at specific frequencies, are computed in real-time by a Goertzel Algorithm. The totality of the accumulator variables is sufficient to determine the condition of the rotating machine and the supplemental variables are temporarily needed for computing the spectral features. The one or more supplemental variables, such as memory addresses, are not based on the received samples of the input data.

A computer-implemented method and system for Condition Monitoring (CM) for rotating machines. The method and system include continuously receiving samples of the envelope of physical quantity data such as speed, vibration, or current, updating in real-time accumulator variables, computing in real-time spectral features based on the accumulator variables and supplemental variables, and determining a condition based on the real-time spectral features. The spectral features, exemplary as amplitudes at specific frequencies, are computed in real-time by a Goertzel Algorithm. The totality of the accumulator variables is sufficient to determine the condition of the rotating machine and the supplemental variables are temporarily needed for computing the spectral features. The one or more supplemental variables, such as memory addresses, are not based on the received samples of the input data.

The invention relates to a method (1) for monitoring a rotating machine (100) of an aircraft, wherein a measurement signal is acquired from the rotating machine. According to the invention, instantaneous frequencies (f.sub.K(t)) of sinusoidal components of the measurement signal are estimated, and, using a computing module (12), a plurality of successive iterations are carried out in each of which: complex envelopes of the components are updated (C1), parameters of a model of a noise of the signal are updated (C21) on the basis of the envelopes, whether the model has converged from the preceding iteration to the present iteration is tested (C4), with a view to: o if not, carrying out a new iteration, o if so, performing a computation (D) of the complex envelopes on the basis of the iterations that have been carried out.

A method for monitoring the status of an apparatus, wherein an analog signal is converted into a digital signal with an analog-digital converter operating within a measuring range, signal portions of the analog signal extending beyond the measuring range are cut in the digital signal, a spectral analysis is applied to the digital signal to determine which frequency potions the analog signal possesses in a frequency spectrum and conclude a malfunction of the apparatus when the analog signal exceeds the measuring range, where when the analog signal extending beyond the measuring range is in the digital signal, this event is detected and determined as a number, where a signal quality is provided which is used to assess whether known damage frequencies can still be identified from determined frequency portions of the frequency spectrum, although additional overcontrol portions in the frequency spectrum occur as a result of possibly cut signal portions.

A method for monitoring the status of an apparatus, wherein an analog signal is converted into a digital signal with an analog-digital converter operating within a measuring range, signal portions of the analog signal extending beyond the measuring range are cut in the digital signal, a spectral analysis is applied to the digital signal to determine which frequency potions the analog signal possesses in a frequency spectrum and conclude a malfunction of the apparatus when the analog signal exceeds the measuring range, where when the analog signal extending beyond the measuring range is in the digital signal, this event is detected and determined as a number, where a signal quality is provided which is used to assess whether known damage frequencies can still be identified from determined frequency portions of the frequency spectrum, although additional overcontrol portions in the frequency spectrum occur as a result of possibly cut signal portions.

A computer-implemented method of Condition Monitoring (CM) for rotating machines like motors, a corresponding computer program, computer-readable medium and data processing system for CM for rotating machines as well as a system including the data processing system for CM for rotating machines. M accumulator variables are updated in real-time based on L samples including a current sample sn and at least one preceding sample Sn−1 of input data. Based on the M accumulator variables N spectral features are computed in real-time. A condition of the rotating machine is determined based on the N spectral features.