A dynamic response at a designated position is derived based on a deflection amount normalized by a vibration component of the dynamic response, an amplitude ratio, which is a ratio of a first deflection amount that is the normalized deflection amount indicating a distribution of a vibration amplitude of the observation point to a second deflection amount that is the normalized deflection amount indicating a distribution of a vibration amplitude of a designated position, the vibration component of the designated position derived based on the vibration component and the amplitude ratio, and the static response of the designated position derived based on the time-series data and the estimated value.

A time point is acquired by steps including a data acquisition step of acquiring time-series data indicating a time change of a displacement of a structure based on a physical quantity generated at a predetermined observation point in the structure as a response caused by a movement of a formation moving object formed with one or more moving objects on the structure; a removing step of removing a vibration component included in the time-series data; and a time point acquisition step of acquiring an entry time point at which the formation moving object enters the structure and an exit time point at which the formation moving object exits from the structure, based on the time-series data after the vibration component is removed.

A first index value, which is an index value of a deflection amount of a structure generated at an observation point, and a second index value, which is an index value of a deflection amount at a designated position in the structure, are acquired based on the number of moving objects formed in a formation moving object, an entry time point, an exit time point, and environment information. An estimated value of the deflection amount of the structure at the designated position is derived based on time-series data measured at the observation point, the first index value, and the second index value.

A system for estimating both thickness and wear state of refractory material (1) of a metallurgical furnace (12), including at least on processor including a database of simulated frequency domain data named simulated spectra representing simulated shock waves reflected in simulated refractory materials of known state and thickness, each simulated spectrum being correlated with both known state and thickness data of the considered simulated refractory material, wherein the at least one processor is configured to record a reflected shock wave as a time domain signal, and to convert it into frequency domain data named experimental spectrum, and are further configured to compare the experimental spectrum with at least a plurality of simulated spectra from the database, to determine the best fitting simulated spectrum with the experimental spectrum and to estimate thickness and state of the refractory material (1) of the furnace (12) using known state and thickness data correlated with the best fitting simulated spectrum.

A method of determining the location and size of a crack in a blade includes measuring a time of arrival of a tip of the blade at an angular position in a rotation, using the time of arrival to calculate a displacement of the tip of the blade, and using the displacements to calculate a first vibration condition and a second vibration condition for the blade. The method also includes comparing the first vibration condition and the second vibration condition for the blade to a predetermined baseline first vibration condition and a predetermined baseline second vibration condition for the blade to determine a change in the first vibration condition and a change in the second vibration condition, and using the magnitude of the change in the second vibration condition relative to the change in the first vibration condition to determine the likely location of the crack and using the magnitude of the change in the first vibration condition and the change in the second vibration condition to determine the size of the crack.

According to one embodiment, a structure evaluation system of the embodiments includes a plurality of sensors, an arrival time determiner, a reliability calculator, and a map generator. The plurality of sensors detect elastic waves. The arrival time determiner determines arrival times of the elastic waves using elastic waves detected by the plurality of respective sensors. The reliability calculator calculates reliabilities related to measurement waveforms of the elastic waves on the basis of the arrival times. The map generator generates a first map on the basis of the calculated reliabilities or the reliabilities and a distance.

Disclosed herein are components, systems, and methods to monitor acoustic emissions of a high pressure system to predict failure of the high pressure system. Further disclosed herein are components, systems, and methods to monitor acoustic emissions of a high pressure system to identify characteristics of one or more defects as they form and grow within components of the high pressure system. Characteristics of the defects include type, size, growth, and location.

A testing procedure including a data collection procedure and a contrastive learning-based approach, for establishing a profile for utility poles surveyed in an embedding space. Unique properties of utility poles are preserved in a low-dimensional feature vector. Similarities between pairs of samples collected at the same or different poles is reflected by the Euclidean distance between the pole embeddings. During data collection—variabilities of excitation signals are manually introduced, e.g. impact strength, impact locations, impact time ambiguity, data collecting location ambiguity on a DFOS/DAS optical sensor fiber/cable. Data so collected provides a learned model learned complete information about a utility pole and is more robust with respect to uncontrollable factors during operation. A model training procedure that effectively extracts a utility pole intrinsic properties (e.g., structure integrity, dimensions, structure variety) and remote extrinsic influence (e.g., excitation strength, weather conditions, road traffic), without knowing the ground truth of these factors. The only identifying label required is an ID of any tested poles, which is readily available. The model is trained adaptively—end-to-end—is advantageously easy-to-implement on modern deep learning frameworks such as PyTorch.

An apparatus for detecting a transient event in an operating machine, the apparatus comprising: a controller configured to control performance of the following steps: a measurement step comprising measuring a periodic signal from a machine; a processing step comprising synchronously processing the periodic signal to track the primary frequency; a filtering step comprising removing the primary periodic component and its harmonics from the periodic signal to yield a filtered dataset; an integration step comprising integrating the filtered dataset over the remaining frequencies to yield an integrated dataset representing the periodic energy at frequencies other than the primary frequency and its harmonics; an analysis step comprising identifying a short-term transient in the integrated dataset to identify a transient disruption in the operation of the machine.

Systems and methods of providing power to high-voltage sensors in power-limited environments through environmental energy harvesting are disclosed. The systems and methods are configured to intermittently power high-voltage sensors by repeatedly releasing stored energy in bursts. An environmental energy harvesting device generates a low-voltage power supply and is coupled to one or more capacitors to charge the capacitors to a high-voltage threshold. After such high-voltage threshold has been reached, the capacitors are discharged to provide a high-voltage power burst to a high-voltage sensor configured to inspect a component and generate an inspection result signal. The inspection result signal is received by an output module, which may further store or transmit to an external receiver a data signal indicating the inspection results.