Patent classifications
G01N29/4445
METHOD AND APPARATUS FOR MONITORING BATTERY STATE
A method and an apparatus for monitoring battery state are provided. A method of monitoring battery state involves collecting vibration information based on a signal from an acceleration sensor, calculating a cumulative impact based on the vibration information, and estimating a degree of damage to a battery based on the cumulative impact.
DIGITAL TWIN MODEL INVERSION FOR TESTING
Creation and use of a digital twin instance (DTI) for a physical instance of the part. The DTI may be created by a model inversion process such that model parameters are iterated until a convergence criterion related to a physical resonance inspection result and a digital resonance inspection result is satisfied. The DTI may then be used in relation to part evaluation including through simulated use of the part. The physical instance of the part may be evaluated by way of the DTI or the DTI may be used to generate maintenance schedules specific to the physical instance of the part.
Non-linear Lamb wave mixing method for measuring stress distribution in thin metal plates
The invention discloses a non-linear Lamb wave mixing method for measuring stress distribution in thin metal plates. The method is suitable for stress distribution detection and stress concentration area positioning in a plate structure and belongs to the field of nondestructive detection. The steps of the present invention is: first determines the excitation frequencies of two fundamental waves according to the measured object and the nonlinear Lamb wave mixing resonance conditions; the left and right ends of the test piece are oppositely excited two rows of A0 mode waves, and the excitation signal receive the sum-frequency S0 signal at a certain position to detect non-linear mixing stress of the plate structure; by changing the excitation time delay of the excitation signal, perform mixing scan on different positions of the test piece to extract the mixing wave amplitude; finally, according to the variation of amplitude of sum frequency difference signal with mixing position to realize the detection of stress distribution of metal plate and the positioning of the stress concentration area.
Integrated laser bond inspection and associated systems and methods
Disclosed herein is a system and method for inspecting a bonded structure in a component. The system includes an integrated probe and a processor coupled to the integrated probe. The integrated probe includes an ultrasonic component and a laser component. The ultrasonic component is configured to transmit pulsed sound waves into the bonded structure and receive reflected pulsed sound waves from the bonded structure. The laser component is configured to generate laser pulses and direct the laser pulses to the bonded structure to generate tension waves across the bonded structure. The processor is configured to test a bonded structure in the component. Further, the processor includes a pre-test module configured to operate the ultrasonic component in a pre-test mode, a test module configured to operate the laser component in a test mode, and a post-test module configured to operate the ultrasonic component in a post-test mode.
DIGITAL TWIN MODEL INVERSION FOR TESTING
Creation and use of a digital twin instance (DTI) for a physical instance of the part. The DTI may be created by a model inversion process such that model parameters are iterated until a convergence criterion related to a physical resonance inspection result and a digital resonance inspection result is satisfied. The DTI may then be used in relation to part evaluation including through simulated use of the part. The physical instance of the part may be evaluated by way of the DTI or the DTI may be used to generate maintenance schedules specific to the physical instance of the part.
STRUCTURE EVALUATION SYSTEM, STRUCTURE EVALUATION APPARATUS, AND STRUCTURE EVALUATION METHOD
According to one embodiment, a structure evaluation system according to an embodiment includes a plurality of sensors, a position locator, a corrector, and an evaluator. The plurality of sensors detect elastic waves generated from a structure. The position locator locates the position of a generation sources of a plurality of elastic waves on the basis of the plurality of elastic waves detected by the plurality of sensors. The corrector corrects information based on the position locating performed by the position locator using a correction value set in correspondence with an impact. The evaluator evaluates a deterioration state of the structure on the basis of the corrected information.
NON-DESTRUCTIVE TEST SYSTEMS WITH INFRARED THERMOGRAPHY ASSEMBLIES AND ULTRASONIC TEST ASSEMBLIES, AND ASSOCIATED METHODS
Non-destructive test systems and associated methods. A non-destructive test system includes an infrared thermography assembly and an ultrasonic test assembly for testing a test piece. The infrared thermography assembly may include one or more thermography sensor modules and a thermography test controller. The ultrasonic test assembly may include one or more ultrasonic sensor subassemblies with respective excitation modules and respective detector modules and an ultrasonic test controller. Each excitation module may be configured to produce a respective ultrasonic beam within the test piece, and each detector module may be configured to detect a respective reflected vibration of the test piece. In some examples, a method of performing a non-destructive test on a test piece includes testing an infrared test region of the test piece with an infrared thermography assembly and testing an ultrasonic test region of the test piece with an ultrasonic test assembly.
Predictive integrity analysis
A system includes one or more tools, sensors, or both configured to obtain data related to the one or more pipelines, wherein the data is ultrasonic data, electromagnetic data, or both, and a cloud-based computing system including at least one processor that receives the data from the one or more tools, sensors, or both, performs analysis to generate a virtual structural model of the one or more pipelines based on the data, determines one or more states of the one or more pipelines using the virtual structural model and determines whether to take one or more actions when the one or more states indicate that the one or more pipelines violate a threshold operation boundary.
Characterization of nanoindentation induced acoustic events
A method of creating and characterizing a representative image of the surface of an object from acoustic emissions of a multimode ultrasonic probe tip and transducer integrated into a micro tool, such as a nano indenter or a nano indenter interfaced with a Scanning Probe Microscope (SPM). The representative image may be utilized to predict mechanical properties or characteristics of the sample, including topography, fracture patterns, indents and artifacts. The tip component is configured to operate at multi-resonant frequencies providing sub-nanometer vertical resolution. The tip component may be quasi-statistically calibrated and deep learning iterative image comparison and characterization may be utilized to derive mechanical properties of a sample.
METHOD AND SYSTEM FOR ASSESSING HEALTH OF A WOOD SPECIMEN
Present disclosure discloses method and system for assessing health of a wood specimen. Method receives ultrasonic data for each of a plurality of alignments of a transmitter and associated receiver across a cross-section of one or more cross-sections along a length of the wood specimen. The ultrasonic data comprises a pulse velocity, a transit time and a distance travelled by an ultrasonic pulse between the transmitter and the associated receiver. Thereafter, method measures relative features of the wood specimen using the ultrasonic data. Subsequently, method identifies a condition of the cross-section of the wood specimen based on the relative features using a trained ML model. Upon identifying the condition of the cross-section to be defective, method determines a position of a defect in the cross-section of the wood specimen using the relative features and determines a severity of the defect using the trained ML model and the relative features.