An ultrasonic quality control as disclosed can inspect a quality of a piece and classify the piece automatically. The piece can be scanned, and an image formed from the scanning. A reference piece is also scanned, and a reference image is formed. A negative image of the reference image is formed, and an indication image is created by utilizing the image and the negative image. The indication image is filtered by utilizing several image filters, each image filter filtering all data of the indication image except an image filter specific indication level data. Further several indication levels data are provided from the image filter specific indication level data, and the piece can be classified utilizing the several indication levels data.

An inspection robot, and methods and a controller thereof are disclosed. An inspection robot may include an inspection chassis including a plurality of inspection sensors and coupled to at least one drive module to drive the robot over an inspection surface. The inspection robot may also include a controller including an inspection data circuit to interpret inspection base data, an inspection processing circuit to determine refined inspection data, and an inspection configuration circuit to determine an inspection response value in response to the refined inspection data. The controller may further include an inspection response circuit to, in response to the inspection response value, provide an inspection command value while the inspection robot is interrogating the inspection surface.

A method of monitoring a portion of an equipment under pressure implementing a control station to control an ultrasonic non-destructive testing device through a remote network, includes: the control station sends a first measurement request to the non-destructive testing device; the control station receives a first plurality of measurement data from the non-destructive testing device, constructs a first mapping of the portion of the structure from the data; sends a second measurement request to the non-destructive testing device, receives a second plurality of measurement data from the non-destructive testing device, constructs a second mapping of the portion of the structure, from the second plurality of measurement data, and compares the first mapping and the second mapping.

Systems and methods are disclosed for detecting a crack in an automotive windshield and alerting a user of the same. This can allow the user to repair the crack before the user might otherwise detect the crack by his/her own visual inspection. The windshield can be provided with emitters configured to emit signals (e.g., sound, light, etc.) and corresponding detectors configured to detect the emitted signals. Signal profiles or signatures can be stored that represent normal measurements when there is no crack. Upon detecting a signal signature that deviates from the stored normal signal signatures, the system can notify the user of a potential crack in the windshield. The system can also determine the location of the crack based upon which of the detectors detect a change in the detected signal.

A method of inspection or maintenance of a curved ferromagnetic surface using an unmanned aerial vehicle (UAV) having a releasable crawler is provided. The method includes: flying the UAV from an initial position to a pre-perching position in a vicinity of the ferromagnetic surface; autonomously perching the UAV on the ferromagnetic surface; maintaining magnetic attachment of the perched UAV to the ferromagnetic surface; releasing the crawler from the magnetically attached UAV onto the ferromagnetic surface; moving the crawler over the curved ferromagnetic surface while maintaining magnetic attachment of the released crawler to the ferromagnetic surface; inspecting or maintaining the ferromagnetic surface using the magnetically attached crawler; and re-docking the released crawler with the perched UAV.

A method for detecting breaks or defects in railroad spikes transmits an ultrasonic signal that propagates along the body of the spike and detects the resulting reflected ultrasonic signal. The reflected signal is then analyzed to automatically detect the presence of a break or defect in the spike based on the time delay between the reflected signal and the transmitted signal.

A computer-implemented process determines, based on bearing fault frequencies, optimum values for the maximum frequency (F.sub.max) and the number of lines of resolution (N.sub.lines) to be used in collecting machine vibration data so as to adequately distinguish between spectral peaks for identifying faults in machine bearings. The process can be extended to any other types of fault frequencies that a machine may exhibit, such as motor fault frequencies, pump/fan fault frequencies, and gear mesh fault frequencies. Embodiments of the process also ensure that the time needed to acquire the waveform is optimized. This is particularly useful when collecting data using portable vibration monitoring devices.

A computer-implemented process determines, based on bearing fault frequencies, optimum values for the maximum frequency (F.sub.max) and the number of lines of resolution (N.sub.lines) to be used in collecting machine vibration data so as to adequately distinguish between spectral peaks for identifying faults in machine bearings. The process can be extended to any other types of fault frequencies that a machine may exhibit, such as motor fault frequencies, pump/fan fault frequencies, and gear mesh fault frequencies. Embodiments of the process also ensure that the time needed to acquire the waveform is optimized. This is particularly useful when collecting data using portable vibration monitoring devices.

Embodiments provide systems and methods for utilizing acoustic sensors to detect defects via online or in situ monitoring of additive manufacturing (AM) processes. Sensors may capture acoustic waves associated with AM manufacturing operations. The acoustic emissions in combination with other sensing data, such as cameras or thermometers, may be used to characterize the state of the AM process, such as to detect a defect has occurred or confirm a defect has not occurred. When defects are detected, the AM process may be stopped to prevent further processing of a defective part. When defects are predicted as likely to occur, operational parameters of the AM device or process may be adjusted to mitigate the occurrence of a defect. The techniques disclosed herein enable detection of defects that occur underneath the surface of the part being manufactured, as well as correct issues with the AM device or process before a defect occurs.

Inspection robots with swappable drive modules are described. An example inspect robot may include a first removeable interface plate on the side of a robot chassis. The first removable interface plate may couple a first drive module to an electronic board, within the chassis, where the electronic board includes a drive module interface circuit communicatively coupled to the first drive module. The example inspect robot may also include a second removeable interface plate on a side of a robot chassis. The second removable interface plate may couple a second drive module to an electronic board, within the chassis, where the electronic board includes a drive module interface circuit communicatively coupled to the second drive module.