The invention relates to a method for determining the degree of wear of at least one component of a machining device (10), wherein at least one actual condition (19) of the machining device (10) is established and the at least one actual condition (19) is compared to at least one comparative condition (18) of the machining device (10), and a conclusion is drawn as to the degree of wear of the at least one component as a function of a deviation determined between the at least one actual condition (19) and the at least one comparative condition (18), wherein, to establish the at least one actual condition (19) and/or the at least one comparative condition (18), sound emissions (16) of the machining device (10) are captured. The invention also relates to a device (13) for determining a degree of wear of at least one component of a machining device (10), a machining device (10) for machining workpieces (11), and a computer program for determining a degree of wear of at least one component of a machining device (10).

A method of sorting chips divided from a plate-shaped workpiece into acceptable chips and defective chips includes an ultrasonic vibration applying step of applying ultrasonic vibrations to chips, a fracture confirming step of confirming whether the chips have been fractured in the ultrasonic vibration applying step or not, and a sorting step of sorting those chips which have been confirmed as not fractured in the fracture confirming step as acceptable chips. The ultrasonic vibrations applied to the chips in the ultrasonic vibration applying step are set to values that do not cause chips to be fractured if the chips are free of minute fractures and cause chips to be fractured if the chips contain minute fractures.

An inspection apparatus for enabling a remotely-located expert to monitor an inspection by a non-expert, the apparatus comprising an inspection device capable of being operated by the non-expert, which is configured to generate inspection data indicative of a condition of a test object, and a communication unit configured to: divide the inspection data into first and second data; transfer the first data for being presented to the remotely-located expert at a first time, to facilitate substantially real-time monitoring of the inspection by the expert; and transfer the second data for being presented to the remotely-located expert at a second time, which is later than the first time, to facilitate non-real time monitoring of the inspection by the expert.

Methods for quantitatively determining the time (TNI) between (1) the application of this method and (2) the time at which the next out-of-service API 653 internal inspection of a steel, field-erected, aboveground storage tank (AST) containing petroleum/water products should be performed. These methods combine four in-service measurements of the thickness, integrity, and corrosion rate of the tank bottom with an empirical corrosion rate cumulative frequency distribution (CFD) for the tank of interest to develop a Bayesian tank bottom survival probability distribution to determine TNI. During this entire TNI time period, the risk of tank bottom failure is less than at the time these methods were applied. If available, the results of a previous out-of-service API 653 internal inspection are also used. These methods can be applied at any time while the tank is in-service to update the internal inspection interval previously determined in an out-of-service internal inspection of the tank.

A method and a test fixture for evaluating a battery cell composed of a cell body having a plurality of electrode foils, a positive terminal and a negative terminal, wherein the positive terminal and the negative terminal are each joined to the cell body at weld junctions. This includes retaining the cell body of the battery cell in a first clamping device. The terminal is grasped in a terminal gripper. A dynamic stress end effector coupled to the terminal gripper applies a vibrational excitation load to the terminal. A static stress end effector applies a static load to the terminal. Integrity of the weld junction is evaluated based upon the applied static load.

A computer-implemented method, computer program, and device for evaluating timed-based probabilities of failure of sections of a pipe network are provided. To do so, the pipe sections are clustered into classes based on structural and environmental parameters; within each class a sample of pipe sections are selected to be inspected. The scores that are obtained through the inspection are used to train a model of pipe conditions of pipes in a class, in order to estimate the pipe conditions of pipes that have not been inspected. The pipe conditions are used to parameterize a predictive model of pipe failures.

An Internet of Thing (IoT) device includes a body with a processor, a camera and a wireless transceiver coupled to the processor.

A system for measuring the position of a rod element as, for example, a hydraulically or pneumatically operated piston rod. Unlike the prior art, the system according to the present invention employs a measuring principle that does not require preparatory treatment of the rod element as is required in the known solutions. The system employs direct time of flight measurements with the aid of acoustic surface waves that are introduced into the rod element. The instrument is retrofittable on existing cylinders without any modification/reconstruction thereof. An EMAT principle is employed to introduce the surface waves into the measurement in a non-contact manner.

A drilling tool for drilling a wellbore in a formation, where the drilling tool includes: a drill bit comprising a cutting element, a sensor array, and a controller. The sensor array includes: an acoustic emissions (AE) sensor configured to measure an acoustic signal generated during drilling of the formation by the cutting element and a load sensor configured to measure an applied load by the cutting element on the formation. The controller is communicably connected to the sensor array and configured to determine a toughness of the cutting element using the acoustic signal, the applied load, and a wear state.

A method for probabilistic fatigue life prediction using nondestructive testing data considering uncertainties from nondestructive examination (NDE) data and fatigue model parameters. The method utilizes uncertainty quantification models for detection, sizing, fatigue model parameters and inputs. A probability of detection model is developed based on a log-linear model coupling an actual flaw size with a nondestructive examination (NDE) reported size. A distribution of the actual flaw size is derived for both NDE data without flaw indications and NDE data with flaw indications by using probabilistic modeling and Bayes theorem. A turbine rotor example with real world NDE inspection data is presented to demonstrate the overall methodology.