The present invention relates to a system and method for monitoring wear in pipes, particularly irregular wear in pipelines transporting abrasive fluids. The system includes a plurality of wear sensors spaced along a length of a pipe. Each wear sensor is configured to detect wear in a wall of the pipe. The system further includes at least one remotely accessible server operatively connected to the sensors for receiving and monitoring data output from said sensors. The server is configured to alert an operator when said data received from any one of the plurality of sensors is indicative of irregular wear in the wall of the pipe.

A method is provided for determining the geometry of one or more real, examined defects of a metallic and in particular magnetizable object, in particular a pipe or a tank, by means of at least two reference data sets of the object generated on the basis of different, non-destructive measuring methods.

A method is provided for determining the geometry of one or more real, examined defects of a metallic and in particular magnetizable object, in particular a pipe or a tank, by means of at least two reference data sets of the object generated on the basis of different, non-destructive measuring methods.

A degradation predicting method is a degradation predicting method for predicting degradation of a reinforced concrete structure buried in the ground, the method including: a condensation occurrence condition evaluating step (S1) of evaluating a condensation occurrence condition on which condensation occurs on reinforcing steel; a condensation time calculating step (S2) of calculating a condensation time that is a total time in which condensation occurs on the reinforcing steel based on the condensation occurrence condition for each of a plurality of the reinforced concrete structures; a threshold determining step (S3) of determining a threshold of underground depth at which the reinforced concrete structure is less prone to degradation based on a relationship between the condensation time and a underground depth of the reinforced concrete structure; and a degradation predicting step (S4) of predicting degradation of a prediction-target reinforced concrete structure based on the threshold.

A degradation predicting method is a degradation predicting method for predicting degradation of a reinforced concrete structure buried in the ground, the method including: a condensation occurrence condition evaluating step (S1) of evaluating a condensation occurrence condition on which condensation occurs on reinforcing steel; a condensation time calculating step (S2) of calculating a condensation time that is a total time in which condensation occurs on the reinforcing steel based on the condensation occurrence condition for each of a plurality of the reinforced concrete structures; a threshold determining step (S3) of determining a threshold of underground depth at which the reinforced concrete structure is less prone to degradation based on a relationship between the condensation time and a underground depth of the reinforced concrete structure; and a degradation predicting step (S4) of predicting degradation of a prediction-target reinforced concrete structure based on the threshold.

A method for detecting a structural anomaly in a pipeline supply network is disclosed where the pipeline supply network is configured to supply fluid to multiple receiving locations. The method comprises receiving acoustic signal data from a selected location in the pipeline supply network and generating a first time window of acoustic signal data based on the acoustic signal data. The method then includes benchmarking the first time window of acoustic signal data with respect to historical background acoustic signal data characterising the pipeline supply network to generate a corresponding background benchmarked first time window of acoustic signal data and then determining an anomaly measure for the background benchmarked first time window of acoustic signal data where the anomaly measure indicates a presence of the structural anomaly.

Method for determining the geometry of multiple defects in a magnetizable object using a reference data record of the object, comprising determining an initial defect geometry as starting defect geometry, determining a first MFL prediction data record as starting prediction data record on the basis of the starting defect geometry, and iteratively adapting the starting defect geometry to the geometry of the real defect(s) by means of the EDP unit and by means of multiple expert routines (11) running in competition and preferably in parallel with one another.

Method for determining the geometry of multiple defects in a magnetizable object using a reference data record of the object, comprising determining an initial defect geometry as starting defect geometry, determining a first MFL prediction data record as starting prediction data record on the basis of the starting defect geometry, and iteratively adapting the starting defect geometry to the geometry of the real defect(s) by means of the EDP unit and by means of multiple expert routines (11) running in competition and preferably in parallel with one another.

An inspection device includes multiple magnetic sensors, wiring for calibration and a controller. The wiring for calibration is arranged at the same relative position with respect to a magnetically sensitive portion of each of the multiple magnetic sensors. The controller obtains a first output value of each of the multiple magnetic sensors in advance. Before a predetermined portion of an electrical steel sheet passes the position of the magnetic sensors, the controller retracts the multiple magnetic sensors. The controller starts applying a current to the wiring for calibration. The controller obtains a second output value of each of the multiple magnetic sensors. After the predetermined position passes, the controller displaces the multiple magnetic sensors to the detection position. The controller corrects a measurement value measured by each of the multiple magnetic sensors based on the first output value and the second output value.

An inspection device includes multiple magnetic sensors, wiring for calibration and a controller. The wiring for calibration is arranged at the same relative position with respect to a magnetically sensitive portion of each of the multiple magnetic sensors. The controller obtains a first output value of each of the multiple magnetic sensors in advance. Before a predetermined portion of an electrical steel sheet passes the position of the magnetic sensors, the controller retracts the multiple magnetic sensors. The controller starts applying a current to the wiring for calibration. The controller obtains a second output value of each of the multiple magnetic sensors. After the predetermined position passes, the controller displaces the multiple magnetic sensors to the detection position. The controller corrects a measurement value measured by each of the multiple magnetic sensors based on the first output value and the second output value.