In this paper, a detailed description for the ETDR distributed strain sensing mechanism of a coaxial cable was presented, and a signal calibration algorithm for interpreting ETDR signal waveforms was developed. In addition, a prototype coaxial ETDR distributed strain sensor with improved signal sensitivity was presented. The ETDR signal responses of the prototype sensor subjected to a concentrated lateral compression load and distributed axial tension load were experimentally tested. The test results showed that the prototype sensor has a substantially improved signal sensitivity over a commercial RG-174 cable of comparable size. It was also shown that the relation between the impedance change of the sensor and the applied axial tensile strain depends primarily on the mechanical stress–strain response of the sensor. From the test results, it was demonstrated that this relation could be empirically established with the aid of the calibration algorithm.

Feasible application of the electrical time domain reflectometry (ETDR) technique for distributed strain measurement is investigated in this study. A prototype coaxial ETDR distributed strain sensor is embedded into a laboratory-scale reinforced concrete beam specimen, and three-point bending tests are conducted. The ETDR signal waveforms of the embedded sensor are used to determine the deflection profiles of the beam under various bending loads. The resulting deflection profiles are validated by their good agreements with the deflection measurements by LVDT displacement sensors at four discrete locations. It is shown that the ETDR distributed sensing technique has the capability to capture the variation of the load-induced axial strain along the sensing line. In addition, the ETDR distributed sensor could also clearly capture the location of localized high strain points.

Feasible application of the Electrical Time Domain Reflectometry (ETDR) distributed strain sensing technique for structural damage detection was investigated in this study. A smallscale concrete beam specimen with an embedded ETDR distributed strain sensor was tested in three-point bending. The resulting ETDR waveforms of the sensor were studied in conjunction with the load-displacement curve of the concrete beam and the video images of the specimen recorded during the test. It was shown that the embedded ETDR sensor was capable of detecting weak points in the structure resulted from structural defects. The embedded sensor also had the capability to detect a load-induced damage at its early stage when no surface crack line was visible. On the occurrence of an apparent crack damage that passed through the sensing line, the embedded sensor could locate its position with a precision within 0.25 . Moreover, the ETDR distributed sensor had the capability to detect multiple cracks simultaneously along a single sensing line.

The valve condition prognostics (VCP) system detects anomalies on high-pressure pump fluid-end valves and seats during fracturing before a total functional failure occurs. The VCP enables condition-based fluid-end replacement instead of time-based maintenance intervals, thereby minimizing downtime and maintenance cost and increasing asset utilization while eliminating permanent fluid-end damage due to operating with leaky valves. This is a step change when compared to the fixed-interval maintenance system. The VCP includes the programmable logic controller (PLC), analog and digital modules, a rotation monitoring encoder connected to the power end, and pressure transducers to monitor fluid-end discharge and suction pressures. The intelligent algorithms feature robust failure prediction criteria based on machine learning [1], pattern classification [2], and adaptive algorithms, applicable to various equipment and field conditions. By obtaining ongoing and accurate pressure signatures, the VCP detects warnings and alarms that are sent to the operators in real time for action. Based on the alarms and operating parameters, the pumps can be shut down automatically to prevent damage. During multiple field tests, the VCP successfully extended usable valve life by at least 45% when compared to our current fixed-interval maintenance method. The VCP is 100% accurate in detecting a catastrophic valve failure and avoided fluid-end damage. The VCP kits are easy to install onto existing pumps using existing discharge and suction pressure sensors. The data are sent to the cloud, and high-frequency data are recorded in the PLC for detailed analysis as needed. In contrast to the common replacement approach that is based on either a scheduled time interval or when an operational failure happens, the VCP can detect and notify when an anomaly occurs and performs maintenance only when necessary. The fixed-schedule maintenance approach replaces the valves and seats in a conservative fashion regardless of their condition, often leading to waste. In the failure-based maintenance situation, equipment damage often results, leading to devastating pump shut down and expensive fluid end replacement. The VCP addresses both challenges. It not only prevents prolonged and costly equipment failures, but also reduces downtime, valve and seat parts cost, and maintenance time.