Saudi Arabian Oil Company

Avitas Systems, Inc.

Ali Al Shehri

Ayman Amer

Keith William Brashler

Brian Parrott

Vincent Cunningham

Doru Catalin Turcan

Ahmad Aldabbagh

Ser Nam Lim

Muhammad Ababtain

Mustafa Uzunbas

Mohammed Sarraj

Kamal Youcef-Toumi

Aziz Fihri

Haleema Alamri

Husnul Maab

Layla Alabdrabalnabi

Faisal AlThenayan

John Boot

Godine Kok Yan Chan

Muhammad Sarraj

Example systems and methods for pipe strain detection and diagnosis using sensors for machine casing nozzles are disclosed. One example method includes introducing a rotating machine that includes a rotating element, a machine casing, an inlet nozzle, and an outlet nozzle, where the rotating element is configured to pump a fluid into the inlet nozzle through a first pipe and out of the outlet nozzle through a second pipe. A vibration sensor is attached to a nozzle flange connection of one of the inlet nozzle and the outlet nozzle, where the vibration sensor includes a substrate and a resonant layer disposed on a surface of the substrate, the resonant layer is configured to produce a resonant response in response to receiving a radio frequency signal while the fluid is being pumped. The resonant response is received by a radio frequency resonance detector in response to the radio frequency signal.

Pipe strain detection and diagnosis using sensors for machine casing nozzles

A vertical molten sulfur pump assembly includes a pump motor disposed in a top portion and an impeller disposed in a bottom portion, within an impeller casing. A pump inlet is disposed at the second end below the impeller casing. The vertical molten sulfur pump assembly is configured to pump molten sulfur into the inlet and upwards through a discharge passageway by rotation of the impeller. A vibration sensor and a temperature sensor are disposed on an external surface of the bottom portion, on or proximate to the impeller casing and the pump inlet. A temperature sensor is configured to measure a temperature of the molten sulfur proximate to the pump inlet. A vibration sensor includes a substrate comprising a polymer and a resonant layer, and resonant layer includes an electrically conductive nanomaterial and is configured to produce a resonant response in response to receiving a radio frequency signal.

Molten sulfur pump vibration and temperature sensor for enhanced condition monitoring

A smart pipe segment for use in construction of a pipeline. The smart pipe segment includes a pipe body and a sensing nerve network that is associated with the pipe body and is configured to monitor a condition of the pipe segment in real-time. The sensing nerve network comprises optical nerves, electrical nerves or a combination thereof.

Non-metallics enhanced reliability via embedded sensors (NERVES): optical and electrical sensory nerves

A system includes a vertical charge pump assembly. The vertical charge pump assembly includes a top portion adjacent to a first end of the vertical charge pump assembly and a bottom portion adjacent to a second end of the vertical charge pump assembly. A pump motor is disposed in the top portion and an impeller is disposed in the bottom portion within a bowl casing. A shaft is disposed within a central passageway and connects the pump motor with the impeller. The vertical charge pump assembly also includes an inlet at the second end below the bowl casing. The pump inlet and the bowl casing are configured to be immersed in a fluid, and the vertical charge pump assembly is configured to pump the fluid into the inlet and upwards through the central passageway by rotation of the impeller. A vibration sensor is disposed on an external surface of the bottom portion, on or proximate to the bowl casing and the pump inlet. The vibration sensor includes a substrate comprising a polymer and a resonant layer disposed on a surface of the substrate. The resonant layer comprises an electrically conductive nanomaterial and is configured to produce a resonant response in response to receiving a radio frequency signal.

Vibration monitoring and data analytics for vertical charge pumps

A system includes a vertical molten sulfur pump assembly that includes a top portion adjacent to a first end of the vertical molten sulfur pump assembly and a bottom portion adjacent to a second end of the vertical molten sulfur pump assembly. A pump motor is disposed in the top portion, an impeller is disposed in the bottom portion within an impeller casing, and a shaft is disposed within a central column and connecting the pump motor with the impeller. A pump inlet is disposed at the second end below the impeller casing. The pump inlet and the impeller casing are configured to be immersed in molten sulfur. The vertical molten sulfur pump assembly is configured to pump the molten sulfur into the inlet and upwards through a discharge passageway by rotation of the impeller. A vibration sensor and a temperature sensor are disposed on an external surface of the bottom portion, on or proximate to the impeller casing and the pump inlet. The temperature sensor is configured to measure a temperature of the molten sulfur proximate to the pump inlet. The vibration sensor includes a substrate comprising a polymer and a resonant layer disposed on a surface of the substrate. The resonant layer includes an electrically conductive nanomaterial and is configured to produce a resonant response in response to receiving a radio frequency signal.

A sensor includes a radio frequency interrogator, a responsive patch, a radio frequency resonance detector, and a transmission line. The radio frequency interrogator is configured to produce an electromagnetic interrogation pulse having a first frequency. The responsive patch includes a substrate and a resonant layer disposed on a surface of the substrate. The substrate includes a polymer. The resonant layer includes an electrically conductive nanomaterial. The resonant layer is configured to resonate at the first frequency in response to receiving the electromagnetic interrogation pulse. The radio frequency resonance detector is configured to detect a resonating response of the responsive patch. The transmission line couples the responsive patch to the radio frequency resonance detector. The transmission line is configured to transmit the resonating response of the responsive patch to the radio frequency resonance detector.

Nanosensor coupled with radio frequency for pump condition monitoring

A composite insulating material is provided. In one or more configurations the composite insulating material includes one or more active or responsive elements that mitigate corrosion under insulation (CUI). In a further aspect of the present invention, one or more active components of a composite insulation material are provided that dynamically generate an insoluble barrier within an insulating material through a bio-mineralization process.

Superabsorbent polymer capsules and bio-mineralization process for the mitigation of corrosion under insulation as smart packaging materials

A technological solution for analyzing a sequence of electromagnetic spectrum image frames of a nonmetallic asset and detecting or predicting an aberration in the asset, including a detected or predicted location of the aberration. The technological solution includes receiving the electromagnetic spectrum image frames by a pair of machine learning systems of different types, applying a machine learning algorithm to the electromagnetic spectrum image frames to stratify the electromagnetic spectrum images into abstraction levels according to an image topology and output first aberration determination information, applying a second machine learning algorithm to the electromagnetic spectrum image frames to detect patterns in electromagnetic spectrum images over time and output second aberration determination information, generating an aberration assessment based on the first and second aberration determination information, and transmitting the aberration assessment to a communicating device, including a prediction and location of an aberration in or on the nonmetallic asset.

System and method for cyber-physical inspection and monitoring of nonmetallic structures

A system for predicting corrosion under insulation (CUI) in an infrastructure asset includes at least one infrared camera positioned to capture thermal images of the asset, at least one smart mount supporting and electrically coupled to the at least one infrared camera and including a wireless communication module, memory storage, a battery module operative to recharge the at least one infrared camera, an ambient sensor module adapted to obtain ambient condition data and a structural probe sensor to obtain CUI-related data from the asset. At least one computing device has a wireless communication module that communicates with the at least one smart mount and is configured with a machine learning algorithm that outputs a CUI prediction regarding the asset. A cloud computing platform receive and stores the received data and the prediction output and to receive verification data for updating the machine learning algorithm stored on the computing device.

Cloud-based machine learning system and data fusion for the prediction and detection of corrosion under insulation

A method for identifying corrosion under insulation (CUI) in a structure comprises receiving thermographs from the structure using an infrared camera, applying filters to the thermograph using a first machine learning system, initially determining a CUI classification based on output from the filters, and validating the initial CUI classification by an inspection of the structure. The first machine learning system is trained using results of the validation. Outputs of the first machine learning system and additional structural and environmental data are fed into a second machine learning system that incorporates information from earlier states into current states. The second machine learning system is trained to identify CUI according to changes in the outputs of the first machine learning system and the additional data over time until a second threshold for CUI classification accuracy is reached. CUI is thereafter identified using the first and second machine learning systems in coordination.

Thermography image processing with neural networks to identify corrosion under insulation (CUI)

A system for predicting and detecting of corrosion under fireproof insulation (CUF) in an infrastructure asset comprises a first detection apparatus adapted to capture thermal images of the asset, a second detection apparatus adapted to receive THz radiation from the asset, and at least one ambient condition sensor for detecting environmental conditions at a location of the asset, a communication device coupled to the first and second detection apparatus and at least one ambient condition sensor to receive data therefrom and adapted to communicate the received data, and a computing device communicatively coupled to the communication device and configured with instructions for executing a machine learning algorithm taking as inputs the thermal image, THz and ambient condition data received from the communication device, and to output a CUF prediction regarding the asset.

Inspection and failure detection of corrosion under fireproofing insulation using a hybrid sensory system

Machine learning system and data fusion for optimization of deployment conditions for detection of corrosion under insulation

A system and method is disclosed for measuring the dimensions of physical objects. The systems and methods include a measuring instrument of significant length comprising an array of patch antennas arranged along the length of an elongate substrate such that the antenna array expands and contracts with the substrate. The system also includes a diagnostic computing device for measuring the array's electrical properties including resonance frequency and changes in said properties relative to reference electrical properties that correspond to a reference length of the array and substrate. Accordingly, based on the measured changes in electrical properties and the reference length, the diagnostic system can calculate the current length of the measuring instrument. Accordingly, the disclosed systems and methods can provide self-calibrating measuring systems and measuring systems capable of being deployed onto a structure for periodically calibrating the structure's dimensions as it expands or contracts during operation.

Growing community of inventors

Thuwal, Saudi Arabia

Ali Al Shehri