Abstract:
A vehicle includes an automatic transmission and a set of sensor inputs providing values indicating a current operational status of the vehicle pertinent to controlling the automatic transmission. The set of sensor inputs include: engine speed, engine torque, current transmission gear; and vehicle speed. The vehicle includes a programmed processor configured to iteratively and co-dependently generate a vehicle mass parameter value and a grade of incline parameter value. The programmed processor, when generating the vehicle mass parameter value and the grade of incline parameter value, uses a set of parameters including: a propulsive force driving the vehicle; a set of forces acting on the vehicle resisting forward movement, and an observed rate of change of a speed of the vehicle.
Abstract:
A method may include receiving information related to operation or a configuration of a hydraulic fracturing system. The hydraulic fracturing system may include a plurality of electric power source outputs and a plurality of hydraulic fracturing rigs. The method may further include performing, based on the information, asymmetric power management of the plurality of electric power source outputs. The method may further include performing, based on the information, asymmetric load management of the plurality of hydraulic fracturing rigs.
Abstract:
A detection system for detecting winding faults, such as inter-turn winding faults in the stator and/or rotor of an electrical generator utilizes one or more vibration sensors that can be located on a generator housing. The vibration sensors make mechanical vibration measurements and transmit them to a fault analyzer. The fault analyzer can compare the measured vibrations with a threshold to determine if a winding is occurring. In an embodiment, the fault analyzer can convert the mechanical vibration measurements from the time domain to a frequency domain to facilitate analysis.
Abstract:
A system may comprise a device. The device may be configured to receive, from one or more sensor devices of the machine, sensor data associated with wear of one or more components of an undercarriage of the machine; and predict, using a machine learning model and the sensor data, an amount wear of the one or more components based on a wear rate of the one or more components. The machine learning model is trained, using training data, to predict the wear rate of the one or more components. The training data includes two or more of: historical sensor data, historical inspection data, or simulation data, of a simulation model, from one or more third devices. The device may perform an action based on the amount of wear.
Abstract:
A detection system for detecting winding faults, such as inter-turn winding faults in the stator and/or rotor of an electrical generator utilizes one or more vibration sensors that can be located on a generator housing. The vibration sensors make mechanical vibration measurements and transmit them to a fault analyzer. The fault analyzer can compare the measured vibrations with a threshold to determine if a winding is occurring. In an embodiment, the fault analyzer can convert the mechanical vibration measurements from the time domain to a frequency domain to facilitate analysis.
Abstract:
A hydraulic fracturing machine includes a pump failure detection system. The hydraulic fracturing machine includes a hydraulic fracturing pump with a power end and a fluid end. The power end includes a plurality of roller bearings, and the fluid end includes a flow of fluid. A particle sensor coupled to the power end is configured to transmit particle information regarding a quantity of particles in the fluid. A temperature sensor, also coupled to the power end, is configured to transmit temperature information regarding a temperature of the fluid. A vibration sensor coupled to the power end is configured to transmit vibration information regarding a vibration of each of the plurality of roller bearings. An electronic control module analyzes the particle information, the temperature information and the vibration information, and calculates a failure warning level based on the analysis.
Abstract:
A computer implemented preventative maintenance schedule can includes a plurality of predetermined maintenance intervals. A replaceable maintenance item may be initially assigned to an initially assigned maintenance interval. A performance data associated with the replaceable maintenance item may be measured and an estimated end of useful life may be determined based on the performance data. The estimated end of useful life is compared to the assigned maintenance interval and, if warranted, the assigned maintenance schedule is modified.
Abstract:
A system for detecting wear or failure of a genset coupling of a genset power system is provided. The system includes a vibration sensor for measuring vibrations, and an additional sensor for measuring an operating condition. A controller is configured to process operating condition data from the additional sensor using a modeling software to generate simulated data. The controller applies time domain information of at least one of the simulated data and vibration sensor data to the modeling software using a machine learning algorithm, and perform a comparison to identify wear or failure of the coupling, wherein, when performing the comparison, the controller compares at least one of: time domain information of the vibration sensor data to time domain information of the simulated data or frequency domain information of the vibration sensor data to frequency domain information of the simulated data, to identify wear or failure of the coupling.
Abstract:
A rig management system is disclosed. The rig management system may be configured to receive vibration data from a set of sensors installed on one or more elements of a hydraulic fracturing rig. The rig management system may be configured to perform a first processing of the vibration data utilizing a moving window technique to identify a possible failure of a set of bearings. The rig management system may be configured to perform a second processing utilizing a set of processing techniques after identifying the possible failure of the set of bearings. The rig management system may be configured to determine that the possible failure is an actual failure based on a result of performing the second processing. The rig management system may be configured to perform an action after determing that the possible failure is the actual failure.
Abstract:
Methods and apparatus for predicting clutch local peak temperatures in real time and controlling engagement of a friction clutch are disclosed. The clutch local peak temperature prediction can take into account machine operating parameters such as clutch control current, clutch shaft speed and clutch load to determine clutch local peak temperatures at hot spots within the friction clutch. A thermal-mechanical finite element analysis model may be developed for the friction clutch and used to generate a surrogate model of the friction clutch that can be used by an electronic control module of the machine to predict the local peak temperature of the friction clutch in real time and control engagement and disengagement of the friction clutch to maintain the local peak temperature below a critical peak temperature above which damage to the components of the friction clutch may occur.