A method of calculating a speed of an aircraft, a method for calculating a protection radius, a positioning system and an associated aircraft are disclosed. In one aspect, the method includes obtaining a measured speed of the aircraft and obtaining a measured position of the aircraft, associated with a reliability protection radius related to position. The method also includes calculating, by a correction loop, a corrected speed, wherein the calculation of the corrected speed includes calculating a calculated position by integration of the corrected speed, and correcting the measured speed as a function of a difference between the calculated position and the measured position. The method further comprising calculating a reliability protection radius related to the corrected speed.

Apparatus and associated methods relate to generating a frequency spectrum weighting function for use in estimating a rotational frequency of the rotating member. The estimation of the rotational frequency is based on vibrations sensed by an accelerometer remotely located from a rotating member. The frequency spectrum weighting function is generated by a supervised learning method. The method includes receiving a set of test vectors. The test vectors include a rotational frequency value of the rotating member and a vibrational frequency spectrum corresponding to vibrations propagated to the accelerometer. The vibrations include vibrations caused by the rotating member rotating at the rotational frequency. The method includes calculating a test weighting function, and then weighting the vibrational frequency spectra by the test weighting function. The method includes calculating a vector score indicative of whether the weighted vibrational frequency spectra promote the identification of the rotational frequency of the rotating member.

Apparatus and associated methods relate to generating a frequency spectrum weighting function for use in estimating a rotational frequency of the rotating member. The estimation of the rotational frequency is based on vibrations sensed by an accelerometer remotely located from a rotating member. The frequency spectrum weighting function is generated by a supervised learning method. The method includes receiving a set of test vectors. The test vectors include a rotational frequency value of the rotating member and a vibrational frequency spectrum corresponding to vibrations propagated to the accelerometer. The vibrations include vibrations caused by the rotating member rotating at the rotational frequency. The method includes calculating a test weighting function, and then weighting the vibrational frequency spectra by the test weighting function. The method includes calculating a vector score indicative of whether the weighted vibrational frequency spectra promote the identification of the rotational frequency of the rotating member.

A device for increasing the precision of the distance and the relative velocity of a camera-based sensor with the aid of longitudinal acceleration for use in vehicles, e.g., in passive safety applications. In a first arithmetic unit of the inventive device, a correction of a slowly repeated camera-based measurement of the distance to an object is performed with the aid of an internal, longitudinal acceleration signal sampled at a much higher rate, wherein the inventive correction may be performed within an arithmetic unit of the camera, within a passive safety system or in a unit outside the camera and outside the safety system in the vehicle.

A device for increasing the precision of the distance and the relative velocity of a camera-based sensor with the aid of longitudinal acceleration for use in vehicles, e.g., in passive safety applications. In a first arithmetic unit of the inventive device, a correction of a slowly repeated camera-based measurement of the distance to an object is performed with the aid of an internal, longitudinal acceleration signal sampled at a much higher rate, wherein the inventive correction may be performed within an arithmetic unit of the camera, within a passive safety system or in a unit outside the camera and outside the safety system in the vehicle.

A system and method for real-time data acquisition and presentation of force, position, load, pressures, and movement within a subterranean well pumping system, such as an oil well. Data is gathered using sensors attached to a surface level pump drive and wellhead system. Well structural data and well production data are combined therewith to generate a real-time display of down-hole well operation, including animated graphics of the pump operation, including pump movement, rod and tubing stretch, fluid movement, gas compression, system forces, and fluid pressures. Liquid levels are tested using an acoustic liquid level instrument, and incorporated to improve well performance analysis.

A system and method for real-time data acquisition and presentation of force, position, load, pressures, and movement within a subterranean well pumping system, such as an oil well. Data is gathered using sensors attached to a surface level pump drive and wellhead system. Well structural data and well production data are combined therewith to generate a real-time display of down-hole well operation, including animated graphics of the pump operation, including pump movement, rod and tubing stretch, fluid movement, gas compression, system forces, and fluid pressures. Liquid levels are tested using an acoustic liquid level instrument, and incorporated to improve well performance analysis.

The present invention involves a test subject performing a sit-to-stand (STS) operation while wearing a device (MD) that contains an acceleration sensor (11) on the front of the chest. The present invention derives a muscular strength index (maximum acceleration value per unit of muscle mass during STS activity) representing the muscular strength of a human body by obtaining maximum acceleration value data from a signal expressing the size of an acceleration vector comprising a tri-axial component in detected acceleration, and using the maximum acceleration value data and the muscle mass or body fat mass of the text subject.

The present invention involves a test subject performing a sit-to-stand (STS) operation while wearing a device (MD) that contains an acceleration sensor (11) on the front of the chest. The present invention derives a muscular strength index (maximum acceleration value per unit of muscle mass during STS activity) representing the muscular strength of a human body by obtaining maximum acceleration value data from a signal expressing the size of an acceleration vector comprising a tri-axial component in detected acceleration, and using the maximum acceleration value data and the muscle mass or body fat mass of the text subject.

A system estimates the speed of a moving vehicle and hence the driving behavior of an individual driving the vehicle using accelerometer data. To do so, the system analyzes received accelerometer data to find idling points when the vehicle is not moving during a driving session. Based on the idling points, the system may divide the driving session into two or more segments. The system may then determine the speed of the vehicle at one or more boundary points of each segment. For each segment, the system may analyze the accelerometer data to determine the acceleration of the vehicle for points when the vehicle is moving. Subsequently, the system may calculate the speed of the vehicle for the points when the vehicle is moving based on the acceleration of the vehicle at the points when the vehicle is moving and the speed of the vehicle at the boundary points.