A method for detecting a wiring fault in a capacitive sensor (1), such as a knock sensor, connected, via a passive acquisition interface (5), to a communication port (P1), that can be configured in either input mode or output mode, of a computer (2), wherein the communication port (P1) is configured in output mode, and a square wave voltage Vn capable of at least partially charging the capacitors (C6, C7, C8a, C8b, C10) of the acquisition interface (5) and the capacitive sensor (1) is generated during a time interval Tc, after which the communication port is switched to its input mode, so that at least one data element representative of the voltage of the capacitors and of the capacitive sensor is acquired, and finally these data are compared with previously stored reference data so that a wiring fault can be deduced if there is no matching between the data.

A system for controlling the position of a diaphragm in a diaphragm-containing pressure pod, is provided. The system can include a peristaltic pump, a pressure pod having a flow-through fluid side and a gas side that are separated by a diaphragm, and a pressure sensor operatively connected to the gas side. The pressure sensor is configured to sense pulses of pressure resulting from movement of the diaphragm and caused by the action of the peristaltic pump. A gas source and a valve can be in fluid communication with the gas side of the pressure pod and can be configured to provide gas to, or vent gas from, the gas side. A controller receives pressure signals from the pressure sensor and controls the valve in response, and in so doing, controls the position of the diaphragm. Methods for positioning the diaphragm are also included.

Determining calibration values for atmospheric sensors that provide measured pressures used for estimating altitudes of mobile devices. Particular systems and methods determine if any uncalibrated reference-level pressure estimates associated with an unstable pressure sensor should not be used when calibrating the unstable pressure sensor, and calibrate the unstable pressure sensor using all of the uncalibrated reference-level pressure estimates except any uncalibrated reference-level pressure estimate that should not be used when calibrating the unstable pressure sensor.

A positive airway pressure device is disclosed herein. The positive airway pressure device includes a blower, a buffer chamber, a gas manifold, a first sensor, a second sensor, and a controller. The buffer chamber is downstream of the blower. The buffer chamber configured to receive gas generated by the blower and output the gas to a patient. The gas manifold is fluidly coupling the blower to the buffer chamber. The first sensor is at least partially disposed in the gas manifold. The first sensor is configured to measure a first pressure in the gas manifold. The second sensor is at least partially disposed in the buffer chamber. The second sensor is configured to measure a second sensor in the buffer chamber.

An example system for non-invasive determination of target properties of a pressure vessel includes: a signal generator acoustically coupled to a fluid contained in the pressure vessel and disposed externally to the pressure vessel, the signal generator to emit acoustic signals into the fluid; a plurality of sensors acoustically coupled to the fluid and disposed externally to the pressure vessel to detect the acoustic signals; a control device interconnected with the signal generator and the plurality of sensors, the control device configured to: control the signal generator to emit acoustic signals into the pressure vessel; obtain sensor data from the plurality of sensors, the sensor data representing the acoustic signals as received by the plurality of sensors; compute, based on the detected signal data, the target properties of the pressure vessel; and output an indication of the target properties.

The present tool and method relate to device fault detection, diagnosis and prognosis. More particularly, the present tool and method store in a database a plurality of measured indicators representative of at least one dynamic condition of the device. The present tool and method further binarize by a processor the plurality of measured indicators, and analyze the plurality of binarized measured indicators using a machine learning data tool for extracting at least one pattern from the binarized measured indicators by adding at least one different constraint to each iteration. The at least one extracted pattern is indicative of whether the device has a fault or not.

The fuel pressure sensor abnormality diagnosis apparatus diagnoses that a fuel pressure sensor is abnormal in the case where, because a state where a detected value of the fuel pressure sensor is less than a target value occurs, a fuel discharge amount of a fuel pump is increased, and as a result, the fuel discharge amount reaches its maximum amount, and even if a predetermined period has elapsed since the fuel discharge amount reaches its maximum amount, the detected value is less than the target value.

A pressure sensor which detects a combustion pressure of an engine includes: a contact part which is in direct or indirect contact with a casing of the engine when the pressure sensor is attached to the engine; and a pressure detection unit which detects the combustion pressure and outputs a signal corresponding to the combustion pressure, wherein the pressure detection unit includes a pressure detection element which detects the combustion pressure and outputs a signal, and a circuit unit which converts the signal obtained from the pressure detection element into a signal corresponding to the combustion pressure, and the pressure detection unit is provided at a location positioned more inside the engine than the contact part when the pressure sensor is attached to the engine.

A method for estimating the pressure measurement bias of a barometric sensor in a wireless terminal. A location engine using the method generates an enhanced estimate of the measurement bias. The location engine generates the enhanced estimate based in part on relatively coarse estimates of the elevation of the wireless terminal. Each coarse estimate of elevation is often generated from noisy measurements, such as measurements of signals transmitted by Global Positioning System (GPS) satellites, and has an associated uncertainty. The location engine accounts for the uncertainty in these estimates of elevation by applying an optimal estimation technique, such as Kalman filtering, and by compensating for environment-related effects. Compensating Includes filtering across a plurality of lateral locations and imposing a lower bound of bias uncertainty at the lateral locations. Once the location engine generates the enhanced estimate of measurement bias, it can generate improved estimates of elevation of the wireless terminal.

An interface pressure sensor includes a fluid pressure sensor disposed in a volume defined by a shear wall. The volume is enclosed, and the fluid pressure sensor is encapsulated by, an infill material. The infill material defines a sensing surface that, when pressed, can impart a force that is detectable by the fluid pressure sensor.