Portable Pump Capable of Transmitting Air Pressure Value Via Wireless Transmission to Mobile Electronic Device for Indication
US-2015110645-A1 · Apr 23, 2015 · US
US9790938B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9790938-B2 |
| Application number | US-201514856705-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 17, 2015 |
| Priority date | Sep 17, 2014 |
| Publication date | Oct 17, 2017 |
| Grant date | Oct 17, 2017 |
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A system for monitoring the operation of a surface pump such as a hand-operated water pump or oil pump, which uses an accelerometer mounted to a component of the pump to monitor movement of a pump component, for example the handle, and transmitted via a data connection such as a mobile data communications network to a server. The accelerometer measurements are processed by using a trained model such as a support vector machine to output an indication of the condition of the pump or the level of liquid in the well or borehole served by the pump. The model may be trained using a training data set of sensor measurements associated with liquid level in the well and condition of the pump.
Opening claim text (preview).
Therefore, the following is claimed: 1. A system for monitoring a surface pump for raising liquid from a well, the monitoring system comprising: a surface pump comprising a handle for operating the pump; a sensor mounted on or associated with the handle, wherein the sensor is configured to sense movement of the handle and provide an output signal representative thereof; and a signal processor for receiving the sensor output signal and processing it to derive therefrom an estimate of the level of liquid in the well or an estimate of the condition of the pump or both. 2. The system according to claim 1 , wherein the signal processor comprises a trained model for deriving the estimate of the level of liquid or the condition of the pump, or both, from the output signal from the sensor. 3. The system according to claim 2 , wherein the trained model comprises a classifier. 4. The system according to claim 2 , wherein the trained model comprises a support vector machine, artificial neural network, kernel-based machine or Gaussian process classifier. 5. The system according to claim 1 , wherein the signal processor is adapted to extract a plurality of features from successive periods of the output signal and form them into a feature vectors respectively representing the output signal in the successive periods. 6. The system according to claim 5 , wherein the signal processor is adapted to form a feature vector for each cycle of a periodic output signal from the sensor. 7. The system according to claim 6 , wherein the signal processor is adapted to divide each cycle into a plurality of segments and to form as the feature vector for that cycle the values of the underlying waveform of the output signal at a predetermined position in each segment together with an estimate of the noise in each segment. 8. The system according to claim 7 , wherein the signal processor is adapted to divide each cycle into the same number of segments whereby the duration of each segment may vary from cycle to cycle. 9. The system according to claim 1 , wherein the system comprises a surface pump and a monitoring system, wherein the monitoring system comprises the sensor and the signal processor. 10. The system according to claim 1 , wherein the surface pump is one of: a water pump, an oil pump, a hand pump, or a reciprocating pump. 11. The system according to claim 1 , wherein the sensor is an accelerometer, pressure sensor or vibration transducer. 12. The system claim 2 , wherein the sensor is an accelerometer, pressure sensor or vibration transducer. 13. The system according to claim 1 , wherein the signal processor processes the output signal to classify at least one of: the condition of pump, or the user of the pump. 14. The system according to claim 1 , further comprising a data transmitter for sending data from at least one of the sensor and the signal processor via a data communications link. 15. A method of monitoring a surface pump for raising liquid from a well, the method comprising: measuring movement of a handle of the pump and providing an output signal representative thereof; receiving the output signal and processing it to derive therefrom an estimate of the level of liquid in the well, or an estimate of the condition of the pump or both. 16. The method according to claim 15 , wherein the output signal is processed to derive the estimate of the level of liquid in the well or the condition of the pump by means of a trained model. 17. The method according to claim 16 , wherein the trained model comprises a classifier, support vector machine, artificial neural network, kernel-based machine or Gaussian process classifier. 18. The method according to claim 15 , comprising the steps of extracting a plurality of features from successive periods of the output signal and forming them into a feature vectors respectively representing the output signal in the successive periods. 19. The method according to claim 18 , wherein each successive period is divided into a plurality of segments and the feature vector for that period is formed by the values of the underlying waveform of the output signal at a predetermined position in each segment together with an estimate of the noise in each segment. 20. The system according to claim 1 , wherein the sensor is an accelerometer or vibration transducer.
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