Multi-function liquid leak detector and analyzer
Abstract
A method of monitoring liquid flow includes monitoring liquid flow including the pressure of the liquid, through a slave analyzer device, reporting the monitoring results to a processor configured to control a master analyzer device to adjust the liquid flow and pressure. Periods of usage and periods of non-usage of the liquid are detected by the processor. Subsequently, based on the detected periods of usage and periods of non-usage are used for learning a pattern associated and based upon the learned pattern, the liquid flow is automatically controlled by stopping the liquid flow during expected non-usage periods of time and turning the liquid flow on during expected usage periods of time.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A method of monitoring liquid flow comprising:
monitoring liquid flow, including the pressure of the liquid, through a slave analyzer device; measuring the pressure of the liquid; detecting periods of usage and periods of non-usage of the liquid through the measured pressure; learning a pattern associated with the periods of usage and the periods of non-usage; based upon the learned pattern, automatically controlling the liquid flow by stopping the liquid flow during expected non-usage periods of time and turning the liquid flow on during expected usage periods of time.
2 . The method of monitoring liquid flow, as recited in claim 1 , wherein slave analyzer devices located remotely to one another and to a master analyzer device controlling liquid flow of different locations independently of one another.
3 . The method of monitoring liquid flow, as recited in claim 1 , further including learning, through passage of time, time periods of liquid usage and time periods of liquid non-usage.
4 . The method of monitoring liquid flow, as recited in claim 1 , further including detecting time periods of usage and time periods of non-usage of the liquid through the measured pressure and learning a pattern associated with the time periods of usage and the time periods of non-usage, wherein the automatically controlling the liquid flow is based upon the learned pattern.
5 . The method of monitoring liquid flow, as recited in claim 1 , further including creating a statistical model of the usage.
6 . The method of monitoring liquid flow, as recited in claim 5 , wherein the statistical model is created for each zone of usage.
7 . The method of monitoring liquid flow, as recited in claim 5 , wherein based on the statistical model, detecting an existing leak based on a degree of confidence.
8 . The method of monitoring liquid flow, as recited in claim 7 , further including alerting a user of the existing leak upon the degree of confidence surpassing a threshold level.
9 . The method of monitoring liquid flow, as recited in claim 8 , wherein providing data supporting the existing leak to the user.
10 . The method of monitoring liquid flow, as recited in claim 9 , further including storing the data in non-volatile memory.
11 . The method of monitoring liquid flow, as recited in claim 5 , further including calculating the degree of confidence using Bayes' theorem.
12 . The method of monitoring liquid flow, as recited in claim 5 , as recited in claim 5 , using conditional probabilities to false alarms.
13 . The method of monitoring liquid flow, as recited in claim 5 , further including determining by, where a probability of a leak is a probability of having a leak over a probability of not having a leak, i.e. P(A/B), is equal to the probability of not having a leak divided by the probability of having a leak, i.e. P(B/A) times the probability of having a leak, i.e. P(A), divided by the probability of not having a leak, i.e. P(B), as expressed by
P ( A/B )=( P ( B/A ) P ( A ))/ P ( B ).
14 . The method of monitoring liquid flow, as recited in claim 1 , wherein the usage is continually updated over time.
15 . The method of monitoring liquid flow, as recited in claim 1 , further including iteratively checking for leaks to determine an actual leak rate over time and filter non-human usage random abnormality events from actual leak events.Join the waitlist — get patent alerts
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