1. A high pressure transducer comprising:
a supply inlet configured to provide a gas supply to the high pressure transducer at a variable supply pressure, wherein the variable supply pressure is greater than or equal to 750PSI;
a pressure divider section comprising a ratio piston assembly having a lower small area piston and an upper large area piston, coupled to the supply inlet and configured to reduce the variable supply pressure, by a fixed ratio equal to a ratio of the diameter of the lower small area piston to the diameter of the upper large area piston, and wherein the reduced pressure is variable, proportional to the variable supply pressure, and less than or equal to 200PSI;
a low pressure control section coupled to the pressure divider section, the low pressure control section comprising at least one pair of feed and bleed valves, the low pressure control section configured to receive the reduced pressure gas from the pressure divider section and to vary the pressure to produce a variable control pressure;
an amplifying section coupled to the low pressure control section and coupled to a main supply valve, wherein the low pressure control section actuates the amplifying section in response to the variable control pressure, the amplifying section configured to control the main supply valve to produce an output pressure that is a multiple of the variable control pressure by modulating the variable input pressure applied to the main supply valve; and
an electrical feedback control circuit having a first pressure sensor for monitoring pressure in the pressure divider section and a second pressure sensor for monitoring output pressure in the amplifying section, the feedback control circuit configured to control the low pressure control section as a function of the pressure in the pressure divider section, the pressure in the amplifying section, and a control signal.
2. A high pressure transducer according to claim 1, wherein the amplifying section comprises a multiplying ratio piston assembly configured to modulate the output pressure of the supply valve based on the variable control pressure.
3. A high pressure transducer according to claim 1, wherein the pressure divider section comprises a flapper nozzle valve configured to control output of the pressure divider section.
4. A high pressure transducer according to claim 3, wherein the flapper nozzle valve comprises a flapper column configured to act as a force limiter.
5. A high pressure transducer according to claim 1, wherein the electrical feedback control circuit further comprises a pulse width modulated controller which controls the low pressure control section as a function of at least one of the pressure in the pressure divider section, pressure in the amplifying section, and a control signal.
6. A method for controlling a high pressure transducer, comprising the steps of:
providing a gas supply at a variable supply pressure through a supply inlet to the high pressure transducer, wherein the variable supply pressure is greater than or equal to 750PSI;
receiving the gas supply at a pressure divider section coupled to the supply inlet, the pressure divider section comprising a ratio piston assembly having a lower small area piston and an upper large area piston, the pressure divider section configured to reduce the variable supply pressure by a fixed ratio equal to the ratio of the diameter of the lower small area piston to the diameter of the upper large area piston, and wherein the reduced pressure is variable, proportional to the variable supply pressure, and less than or equal to 200PSI;
supplying a low pressure control section which is coupled to the pressure divider section with the reduced pressure gas, wherein the low pressure control section comprises at least one pair of feed and bleed valves configured to receive the low pressure gas from the pressure divider and to vary the reduced pressure to produce a variable control pressure output;
transporting the variable control pressure output of the low pressure control section to an amplifying section which is coupled to the low pressure control section and coupled to a main supply valve, the amplifying section configured to be actuated by the low pressure control section in response to the variable control pressure;
controlling the main supply valve to produce an output pressure through the main supply valve that is a multiple of the variable control pressure, by modulating the variable input pressure applied to the main supply valve, wherein the amplifying section controls the main supply valve;
receiving, by a control circuit, a first sensor signal from a first pressure sensor configured to monitor the pressure in the pressure divider section;
receiving, by the control circuit, a second sensor signal from a second pressure sensor configured to monitor the pressure in the amplifying section;
determining, by the control circuit, control signals configured to control the feed and bleed valves based at least in part on the first and second sensor signals; and
transmitting, by the control circuit, the control signals to the feed and bleed valves.
7. A method according to claim 6, wherein the amplifying section of the transporting step comprises a multiplying ratio piston assembly configured to modulate the output pressure of the supply valve based on the variable control pressure.
8. A high pressure transducer comprising:
a supply inlet configured to provide a gas supply to the high pressure transducer at a variable supply pressure, wherein the variable supply pressure is greater than or equal to 750PSI;
a pressure divider section comprising a ratio piston assembly having a lower small area piston and an upper large area piston, coupled to the supply inlet and configured to reduce the variable supply pressure by a fixed ratio equal to a ratio of the diameter of the lower small area piston to the diameter of the upper large area piston, and wherein the reduced pressure is variable, proportional to the variable supply pressure, and less than or equal to 200PSI;
a low pressure control section coupled to the pressure divider section, the low pressure control section comprising at least one pair of feed and bleed valves, the low pressure control section configured to receive the reduced pressure gas from the pressure divider section and to vary the pressure to produce a variable control pressure;
an amplifying section coupled to the low pressure control section and coupled to a main supply valve, wherein the low pressure control section actuates the amplifying section in response to the variable control pressure, the amplifying section configured to control the main supply valve to produce an output pressure that is a multiple of the variable control pressure by modulating the variable input pressure applied to the main supply valve; and
an electrical feedback control circuit configured to:
receive a first sensor signal from a first pressure sensor configured to monitor the pressure in the pressure divider section,
receive a second sensor signal from a second pressure sensor configured to monitor the pressure in the amplifying section, and
activate the feed and bleed valves to control the pressure in the low pressure control section and the output pressure of the main supply valve, based at least in part on the first sensor signal and the second sensor signal.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A tool for performing fault detection of a device, the tool comprising:
a database for storing a plurality of measured indicators representative of at least one dynamic condition of the device;
a binarization module for binarizing the measured indicators;
a machine learning data mining module for analyzing the binarized measured indicators and extracting patterns indicative of whether the device has a fault or not, and
a processor for computing a discriminate function using the extracted patterns to detect at least one fault of the device.
2. The tool of claim 1, wherein the machine learning data mining module further performs multi classification of the measured indicators.
3. The tool of claim any of claim 1 or 2, wherein the machine learning data mining module is capable of unsupervised learning.
4. The tool of any of claims 1-3, wherein the measured indicators consist of one or several of the following: a value, type of value, a component, a location, a date, time, and identification of a corresponding sensor.
5. The tool of claim 4, wherein the type of value consists of any of the following: pressure, temperature, amplitude, torque, revolution per minute, tension, wattage, humidity level, density, and chemical content.
6. The tool of any of claims 1-5, wherein the machine learning data mining module comprises a Logical Data Analysis algorithm using a strong pattern generation algorithm.
7. The tool of any of claims 1-6, further comprising at least one of the following: a graphical user interface, a memory or a reporting module.
8. The tool of any of claims 1-7, wherein the processor further computes a diagnostic and a prognostic.
9. A method for performing dynamic fault detection of a device, the method comprising:
storing in a database a plurality of measured indicators representative of at least one dynamic condition of the device;
binarizing by a processor the plurality of measured indicators; and
analyzing iteratively 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 pattern being indicative of whether the device has a fault or not.
10. The method of claim 9, wherein the measured indicators consist of one or several of the following: a value, type of value, a component, a location, a date, time, and identification of a corresponding sensor.
11. The method of claim 10, wherein the type of value consists of any of the following: pressure, temperature, amplitude, torque, revolution per minute, tension, wattage, humidity level, density and chemical content.
12. The method of any of claims 9-11, further comprising at least one of the following: a graphical user interface, a memory or a reporting module.
13. The method of any of claims 9-12, further computing a diagnostic or a prognostic based on the at least one extracted pattern.
14. The method of any of claims 9-13, wherein the machine learning data tool comprises a Logical Analysis Data (LAD) algorithm.
15. The method of claim 14, wherein the LAD algorithm performs classification by means of Mixed Integer Linear Programming (MILP) module.