Detection of pump cavitation/blockage and seal failure via current signature analysis
First Claim
1. A system for monitoring the condition of a pump driven by a motor, comprising:
- a sensor operatively coupled to a power lead of the motor, the sensor obtains at least one current signal relating to the operation of the pump; and
a one-shot unsupervised artificial neural network operatively coupled to the sensor, the artificial neural network detects at least one fault relating to the operation of the pump from the at least one current signal.
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Accused Products
Abstract
A system and method is provided for monitoring the operating condition of a pump by evaluating fault data encoded in the instantaneous current of the motor driving the pump. The data is converted to a frequency spectrum which is analyzed to create a fault signature having fault attributes relating to various fault conditions associated with the pump. The fault signature is then input to a neural network that operates in conjunction with a preprocessing and post processing module to perform decisions and output those decisions to a user interface. A stand alone module is also provided that includes an adaptive preprocessing module, a one-shot unsupervised neural network and a fuzzy based expert system to provide a decision making module that operates with limited human supervision.
63 Citations
33 Claims
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1. A system for monitoring the condition of a pump driven by a motor, comprising:
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a sensor operatively coupled to a power lead of the motor, the sensor obtains at least one current signal relating to the operation of the pump; and
a one-shot unsupervised artificial neural network operatively coupled to the sensor, the artificial neural network detects at least one fault relating to the operation of the pump from the at least one current signal. - View Dependent Claims (2, 5, 6)
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- 3. The system of claim 3, further including a processor operatively coupled to the sensor, the processor adapted to generate fast fourier transforms of the at least one current signal.
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7. A method for monitoring the condition of a pump driven by a motor, comprising the steps of:
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collecting a first sample of current data signal relating to the operation of the pump;
inputting the first sample of current data signal to a one-shot unsupervised artificial neural network, collecting a second sample of current data signal relating to the operation of the pump; and
inputting the second sample of current data signal to the one-shot unsupervised artificial neural network, wherein any differences between the first signal and the second signal will be generated as a change in condition signal by the one-shot unsupervised artificial neural network, any change of condition signal representing a pump fault condition. - View Dependent Claims (8, 9, 10, 11, 12, 13, 14)
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15. A stand alone decision module that receives a current signal from a machine and facilitates diagnosing the state of the machine by determining if the current signal contains fault data relating to the state of the machine, the decision module comprising:
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a neural network operatively coupled to a sensor, the neural network synthesizes a change in condition signal from the sampled current data;
a preprocessing portion operatively coupled to the neural network, the preprocessing portion conditions the current signal prior to inputting the current signal into the neural network; and
a post processing portion operatively coupled to the neural network, the post processing portion determines whether the change in condition signal is due to a fault condition related to the state of the machine. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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22. A system for simultaneously monitoring the condition of a pump driven by a motor and the condition of the motor driving the pump, comprising:
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a sensor operatively coupled to a power source of the motor, the sensor obtains at least one current signal relating to the operation of the pump and the operation of the motor; and
a one-shot unsupervised artificial neural network operatively coupled to the sensor, the one-shot unsupervised artificial neural network detects at least one fault relating to the operation of the pump and at least one fault relating to the operation of the motor from the at least one current signal. - View Dependent Claims (23)
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24. A system for diagnosing a plurality of pumps, each driven by a motor, comprising:
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a plurality of sensors for obtaining current data signals from each motor, a channel interface operatively coupled to the plurality of sensors, the channel interface designating a separate channel for each of the plurality of sensors; and
a host computer operatively coupled to the channel interface, the host computer including a neural network operatively coupled to each channel of the channel interface, the neural network detects at least one fault relating to the operation of the plurality of pumps from the current data signals, wherein a processor of the host computer cycles through each of the channels, the processor performing classical signature analysis on each of the plurality of pumps using the current data signal for each respective pump.
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25. A system for monitoring the condition of a pump driven by a motor, comprising:
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means for detecting at least one current signal from the motor, said at least one current signal containing fault attributes related to the condition of the pump;
means for extracting the fault attributes from the at least one current signal;
means for determining if the fault attributes signify a fault condition of the pump; and
means for communicating any fault conditions to a system operator. - View Dependent Claims (26, 27)
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28. A system for monitoring the condition of a pump driven by a motor, comprising:
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a sensor operatively coupled to a power lead of the motor, the sensor obtains at least one current signal relating to the operation of the pump;
a processor operatively coupled to the sensor, the processor converts the at least one current signal to a frequency spectrum having a plurality of fault attributes related to the condition of the pump and preprocess the fault attributes;
an unsupervised artificial neural network operatively coupled to the processor, the artificial neural network recognizes and detects changes in the plurality of preprocessed fault attributes and provides a change of condition pattern relating to changes in the plurality of preprocessed fault attributes; and
a post processor invading decision making rules for determining fault conditions of the pump based on the change of condition pattern, the post processor communicating any fault conditions to a system operator. - View Dependent Claims (29, 30, 31, 32, 33)
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Specification