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公开(公告)号：US12224587B2
公开(公告)日：2025-02-11
申请号：US17656465
申请日：2022-03-25
Inventor： Hongbo Sun , Ashwin Shirsat , Kyeong Jin Kim , Jianlin Guo
Abstract: A computer-implemented method is provided for performing energy disaggregation of a distribution system-level net-load measurements using continuous-point-on-wave (CPOW) measurement units. The method uses a processor coupled with a memory stored instructions implementing the method using neural networks including an encoder network, a feature extractor, a separator network, a decoder network stored in the memory, wherein the instructions, when executed by the processor carry out at steps of the method include generating net-load time series data from voltage and current measurements via the CPOW measurement units, generating a compressed latent space representation from the net-load time series, converting the net-load time series into time-frequency domain, passing time domain cotextual information with the converted time-frequency domain representation of net-load time series to the feature extractor, estimating two weight matrices to be multiplied with an output from the encoder network and learning temporal features of a native load and a photovoltaic (PV) generation, transforming weighted latent representation corresponding the native load and the PV generation into time-domain representations, and predicting the native load and the PV generation at distribution system-level from the transformed time domain representations corresponding to the native load and PV generations.
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2.发明授权公开(公告)号：US12213177B2
公开(公告)日：2025-01-28
申请号：US18507217
申请日：2023-11-13
Inventor： Jianlin Guo , Yukimasa Nagai , Takenori Sumi , Kieran Parsons , Philip Orlik , Pu Wang
IPC: H04W74/0816
Abstract: A computer-executed method is provided for IEEE 802.15.4 devices based on a suspendable carrier-sense multiple access with collision avoidance (CSMA/CA) control program and standard CSMA/CA control program for an IEEE 802.15.4 network composing of IEEE 802.15.4 devices. The computer-executed method is provided on an IEEE 802.15.4 device, and causes a processor of the IEEE 802.15.4 device to perform steps that include determining the permission of backoff suspension and the intention of IEEE 802.15.4 device to perform backoff suspension, selecting the suspendable CSMA/CA control program if the backoff suspension is permitted and IEEE 802.15.4 device intends to perform backoff suspension. The suspendable CSMA/CA control program is configured to perform active CCA within each unit backoff period and suspend backoff if channel is detected to be busy, performing a CCA when backoff completes, transmitting frame when the detected channel status is an idle state or incrementing a number of backoff (NB) when the detected channel status is an busy state, determining if a NB exceeds the macMaxCSMABackoffs, incrementing a number of retransmissions (NR) when a NB exceeds the macMaxCSMABackoffs, and discarding frame when a NR exceeds macMaxFrameRetries.
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公开(公告)号：US20250028873A1
公开(公告)日：2025-01-23
申请号：US18222719
申请日：2023-07-17
Inventor： Hongbo Sun , Anping Zhou
IPC: G06F30/20
Abstract: Disclosed a decision-dependent chance-constrained optimal model for enhancing resilience of power distribution system under renewable generation uncertainty through strategically setting-up and activating dispatchable diesel generators, renewable distributed generations, battery energy storage systems, and switchable devices. By incorporating the information of decision variables, a moment-based ambiguity set is employed to depict the uncertainty arising from renewable distributed generators. By leveraging convex approximations to handle the considered joint chance constraints, the disclosed model is transformed into a tractable mixed-integer second-order conic programming problem to be solved.
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公开(公告)号：US12154194B2
公开(公告)日：2024-11-26
申请号：US16925680
申请日：2020-07-10
Inventor： David Millar , Okan Atalar , Keisuke Kojima , Toshiaki Koike-Akino , Pu Wang , Kieran Parsons
IPC: G06T11/00 , G01B9/02091
Abstract: A method for a target image reconstruction is provided. The method includes emitting stepped frequency waveforms having different constant frequencies at different periods of time, modulating the stepped frequency waveforms into frequency ranges each having a first frequency and a second frequency, wherein each of the stepped frequency waveforms are increased from the first frequency to the second frequency based on a range function, wherein the modulated stepped frequency waveforms are arranged with some sparsity factor. The method further includes transmitting the modulated stepped frequency waveforms to a target and accepting reflection of the modulated stepped frequency waveforms reflected from the target interfering the modulated stepped frequency waveforms and the reflection of the modulated stepped frequency waveforms to produce beat signals of interferences between the modulated stepped frequency waveforms and the reflection of the modulated stepped frequency waveforms, and reconstructing an image of the target from the beat signals.
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公开(公告)号：US20240362457A1
公开(公告)日：2024-10-31
申请号：US18308126
申请日：2023-04-27
Inventor： Pu Wang , Cristian Vaca-Rubio , Toshiaki Koike Akino , Ye Wang , Petros Boufounos
IPC: G06N3/0455 , G05D1/02
CPC classification number: G06N3/0455
Abstract: A system for sensing a state of a device is provided. The system includes an autoencoder comprising an encoder, a latent subnetwork, and an extended decoder. The encoder encodes each input data point of input data from an input state space into a latent space to produce latent data points and propagates the latent data points with a neural Ordinary Differential Equation (ODE) to estimate an initial point of latent dynamics of the device in the latent space. The latent subnetwork propagates the initial point till a time index of interest using the neural ODE to produce a state of latent dynamics of the device at the time index of interest. The extended decoder decodes the state of latent dynamics of the device into an output state space different from the input state space to produce output data including the state of the device at the time index of interest.
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Patent Agency Ranking
公开(公告)号：US12127251B2
公开(公告)日：2024-10-22
申请号：US17321548
申请日：2021-05-17
Inventor： Jianlin Guo , Philip Orlik , Yukimasa Nagai , Takenori Sumi
IPC: H04W74/0816 , H04L1/1829 , H04L1/1867 , H04W84/12
CPC classification number: H04W74/0816 , H04L1/1854 , H04L1/1896 , H04W84/12
Abstract: A wireless smart utility network (Wi-SUN) device is provided for coexistence with a Wi-Fi HaLow network sharing frequency spectra between the networks. The Wi-SUN device includes a receiver receiving packets of neighbor Wi-SUN devices, a memory storing computer executable programs including a hybrid carrier-sense multiple access with collision avoidance (CSMA/CA) control program and Wi-SUN backoff control program, a processor to execute steps of estimating a severity of Wi-Fi HaLow interference based on one or combination of the severity metrics, selecting a CSMA/CA mode between predetermined CSMA/CA modes in response to the estimated severity, detecting a channel status based on the hybrid carrier-sense multiple access, wherein if the channel status is not idle, a maximum limited number of times for re-attempting a packet transmission is checked to determine an allowability of re-attempting the packet transmission, and a transmitter to transmit packets according to a determination result of the allowability.
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公开(公告)号：US20240337735A1
公开(公告)日：2024-10-10
申请号：US18191815
申请日：2023-03-28
Inventor： Joshua Rapp , Alfred Ulvog , Hassan Mansour , Toshiaki Koike-Akino , Petros Boufounos , Kieran Parsons
IPC: G01S7/4911 , G01S7/481 , G01S7/4915 , G01S17/34
CPC classification number: G01S7/4911 , G01S7/4814 , G01S7/4915 , G01S17/34
Abstract: A distance estimation method comprises transmitting a wave of radiation modulated in frequency domain by an emitter to a scene, receiving a reflection of the transmitted wave from the scene, and interfering a copy of the transmitted wave with the received reflection to generate a sequence of samples of the beat signal with wrapped phases in a time domain. The method also comprises estimating a frequency of the beat signal in the time domain in an iterative manner until a termination condition is met. The iterative estimation of the frequency of the beat signal is based on phase unwrapping of the samples of the beat signal subject to correlated phase error derived from phase noise statistics of the emitter and a linear regression fitting the frequency of the beat signal into the unwrapped phases of the beat signal.
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公开(公告)号：US20240322555A1
公开(公告)日：2024-09-26
申请号：US18189529
申请日：2023-03-24
Inventor： Hongbo Sun , Imtiaj Khan , Kyeong Jin Kim , Jianlin Guo
CPC classification number: H02H7/22 , H02H1/0092
Abstract: Disclosed a method and system for identifying an existence, location and type of a weak-signal fault in an islanded inverter-based microgrid. The weak-signal fault includes a high impedance fault, an inverter DC-side short-circuit fault, and an inverter tripping fault, and usually fails to be detected by conventional relay methods due to small magnitude of fault current. Upon received voltage and current measurements from intelligent electronic devices installed in the microgrid, the variation mode decomposition algorithm is firstly applied to detect the existence of fault based on denoised time series of measurements using discrete wavelet transform algorithm. After detecting the presence of fault, the correlation-based matrix is applied to locate the suspicious fault locations, and then K-nearest neighbors model is utilized to identify the faulty branch among those locations using dynamic time warping algorithm to measure the distance between neighbors. Following fault localization, fault classification is done by observing sequence components and phasor measurements and feeding the observational inputs to a fault classification logic circuit model.
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9.发明公开公开(公告)号：US20240310795A1
公开(公告)日：2024-09-19
申请号：US18184065
申请日：2023-03-15
Inventor： Saleh Nabi , Aleksei Sholokhov , Hassan Mansour
IPC: G05B13/02 , G06N3/0455 , G06N3/08
CPC classification number: G05B13/027 , G06N3/0455 , G06N3/08
Abstract: A system and method are provided for training neural network for controlling operation of system having non-linear dynamics represented by partial differential equations (PDEs). The method comprises collecting digital representation of time series data indicative of instances of function space of the system and measurements of state of the operation of the system. Collocation points corresponding to solutions of the PDE are generated. The neural network is trained using training data including the collected time series data and the collocation points to train parameters of non-linear operator. The neural network has autoencoder architecture including encoder to encode each instance of the training data into latent space, the non-linear operator to propagate the encoded instances into the latent space with transformation determined by parameters of the non-linear operator, and decoder to decode the transformed encoded instances of the training data to minimize a hybrid loss function.
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公开(公告)号：US20240304205A1
公开(公告)日：2024-09-12
申请号：US18224659
申请日：2023-07-21
Inventor： Aswin Shanmugam Subramanian , Christoph Böddeker , Gordon Wichern , Jonathan Le Roux
IPC: G10L21/0272 , G10L15/26 , G10L25/78
CPC classification number: G10L21/0272 , G10L15/26 , G10L25/78
Abstract: A system and method for sound processing for performing multi-talker conversation analysis is provided. The sound processing system includes a deep neural network trained for processing audio segments of an audio mixture of the multi-talker conversation. The deep neural network includes a speaker-independent layer that produces a speaker-independent output, and a speaker-biased layer applied once independently to each of the audio segments for each multiple speakers of the audio mixture. The deep neural network also processes a time-invariant embedding by individually assigning each application of the speaker-biased layer to a corresponding speaker by inputting the corresponding time-invariant speaker embedding. The deep neural network thus produces data indicative of time-frequency activity regions of each speaker of the multiple speakers in the audio mixture from a combination of speaker-biased outputs.
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