Mitsubishi Electric Research Laboratories, Inc.

Mitsubishi Electric Corporation

Jianlin Guo

Philip Orlik

Kieran Parsons

Kyeong Jin Kim

Yukimasa Nagai

Jinyun Zhang

Takenori Sumi

Ghulam Bhatti

Raymond Yim

Chunjie Duan

Stefano Di Cairano

Yebin Wang

Hongbo Sun

Pu Wang

Heejin Ahn

Frederick J Igo, Jr

Yehan Ma

Evripidis Paraskevas

Koon Hoo Teo

Toshiaki Koike-Akino

Zafer Sahinoglu

Karl Berntorp

Zhifeng Tao

Ye Wang

Ankush Chakrabarty

Marcel Menner

Toshiaki Koike Akino

Kyeong-Jin Kim

Kyeongjin Kim

Kaikai Liu

Fei Ye

Chuan Han

Shengyi Wang

Shuai Wang

Ashwin Shirsat

Ferdous Pervej

Hao Song

Bryan Liu

Imtiaj Khan

Gilsoo Lee

Ying Liu

Daoud Burghal

Xin Yang

Ke Xu

Jie Liu

Disclosed is 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.

Weak-signal fault identification of inverter-based microgrids

A computer-implemented method is provided for training a global machine learning model using a learning server and a set of vehicle agents connected to roadside units (RSUs). It involves selecting agents, associating them with RSUs based on proximity, and transmitting training data and deadlines. Agents train models locally, which are then aggregated through RSUs to refine the global model to desired precision. The method includes steps of selecting vehicle agents from a pool of the vehicle agents connected to the RSUs, associating the selected vehicle agents and the RSUs respectively based on distances from the selected vehicle agents to the RSUs configured to provide measurements of the distances to the learning server, and transmitting a global model, a selected agent set and deadline thresholds in each global training round to the RSUs configured to transmit the global model and training deadlines to the selected vehicle agents.

Communication and computation aware distributed machine learning for vehicular networks

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.

Suspendable CSMA/CA for IEEE 802.15.4 system to reduce packet discard caused by backoff failure

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.

Extraction of instantaneous renewable generation from net load measurements of power distribution systems

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.

Hybrid carrier sense multiple access system with collision avoidance for IEEE 802.15.4 to achieve better coexistence with IEEE 802.11

A computer-implemented method is provided for discovering heterogenous neighbors in coexisting IoT networks including at least one Wi-Fi device and at least one of Zigbee coordinators, ZigBee routers and ZigBee end devices. The method includes generating a broadcast packet such that the broadcast packet emulates a ZigBee broadcast frame, transmitting the emulated broadcast packet using a transceiver of the at least one Wi-Fi device according to cross-technology communication (CTC) method, wherein the emulated broadcast packet is configured to trigger the at least one of the Zigbee coordinators and ZigBee routers having received the emulated broadcast packet to rebroadcast the received packet. The method also includes generating a unicast packet such that the unicast packet emulates a ZigBee address request frame, transmitting the emulated unicast packet using a transceiver of the at least one Wi-Fi device according to cross-technology communication (CTC) method, wherein the emulated unicast packet is configured to trigger the at least one of the Zigbee coordinators, ZigBee routers and ZigBee end devices having received the emulated unicast packet to respond with a ZigBee address response frame, and determining the at least one ZigBee end device to be a neighbor of the at least one Wi-Fi device if the scanned address response frame is transmitted by the at least one ZigBee end device.

Active cross-technology neighbor discovery

A method for semi-persistent scheduling (SPS) based resource allocation in a private 5G network comprises receiving location data of a plurality of user equipment (UEs) in the private 5G network in a last subframe of respective current communication periods of the UEs and determining distance distribution of the UEs in a subsequent communication period of a candidate UE of the plurality of UEs, based on the respective location data of the UEs. The method further comprises determining signal to noise ratio expectation of the UEs for the subsequent communication period, solving an optimization problem optimizing an expectation of data to be carried by each of the one or more SPS channels in the subsequent communication period, to obtain scheduling result for each of the one or more SPS channels and generating resource allocation data for the candidate UE based on the scheduling result.

Systems, apparatuses, and methods for semi-persistent scheduling in communication networks

A computer-implemented pre-processed time-delay autoencoder based anomaly detection method are provided for detecting anomalous states of machines arranged in a factory automation (FA) system or a manufacturing production line. The method includes acquiring source signals from the machines via an interface performing a data pre-processing process for the acquired source signals by normalizing value ranges of the acquired source signals and filtering undesired features from the acquired source signals performing a time-delayed data reform process for the pre-processed source signals based on a time-delay window to generate pre-processed time-delay data submitting pre-processed time-delay testing data to a pre-processed time-delayed autoencoder (Prep-TDAE) neural network, wherein the pre-processed time-delay testing data are collected online while the machines are operated, wherein the Prep-TDAE neural network has been pre-trained by using the pre-processed time-delay training data detecting, if an anomaly state is encountered with respect to the machines, by computing anomaly scores of the pre-processed time-delay testing data, and determining, when the anomaly state is detected, anomaly occurrence time, duration and severity with respect to the anomaly state of each of the machines.

Anomaly detection and diagnosis in factory automation system using pre-processed time-delay neural network with loss function adaptation

A method for communication between a communication device and a base station in a private 5G network where the communication device and the base station have a base period of transmission defined there between as a minimal scheduling period, comprises transmitting location data of the communication device in a last subframe of a current communication period of the communication device. The method further comprises receiving resource allocation data including a transmission period widening factor for one or more subsequent communication periods of the communication device and computing a semi-persistent scheduling (SPS) period as a subsequent communication period of the one or more subsequent communication periods, based on the transmission period widening factor and the base period of transmission. Uplink communication is performed in the one or more subsequent periods, based on the resource allocation data and the SPS period.

A computer-executed method is provided for IEEE 802.15.4 devices based on an active carrier sense based carrier-sense multiple access with collision avoidance (ACS-CSMA/CA) control program and standard CSMA/CA control program for coexistence of an IEEE 802.15.4 network composing of IEEE 802.15.4 devices and IEEE 802.11 network composing of IEEE 802.11 devices sharing frequency spectra between the networks. 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 estimating a severity of IEEE 802.11 interference based on a severity estimation metric, selecting the ACS-CSMA/CA control program based on the estimated severity. The ACS-CSMA/CA control program is configured to perform dynamically updating a maximum number of backoffs (macMaxCSMABackoffs) based on the estimated severity,cdetermining if a number of backoffs (NB) exceeds the updated macMaxCSMABackoffs, performing consecutive CCA operation to continuously detect channel status, and transmitting frames when the detected channel status is an idle state or incrementing number of retransmissions (NR) when the detected channel status is a busy state.

System and method for active carrier sense based CSMA/CA for IEEE 802.15.4 system to avoid packet discard caused by interference

A wireless smart utility network (Wi-SUN) device participating in a Wi-SUN network for coexistence with a Wi-Fi HaLow network sharing frequency spectra between the networks is provided. The Wi-SUN device includes a receiver to receive packets of neighbor Wi-SUN devices, a memory configured to store 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 configured to execute the hybrid CSMA/CA control program including instructions that 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.

A node device for forming a multi-hop network is provided. The node device is configured to avoid interference from coexisting interfering networks and includes a transceiver configured to receive and transmit data with respect to a Destination Oriented Directed Acyclic Graph (DODAG) Information Object message (DIO message), a memory configured to store computer executable programs including an interfered-node count (IC), single-rate link count (SLC), multi-rate link count (MLC), hop count (HP), path communication latency (PCL) and an interference efficient and multi-rate supported routing program CoM-RPL, and a processor configured to perform steps of the computer executable programs. The steps include determining if the received DIO message indicates a new DODAG or an existing DODAG. In this case, if a determined result in the determining indicates the new DODAG and no single-rate link and no interfered node on a path of multi-hop network, the node device joins DODAG network and the processor selects a sender of the DIO message as a default parent, computes a rank for itself, updates DIO message with its rank, IC, SLC, TRM, HP, PCL and transmits scheduled DIO messages based on transmission rate mode.

Routing data in wireless network that coexists with interfering wireless networks

A system for a region including a processor to receive data including weather and component data. Generate a dataset for the region to identify weather events and a plurality of model forcings converted into tabular form. A machine learning (ML) model for each model forcing for each component uses dataset. Iteratively, for each weather event: identify for each component a corresponding model forcing with weather variables. Generate an output value for ML model corresponding to the identified components to the set of weather variables and update ML model. Receive observed data over time periods of an impending weather (IW) event. Iteratively, for each time period: identify, for each component a corresponding model forcing with weather variables and update ML model. Generate for the updated ML model, an output value predicting a component status as a failed or not failed for the time period.

Weather-related overhead distribution line failures online forecasting

A traffic control system for controlling traffic at interconnected intersections is provided, where the system comprises a receiver that receives traffic data that indicates states of vehicles approaching an intersection of the interconnected intersections and directions of the vehicles exiting the intersection. Further, the system comprises a processor that determines intersection crossing times and velocities of vehicles approaching the intersection by minimizing at least one of a total travel time or a maximum travel time of the vehicles for crossing the intersection. The contribution of each vehicle of the vehicles approaching the intersection in the at least one of a total travel time or a maximum travel time is weighted based on directions of the vehicles and traffic at next intersection. Further, the system comprises a transmitter that transmits the intersection crossing times and velocities to the vehicles exiting the intersection for controlling the traffic at the interconnected intersections.

Adaptive control of vehicular traffic

Growing community of inventors

Newton, MA, United States of America

Jianlin Guo