IP Library Granted Patent US 12,228,596
Granted Patent B2
US 12,228,596 · App. 17/874,484 · Granted Feb 18, 2025

Power quality analysis system and method for monitoring from the outside of multiconductor cables

Inventor: Bo Eskerod Madsen (Østbirk, DK)
Assignee: REMONI A/S
G01R19/2513G01R15/14G01R15/144G01R23/20
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,228,596
App. No.
17/874,484
Granted
Feb 18, 2025
Kind
B2
Abstract

A power quality analysis system is configured to carry out a power quality analysis in an electrical environment. The system comprises one or more power consuming units each electrically connected to a main power supply by a multiconductor (multicore) cable and one or more power quality sensors configured to provide one or more power quality analysis measurements. The one or more power quality sensors are clamp-on power quality sensors configured to provide one or more power quality analysis measurements when the clamp-on power quality sensors are clamped onto the outside of or arranged in the proximity of the multiconductor cable. The clamp-on power quality sensors are configured to provide the one or more power quality analysis measurements without being electrically connected to any of the conductors of the multiconductor cable.

Claims (31)

1. A power quality analysis system for carrying out power quality analysis and detecting power quality distortions in an electrical environment, comprising:

one or more power consuming units each electrically connected to a main power supply by a multiconductor cable that comprises a plurality of conductors insulated from each other;

a plurality of clamp-on power quality sensors configured to provide one or more power quality analysis measurements and to detect power quality distortions when the clamp-on power quality sensors are clamped onto an outside of or arranged in proximity of the multiconductor cable, wherein the clamp-on power quality sensors are not electrically connected to any of the conductors of the multiconductor cable;

wherein each of the clamp-on power quality sensors comprises a plurality of sub-sensors selected from coils, Hall-effect sensors, and/or capacitive probes positioned so that different sub-sensors measure different superpositions of combined electromagnetic fields induced by the conductors of the multiconductor cable;

at least one central power quality unit sensor measuring overall power quality;

a calculation unit adapted to use a mathematical statistical model which combines measurements made by the clamp-on power quality sensors and measurements made by the central power quality unit sensor, the mathematical statistical model comprising:

1) a mathematical function component modelling latent mapping from the central power quality unit sensor measurements onto the clamp-on power quality sensor measurements; and

2) a stochastic component modelling measurement noise and a part of each central power quality unit sensor measurement associated with usage not measured by the clamp-on power quality sensors.

2. The power quality analysis system according to claim 1 , further comprising a time synchronization unit that synchronizes the measurements from the clamp-on power quality sensors and the central power quality unit sensor at a predefined frequency.

3. The power quality analysis system according to claim 1 , wherein the clamp-on power quality sensors measure both the magnetic field and the electric field of the multiconductor cable.

4. The power quality analysis system according to claim 1 , wherein the central power quality unit sensor measures both the magnetic field and the electric field of the multiconductor cable.

5. The power quality analysis system according to claim 1 , wherein at least some of the clamp-on power quality sensors and/or the central power quality unit sensor communicate(s) wirelessly with one or more external devices.

6. The power quality analysis system according to one claim 1 , further comprising one or more energy harvesting devices powering at least some of the clamp-on power quality sensors and/or the central power quality unit sensor.

7. The power quality analysis system according to claim 1 , further comprising one or more energy harvesting devices harvesting energy, measuring voltage in the multiconductor cable, or both.

8. The power quality analysis system according to claim 1 , wherein the central power quality unit sensor pre-analyzes the measured data to reduce data load.

9. A method for carrying out a power quality analysis and detecting power quality distortions in an electrical environment, comprising:

providing a power quality analysis system comprising:

one or more power consuming units each electrically connected to a main power supply by a multiconductor cable that comprises a plurality of conductors insulated from each other;

a plurality of clamp-on power quality sensors configured to provide one or more power quality analysis measurements and to detect power quality distortions when the clamp-on power quality sensors are clamped onto an outside of or arranged in proximity of the multiconductor cable, wherein the clamp-on power quality sensors are not electrically connected to any of the conductors of the multiconductor cable;

wherein each of the clamp-on power quality sensors comprises a plurality of sub-sensors selected from coils, Hall-effect sensors, and/or capacitive probes positioned so that different sub-sensors measure different superpositions of combined electromagnetic fields induced by the conductors of the multiconductor cable;

at least one central power quality unit sensor measuring overall power quality; and

applying a mathematical statistical model which combines measurements made by the clamp-on power quality sensors and measurements made by the central power quality unit sensor, the mathematical statistical model comprising:

1) a mathematical function component modelling latent mapping from the central power quality unit sensor measurements onto the clamp-on power quality sensor measurements; and

2) a stochastic component modelling measurement noise and a part of each central power quality unit sensor measurement associated with usage not measured by the clamp-on power quality sensors.

10. The method according to claim 9 , further comprising synchronizing measurements from the clamp-on power quality sensors and the central power quality unit sensor at a predefined frequency.

11. The method according to claim 9 , wherein the clamp-on power quality sensors measure both the magnetic field and the electric field of the multiconductor cable.

12. The method according to claim 9 , wherein the central power quality unit sensor measure both the magnetic field and the electric field of the multiconductor cable.

13. The method according to claim 9 , wherein at least some of the clamp-on power quality sensors and/or the central power quality unit sensor communicate(s) wirelessly with one or more external devices.

14. The method according to claim 9 , wherein at least some of the clamp-on power quality sensors and/or the central power quality unit sensor is/are powered by at least one energy harvesting device.

15. The method according to claim 14 , wherein the at least one energy harvesting device harvests energy, measures voltage in the multiconductor cable, or both.

16. The method according to claim 9 , further comprising pre-analyzing the data measured by the central power quality unit sensor to reduce data load.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 15, 2022
From: ESKEROD MADSEN, BO
To: REMONI A/S
Reel/Frame 060807/0024 →
Priority Claims (1)
DK PA 2020 00186 · Feb 15, 2020 · national
Continuity (2)
Continuation PCTDK2021050039 · Feb 8, 2021
Related Publication 20220365118A1 · Nov 17, 2022
References Cited (58)
US 5233538A · Wallis · 1993 [cited by applicant]
US 6777953B2 · Blades · 2004 [cited by applicant]
US 6876203B2 · Blades · 2005 [cited by applicant]
US 6882158B2 · Blades · 2005 [cited by applicant]
US 6927579B2 · Blades · 2005 [cited by applicant]
US 7265533B2 · Lightbody et al. · 2007 [cited by applicant]
US 7369950B2 · Wall · 2008 [cited by examiner]
US 8447541B2 · Rada et al. · 2013 [cited by applicant]
US 8659286B2 · Reynolds · 2014 [cited by applicant]
US 8664937B2 · Fisera · 2014 [cited by applicant]
US 8868359B2 · Ganesh et al. · 2014 [cited by applicant]
US 8970206B2 · Cheng et al. · 2015 [cited by applicant]
US 8983670B2 · Shetty et al. · 2015 [cited by applicant]
US 9020769B2 · Rada et al. · 2015 [cited by applicant]
US 9225389B2 · Veronesi et al. · 2015 [cited by applicant]
US 9310401B2 · Tsao et al. · 2016 [cited by applicant]
US 9547026B1 · Chraim et al. · 2017 [cited by applicant]
US 9754329B2 · Lin et al. · 2017 [cited by applicant]
US 9791477B2 · Lorek · 2017 [cited by applicant]
US 10187707B2 · Norwood et al. · 2019 [cited by applicant]
US 10387284B2 · Barbis · 2019 [cited by applicant]
US 10755549B2 · Pop · 2020 [cited by applicant]
US 10761147B2 · Beaudet · 2020 [cited by applicant]
US 10788516B2 · Hui et al. · 2020 [cited by applicant]
US 10859604B2 · Lorek · 2020 [cited by applicant]
US 11175320B2 · Selvaggi · 2021 [cited by applicant]
US 11262386B2 · Donnal et al. · 2022 [cited by applicant]
US 11320467B1 · Aljohani et al. · 2022 [cited by applicant]
US 11358424B2 · Kulkarni et al. · 2022 [cited by applicant]
US 11506546B2 · Blair · 2022 [cited by applicant]
US 20050083206A1 · Couch et al. · 2005 [cited by applicant]
US 20100315092A1 · Nacson · 2010 [cited by examiner]
US 20120001617A1 · Reynolds · 2012 [cited by examiner]
US 20120086433A1 · Cheng et al. · 2012 [cited by applicant]
US 20140320125A1 · Leeb et al. · 2014 [cited by applicant]
US 20140343878A1 · Gudmundsson · 2014 [cited by examiner]
US 20150318686A1 · Hosny et al. · 2015 [cited by applicant]
US 20180088159A1 · Heintzelman et al. · 2018 [cited by applicant]
US 20180106851A1 · Schweitzer, III et al. · 2018 [cited by applicant]
US 20200011909A1 · Bickel · 2020 [cited by examiner]
US 20210080514A1 · Beaudet et al. · 2021 [cited by applicant]
US 20210111561A1 · William · 2021 [cited by applicant]
US 20220376501A1 · Pong et al. · 2022 [cited by applicant]
US 20230030682A1 · Roy et al. · 2023 [cited by applicant]
US 20240085468A1 · Sepulveda Leon et al. · 2024 [cited by applicant]
DE 102016217168A1 · 2018 [cited by applicant]
EP 2618166B1 · 2014 [cited by applicant]
EP 2489987B1 · 2018 [cited by applicant]
EP 1766424B1 · 2018 [cited by applicant]
EP 2518520B1 · 2021 [cited by applicant]
EP 3837559B1 · 2023 [cited by applicant]
EP 4273563A1 · 2023 [cited by applicant]
EP 4030172B1 · 2024 [cited by applicant]
EP 4005047B1 · 2024 [cited by applicant]
WO 2015160779A1 · 2015 [cited by applicant]
WO 2018209436A1 · 2018 [cited by applicant]
WO 2019139540A1 · 2019 [cited by applicant]
WO 23152424A1 · 2023 [cited by applicant]