IP Library › Granted Patent US 12,370,720
Granted Patent B2
US 12,370,720 · App. 18/402,970 · Granted Jul 29, 2025

Concrete sensor system

Inventors: Bryan S. Datema (Rochester, MN); Cody D. Clifton (Oshkosh, WI); Jarrod M. Vagle (Oshkosh, WI); Xiang Gong (Oshkosh, WI); Zhenyi Wei (Oshkosh, WI)
Assignee: Oshkosh Corporation
B28C5/422B28C5/4234B28C7/024B28C7/026B28C7/028G01N33/383G01P1/023G01P3/44G01P15/02B28C5/4272
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 12,370,720
App. No.
18/402,970
Granted
Jul 29, 2025
Kind
B2
Abstract

A mixer vehicle includes a mixer drum, a first acceleration sensor, a second acceleration sensor, and a controller. The first acceleration sensor is configured to produce first acceleration signals and the second acceleration sensor is configured to measure accelerations within the mixer drum to produce second acceleration signals. The controller is configured to receive the first acceleration signals from the first acceleration sensor and second acceleration signals from the second acceleration sensor. The controller is further configured to determine a presence of material within the mixer drum based on the first acceleration signals and the second acceleration signals. The controller is further configured to determine one or more properties of the material within the mixer drum based on the first acceleration signals and the second acceleration signals.

Claims (40)

1. A mixer vehicle comprising:

a mixer drum;

a first sensor and a second sensor, wherein the first sensor is outside the mixer drum and is configured to produce baseline signals, and wherein the second sensor is within the mixer drum such that the second sensor produces disturbed signals; and

processing circuitry configured to:

obtain the baseline signals and the disturbed signals from the first sensor and the second sensor as the mixer drum rotates;

determine an amount of noise in the disturbed signals relative to the baseline signals using a comparison between the baseline signals and the disturbed signals; and

use the amount of noise in the disturbed signals to determine a presence of material and one or more properties of the material within the mixer drum.

2. The mixer vehicle of claim 1 , wherein the one or more properties include a degree of homogeneity of the material, a slump of the material, and a consistency of the material.

3. The mixer vehicle of claim 2 , wherein the processing circuitry is further configured to:

determine the slump of the material based on an amount of noise in the disturbed signals using an empirical relationship that defines slump of the material as a function of the amount of noise; and

use the consistency of the material to determine whether water should be added to or removed from the material.

4. The mixer vehicle of claim 1 , wherein using the amount of noise in the disturbed signals to determine the presence of the material comprises determining the presence of material based on a signal to noise ratio of the disturbed signals.

5. The mixer vehicle of claim 1 , wherein the processing circuitry is further configured to determine an entry angle and an exit angle of the material within the mixer drum based on the baseline signals and the disturbed signals.

6. The mixer vehicle of claim 5 , wherein the processing circuitry is further configured to determine any of a volume, and a weight based on the entry angle and the exit angle of the material.

7. The mixer vehicle of claim 6 , wherein the processing circuitry is further configured to validate the weight of the material within the mixer drum by comparing the weight determined based on the entry angle and the exit angle of the material to a weight determined by a concrete buildup algorithm.

8. The mixer vehicle of claim 6 , wherein the processing circuitry is further configured to use the weight of the material to adjust an operation of one or more systems or devices of the mixer vehicle.

9. The mixer vehicle of claim 1 , wherein the second sensor is positioned inside of the mixer drum and passes through the material as the mixer drum rotates, the second sensor producing the disturbed signals as a result of passing through the material.

10. The mixer vehicle of claim 1 , wherein the processing circuitry is further configured to determine at least one of an orientation and an angular speed of the mixer drum based on at least one of the baseline signals and the disturbed signals.

11. The mixer vehicle of claim 10 , wherein the processing circuitry is further configured to automatically adjust an orientation of the mixer drum based on the orientation such that a solar panel disposed on the mixer drum points in an upwards direction.

12. The mixer vehicle of claim 1 , wherein the first sensor and the second sensor are positioned on a probe, wherein the probe comprises a urethane cover.

13. A sensing system for a concrete mixer vehicle, the sensing system comprising processing circuitry configured to:

obtain baseline signals from a first sensor and disturbed signals from a second sensor, wherein the first sensor is positioned outside a mixer drum of the concrete mixer vehicle and the second sensor is positioned within the mixer drum of the concrete mixer vehicle and produces the disturbed signals;

determine an amount of noise in the disturbed signals relative to the baseline signals based on a comparison between the baseline signals and the disturbed signals; and

use the amount of noise in the disturbed signals to determine a presence of material and one or more properties of the material within the mixer drum.

14. The sensing system of claim 13 , wherein the one or more properties include a degree of homogeneity of the material, a slump of the material, and a consistency of the material.

15. The sensing system of claim 14 , wherein the processing circuitry is further configured to:

determine the slump of the material based on an amount of noise in the disturbed signals using an empirical relationship that defines a slump of the material as a function of the amount of noise; and

use the consistency of the material to determine whether water should be added to or removed from the material.

16. The sensing system of claim 13 , wherein using the amount of noise in the disturbed signals to determine the presence of the material comprises determining the presence of material based on a signal to noise ratio of the disturbed signals.

17. The sensing system of claim 13 , wherein the processing circuitry is further configured to determine:

an entry angle and an exit angle of the material within the mixer drum based on the baseline signals and the disturbed signals; and

any of a volume or a weight based on the entry angle and the exit angle of the material within the mixer drum.

18. The sensing system of claim 13 , wherein the second sensor is positioned inside of the mixer drum and passes through the material as the mixer drum rotates, the second sensor producing the disturbed signals as a result of passing through the material; and

wherein the first sensor is positioned outside of the mixer drum.

19. A method for determining a slump of a material within a concrete mixer drum, the method comprising:

providing a first sensor and a second sensor on a probe that extends into the concrete mixer drum, wherein the first sensor is disposed outside of the concrete mixer drum and is configured to produce baseline signals as the concrete mixer drum rotates, and the second sensor is disposed within the concrete mixer drum on the probe and is configured to produce disturbed signals as the concrete mixer drum rotates and the probe passes through the material;

determining an indication of an amount of noise in the disturbed signals based on a comparison of the baseline signals and the disturbed signals; and

using the amount of noise in the disturbed signals to estimate the slump of the material within the concrete mixer drum.

20. The method of claim 19 , further comprising:

adjusting an operation of the concrete mixer drum using the slump of the material within the concrete mixer drum.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 3, 2024
From: CLIFTON, CODY D.; DATEMA, BRYAN S.; WEI, ZHENYI; GONG, XIANG; VAGLE, JERROD M.
To: OSHKOSH CORPORATION
Reel/Frame 066008/0345 →
Continuity (4)
Continuation 18074899 · Dec 5, 2022
Continuation 16743784 · Jan 15, 2020
Provisional Application 62793680 · Jan 17, 2019
Related Publication 20240181677A1 · Jun 6, 2024
References Cited (79)
US 4114193A · Hudelmaier · 1978 [cited by applicant]
US 5752768A · Assh · 1998 [cited by applicant]
US 5948970A · Te'eni · 1999 [cited by applicant]
US 6484079B2 · Buckelew et al. · 2002 [cited by applicant]
US 7578379B2 · Gillmore et al. · 2009 [cited by applicant]
US 7648015B2 · Gillmore et al. · 2010 [cited by applicant]
US 7931397B2 · Lindblom et al. · 2011 [cited by applicant]
US 8287173B2 · Khouri · 2012 [cited by applicant]
US 8613543B2 · Lindblom et al. · 2013 [cited by applicant]
US 8646965B2 · Datema et al. · 2014 [cited by applicant]
US 8727604B2 · Compton et al. · 2014 [cited by applicant]
US 8858061B2 · Berman · 2014 [cited by applicant]
US D737866S · Datema et al. · 2015 [cited by applicant]
US 9199391B2 · Beaupre et al. · 2015 [cited by applicant]
US D772306S · Datema et al. · 2016 [cited by applicant]
US 9694671B2 · Wildgrube et al. · 2017 [cited by applicant]
US 9952246B2 · Jordan et al. · 2018 [cited by applicant]
US 10156547B2 · Biesak et al. · 2018 [cited by applicant]
US 10239403B2 · Broker et al. · 2019 [cited by applicant]
US 10414067B2 · Datema et al. · 2019 [cited by applicant]
US 10792613B1 · Drake et al. · 2020 [cited by applicant]
US 10843379B2 · Rocholl et al. · 2020 [cited by applicant]
US 10901409B2 · Datema et al. · 2021 [cited by applicant]
US 11273575B2 · Roberts et al. · 2022 [cited by applicant]
US 11385153B2 · Roberts et al. · 2022 [cited by applicant]
US 11897167B2 · Datema · 2024 [cited by examiner]
US 12017381B2 · Datema · 2024 [cited by examiner]
US 20080205188A1 · Lindblom et al. · 2008 [cited by applicant]
US 20090050438A1 · Gillmore et al. · 2009 [cited by applicant]
US 20090050439A1 · Gillmore et al. · 2009 [cited by applicant]
US 20090154287A1 · Lindblom et al. · 2009 [cited by applicant]
US 20090171595A1 · Bonilla Benegas · 2009 [cited by applicant]
US 20110058446A1 · Khouri · 2011 [cited by applicant]
US 20130107656A1 · Datema et al. · 2013 [cited by applicant]
US 20150078417A1 · Verdino · 2015 [cited by applicant]
US 20150142362A1 · Jordan · 2015 [cited by examiner]
US 20150159564A1 · Wildgrube et al. · 2015 [cited by applicant]
US 20150246331A1 · Broker et al. · 2015 [cited by applicant]
US 20150355160A1 · Berman · 2015 [cited by applicant]
US 20160018383A1 · Radjy · 2016 [cited by applicant]
US 20170028586A1 · Jordan · 2017 [cited by examiner]
US 20170080600A1 · Dickerman · 2017 [cited by examiner]
US 20170108421A1 · Beaupre et al. · 2017 [cited by applicant]
US 20170297425A1 · Wildgrube et al. · 2017 [cited by applicant]
US 20170361491A1 · Datema et al. · 2017 [cited by applicant]
US 20170361492A1 · Datema et al. · 2017 [cited by applicant]
US 20170370898A1 · Radjy et al. · 2017 [cited by applicant]
US 20180250847A1 · Wurtz et al. · 2018 [cited by applicant]
US 20190091890A1 · Rocholl et al. · 2019 [cited by applicant]
US 20190121353A1 · Datema et al. · 2019 [cited by applicant]
US 20190126510A1 · Roberts · 2019 [cited by examiner]
US 20190217698A1 · Broker et al. · 2019 [cited by applicant]
US 20190325220A1 · Wildgrube et al. · 2019 [cited by applicant]
US 20190344475A1 · Datema et al. · 2019 [cited by applicant]
US 20200078986A1 · Clifton et al. · 2020 [cited by applicant]
US 20200094671A1 · Wildgrube et al. · 2020 [cited by applicant]
US 20200217833A1 · Davis et al. · 2020 [cited by applicant]
US 20200225258A1 · Beaupre · 2020 [cited by examiner]
US 20200230841A1 · Datema et al. · 2020 [cited by applicant]
US 20200230842A1 · Datema et al. · 2020 [cited by applicant]
US 20200289985A1 · Drake et al. · 2020 [cited by applicant]
US 20210001765A1 · Beaupre et al. · 2021 [cited by applicant]
US 20210031649A1 · Messina et al. · 2021 [cited by applicant]
US 20210039719A1 · Datema et al. · 2021 [cited by applicant]
US 20210237311A1 · Datema · 2021 [cited by examiner]
US 20210333187A1 · Roberts · 2021 [cited by examiner]
US 20240300143A1 · Datema · 2024 [cited by examiner]
CA 2725887A1 · 2009 [cited by applicant]
CA 2896786A1 · 2014 [cited by applicant]
EP 2296854A2 · 2011 [cited by applicant]
EP 2943321A2 · 2015 [cited by applicant]
EP 2977163A1 · 2016 [cited by applicant]
ES 2281267A1 · 2007 [cited by applicant]
JP 2004154996A · 2004 [cited by applicant]
JP 2014004769A · 2014 [cited by applicant]
WO WO2009144523A2 · 2009 [cited by applicant]
WO WO2014108798A2 · 2014 [cited by applicant]
U.S. Appl. No. 61/751,663. [cited by applicant]
Luu L, Dinh A. “Artifact Noise Removal Techniques on Seismocardiogram Using Two Tri-Axial Accelerometers”. Sensors (Basel). Apr. 2, 2018; 18(4):1067. (Year: 2018). [cited by applicant]