DETAILED ACTION
Specification
The disclosure (specification) is objected to because the following paragraphs are unclear. Going forward with examination, the following specification paragraphs are interpreted to be (Note that in applicant’s response, where a change is requested in the specification, an entire paragraph of the specification containing the change will be needed):
--[0026] In general, the present subject matter is directed to systems and methods for detecting bearing failures for disk gang assemblies of an agricultural implement. In several embodiments, a computing system may be configured to monitor a parameter associated with one or more bearings of a disk gang assembly that varies as a function of a condition of the bearing(s), thereby allowing the computing system to determine or infer when the bearing(s) is experiencing a bearing failure condition. For instance, in one embodiment, the monitored “bearing-related parameter” may be a load on the bearing(s), where the computing system is configured to analyze bearing load data associated with the monitored bearing-related parameter to determine when the bearing(s) are experiencing the bearing failure condition (e.g., when the bearing(s) has one or more points of sticking). For example, the computing system may perform a spectral analysis technique (e.g., Fourier transform) on the load data to more easily identify when the bearing(s) is experiencing the bearing failure condition. When the magnitude of the load on the bearing(s) at the rotational frequency of the disk gang assembly (or multiple(s) of the rotational frequency) increases, such as compared to a maximum normal load magnitude or compared to the magnitude of the load on another bearing(s) of the disk gang assembly, the computing system may determine that the bearing(s) is experiencing a bearing failure condition. Upon making such a determination, the computing system may be configured to automatically initiate a control action, such as by generating an operator notification and/or automatically adjusting the operation of the implement.--
--[0042] Thus, as will be described in greater detail below, the bearing-related parameter(s) associated with a given disk assembly 44 may be monitored using one or more bearing sensors 100 provided in operative association with the disk assembly 44. For instance, as shown in FIG. 3, a bearing sensor 100 may be provided in association with at least one of the bearing(s) 64 to monitor the draft load at each of the associated bearing(s). The bearing sensor(s) 100 may be in contact with the bearing(s) 64 or the mount 64C and/or on the hanger(s) 62 supporting such bearing(s) 64.--
--[0050] As such, the computing system 202 may analyze the load data generated by the bearing sensor(s) 100 using one or more spectral analysis techniques to more easily identify the bearing failure related occurrences from other cyclical occurrences during the implement 10 operation. For instance, the computing system 202 may convert the data generated by the bearing sensor(s) 100 from the spatial (time) domain to the frequency domain using a spectral analysis technique, which makes it easier to identify cyclical frequencies. It should be appreciated that any suitable Fourier transformation technique, such as a Fast Fourier, Cooley-Tukey, Prime Factor, Bruun's, Rader's, Bluestein's, and/or Hexagonal techniques, or any other suitable spectral analysis techniques, such as the Bartlett's, Welch's, and/or Least-squares techniques, may be used to analyze the load data generated by the sensor(s) 100. The converted data indicates a magnitude of the load at different rotational frequencies, where the computing system 202 may evaluate the magnitude of the load at a rotational frequency of the disks 46 (or a multiple of the rotational frequency of the disks 46) in the transformed data to determine if the associated bearing 64 is experiencing a bearing failure condition.--
--[0051] In some instances, the computing system 202 may compare the magnitude of the load at the detected rotational frequency of the disks 46 associated with the bearing 64 in the transformed data to a baseline or maximum load magnitude for the rotational frequency (e.g., as determined when the disk gang shaft 56 was known to be operating correctly) for the ground speed and/or penetration depth of the disks 46 to determine when the bearing 64 is likely experiencing a bearing failure condition. For instance, the computing system 202 may estimate or measure the rotational frequency of the disks 46 based at least in part on the ground speed of the implement 10. In such instances, the computing system 202 may determine that the bearing 64 is likely experiencing the bearing failure condition when the magnitude of the load at the rotational frequency of the disks 46 associated with the bearing 64 is greater than the baseline load magnitude by at least a threshold difference. The threshold magnitude difference may be, for example, about 50 or more, such as about 100, such as about 150 and/or the like. However, it should be appreciated that any suitable threshold difference may be used. Moreover, it should be appreciated that, in some instances, the computing system 202 may compare the magnitude of the load at the rotational frequency of the disks 46 associated with the bearing 64 to more than one baseline load magnitude, where the different baseline magnitudes may be associated with different severities of the bearing failure condition (e.g., partial bearing failure condition, complete bearing failure condition, and/or the like).--
--[0052] In one or more instances, the computing system 202 may additionally, or alternatively, compare the magnitude of the load at the rotational frequency of the disks 46 associated with the bearing 64 to the magnitude of the load at the rotational frequency of the disks 46 associated with one or more of the other bearings 64 of the same disk gang assembly 44 and determine when the bearing 64 is likely experiencing a bearing failure condition based at least in part on the comparison. For instance, when the magnitude of the load at the rotational frequency of the disks 46 associated with the bearing 64 differs by at least a threshold amount from the magnitude of the load at the rotational frequency of the disks 46 associated with the other bearing(s) 64 of the disk gang assembly 44, the computing system 202 may determine that the bearing 64 is likely experiencing the bearing failure condition. The threshold amount may be, for example, about or more, such as about 100, such as about 150 and/or the like. However, it should be appreciated that any suitable threshold amount may instead be used, and/or that multiple threshold amounts may be used to indicate different severities of the bearing failure condition.--
--[0053] As an example of such analysis, the top plot 250 in FIG. 6 illustrates the load at a bearing over time whereas the bottom plot 252 in FIG. 6 illustrates the time domain data from the plot 250 converted using a Fast Fourier Transformation (FFT) technique into the frequency domain. In the bottom plot 252 of FIG. 6, there are several frequencies that have a significantly higher load magnitude, particularly a first frequency F1 (e.g., having a frequency of about 50 Hertz [Hz]), a second frequency F2 (e.g., having a frequency of about 125 Hz), a third frequency F3 (e.g., having a frequency of about 875 Hz), and a fourth frequency F4 (e.g., having a frequency of about 950 Hz).--
--[0054] The computing system 202 determines that the rotational frequency of the disks 46 is close, or equal to, the first frequency F1 (e.g., 50 Hz), then compares the load magnitude H1 at the first frequency F1 (e.g., about 600 at 50 Hz) to a baseline load magnitude MAX1 for the first frequency F1 (e.g., about 425 at 50 Hz) associated with the maximum normal magnitude of the load at the current ground speed and/or penetration depth of the disks 46. The computing system 202 may determine that the bearing 64 is likely experiencing a bearing failure condition as the load magnitude H1 at the first frequency F1 for the bearing 64 exceeds the baseline load magnitude MAX1 by at least the threshold difference (e.g., by more than 50). Similarly, in some instances, the computing system 202 may compare the load magnitude H1 of the bearing 64 at the first frequency F1 (e.g., about 600 at 50 Hz for the outer bearing 64) to a load magnitude H2 of a first other bearing (e.g., about 375 at 50 Hz for the middle bearing 64) and/or a load magnitude H3 of a second other bearing (e.g., about 350 at 50 Hz for the inner bearing 64), determined from data generated by other sensor(s) 100 and similarly transformed to the frequency domain. The computing system 202 may determine that the bearing 64 (e.g., outer bearing) is likely experiencing a bearing failure condition as the load magnitude H1 at the first frequency F1 for the bearing 64 (e.g., outer bearing) differs from the load magnitude(s) H2, H3 of the other bearing(s) 64 (e.g., middle and/or inner bearing(s)) by at least the threshold amount (e.g., by more than 150).--
--[0055] Moreover, referring back to FIG. 5, the computing system 202 may determine whether there are multiple instances of a bearing failure condition present at a particular bearing by evaluating secondary load magnitudes at multiples of the rotational frequency of the disks 46. For instance, if the bearing 64 starts to have one or more secondary points of sticking about the rotational axis 56A, the bearing 64 may only stick at these secondary points every nth rotation about the axis 56A at the start of such condition. As such, the computing system 202 may monitor the secondary magnitudes at multiples of the rotational frequency of the disks 46 to determine whether there is more than one instance of a bearing failure condition (e.g., when the secondary magnitude is more than the threshold difference from the baseline load magnitude MAX1 and/or more than a threshold amount from the secondary magnitudes at the multiples of the rotational frequency for the other bearings 64).--
--[0056] In the example plot 252 of FIG. 6, for instance, the second frequency F2 (e.g., about 125 Hz) is not a multiple of the first frequency F1 (e.g., about 50 Hz), so the computing system 202 may determine that the load magnitude H4 at the second frequency F2 is likely associated with another cyclical load on the disk gang assembly 44, such as by the engine cycling. The third frequency F3 (e.g., about 875 Hz) is also not a multiple of the first frequency F1, as such the computing system 202 may determine that the load magnitude H5 at the second frequency F2 is likely associated with another cyclical load on the disk gang assembly 44, such as another cyclical load by the engine cycling or from see sawing of the disk assembly 44. The fourth frequency F4 (e.g., about 950 Hz) is a multiple of the first frequency F1 (e.g., about 50 Hz), as such that computing system 202 may determine that the bearing 64 is likely experiencing at least one other instance of the bearing failure condition, as the secondary load magnitude H6 at the fourth frequency F4 is also greater than the baseline load magnitude MAX1 and/or as the other bearings are not experiencing a spike at the fourth frequency F4.--
--[0061] At (306), the method 300 may include identifying when the bearing is experiencing a bearing failure condition based at least in part on an evaluation of the load data converted to the frequency domain. For instance, as discussed above, the computing system 202 may identify when the bearing(s) 64 is experiencing one or more instances of the bearing failure condition based at least in part on an evaluation of the load data converted to the frequency domain. For example, the computing system 202 may evaluate the load magnitude of each of the monitored bearing(s) at the rotational frequency of the disk gang assembly 44 to determine if the bearing(s) are experiencing at least one instance of the bearing failure condition.--
Appropriate correction is required.
Claim Objections
Claims 2-3 and 12-13 are objected to because they are unclear. Going forward with examination, the claims are interpreted to be:
--2. The system of claim 1, wherein the data converted to the frequency domain indicates a magnitude of the bearing-related parameter at a detected rotational frequency, and
wherein the computing system is configured to identify that the bearing is experiencing the bearing failure condition when the magnitude of the bearing-related parameter at the detected rotational frequency is greater than a baseline magnitude by at least a threshold difference.--
--3. The system of claim 2, wherein the data converted to the frequency domain indicates a secondary magnitude of the bearing-related parameter at a multiple of the detected rotational frequency, and
wherein the computing system is configured to identify that the bearing is experiencing multiple instances of the bearing failure condition when the secondary magnitude of the bearing-related parameter at the multiple of the detected rotational frequency is also greater than the baseline magnitude by at least the threshold difference.--
--12. The method of claim 11, wherein the data converted to the frequency domain indicates a magnitude of the bearing-related parameter at a detected rotational frequency, and
wherein identifying when the bearing is experiencing the bearing failure condition comprises identifying that the bearing is experiencing the bearing failure condition when the magnitude of the bearing-related parameter at the detected rotational frequency is greater than a baseline magnitude by at least a threshold difference.--
--13. The method of claim 12, wherein the data converted to the frequency domain indicates a secondary magnitude of the bearing-related parameter at a multiple of the detected rotational frequency, and
wherein identifying when the bearing is experiencing the bearing failure condition comprises identifying that the bearing is experiencing multiple instances of the bearing failure condition when the secondary magnitude of the bearing-related parameter at the multiple of the detected rotational frequency is also greater than the baseline magnitude by at least the threshold difference.--
Appropriate correction is required.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 7-15, 17-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Schroeder (US 2023/0175923 A1) in view of Thomson (US 9,989,439 B2).
1. Schroeder teaches a system for detecting bearing failures for disk gang assemblies (44) of an agricultural implement (10), the system comprising:
a disk gang assembly (44) comprising (See fig. 3, reproduced below):
a shaft (73);
a bearing (75) rotatably supporting the shaft (73) for rotation about a rotational axis (71); and
a plurality of disks (46) supported on the shaft (75) for rotation with the shaft (75) about the rotational axis (71);
a sensor (80) provided in operative association with the disk gang assembly (44), the sensor (80) being configured to generate data indicative of a disk gang-related parameter; and
a computing system 110 (Fig. 4) configured to:
receive the data generated by the sensor (80);
identify when the bearing (75) is experiencing a bearing failure condition based at least in part on an evaluation of the data
PNG
media_image1.png
648
974
media_image1.png
Greyscale
Schroeder doesn’t teach:
a sensor provided in operative association with the bearing (75), the sensor being configured to generate data indicative of a bearing-related parameter; and
the computing system (110) configured to:
receive the data generated by the sensor;
convert the data to a frequency domain using a spectral analysis technique; and
identify when the bearing (75) is experiencing a bearing failure condition based at least in part on an evaluation of the data converted to the frequency domain.
Thomson teaches a system for detecting bearing failures for mechanical systems (like wind turbines, trains, trucks, automobiles, etc.; Col. 1, lines 20-32), the system comprising (See figs. 1, 2, reproduced below):
a sensor 12 (Fig. 1) provided in operative association with a bearing (10), the sensor (12) being configured to generate data indicative of a bearing-related parameter (e.g., vibrations of the bearing 10; Abstract); and
a computing system 14 (Fig. 1) configured to:
receive the data generated by the sensor 12 (Fig. 2, S100; Thomson claim 1);
convert the data to a frequency domain using a spectral analysis technique (e.g., Fourier Transform; S101; Thomson claim 1); and
identify when the bearing (10) is experiencing a bearing failure condition based at least in part on an evaluation of the data converted to the frequency domain (S107; Thomson claim 1).
As such, the system can at least provide a defect severity assessment of the bearing 10 (S107; Thomson claim 1).
PNG
media_image2.png
608
624
media_image2.png
Greyscale
PNG
media_image3.png
1146
762
media_image3.png
Greyscale
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the present application to apply Thomson teaching to Schroeder system by providing the system with a sensor provided in operative association with the bearing (75), the sensor being configured to generate data indicative of a bearing-related parameter; and the computing system (110) configured to receive the data generated by the sensor; convert the data to a frequency domain using a spectral analysis technique; and identify when the bearing (75) is experiencing a bearing failure condition based at least in part on an evaluation of the data converted to the frequency domain, so as to provide a defect severity assessment of the bearing, for example.
2. Schroeder as modified teaches the system of claim 1, wherein the data converted to the frequency domain indicates a magnitude of the bearing-related parameter at a detected rotational frequency (Thomson fig. 2, S105), and
wherein the computing system (110/14) is configured to identify that the bearing (75/10) is experiencing the bearing failure condition when the magnitude of the bearing-related parameter at the detected rotational frequency is greater than a baseline magnitude (“lower threshold value”) by at least a threshold difference (Thomson Col. 11, lines 30-42).
3. Schroeder as modified teaches the system of claim 2, wherein the data converted to the frequency domain indicates a secondary magnitude of the bearing-related parameter at a multiple of the detected rotational frequency (Thomson Col. 3, lines 56 – Col. 4, line 6; Col. 7, lines 1-17; Col. 10, lines 6-39) and
wherein the computing system (110/14) is configured to identify that the bearing (75/10) is experiencing multiple instances of the bearing failure condition when the secondary magnitude of the bearing-related parameter at the multiple of the detected rotational frequency is also greater than the baseline magnitude (“lower threshold value”) by at least the threshold difference (Thomson Col. 3, lines 56 – Col. 4, line 6; Col. 7, lines 1-17; Col. 10, lines 6-39).
4. Schroeder as modified teaches the system of claim 2, wherein the detected rotational frequency is a rotational frequency of the plurality of disks (which is directly proportional to a rotational speed, or RPM, of the bearing 75/10; Thomson fig. 2, S100; Abstract; Col. 2, lines 46-56).
5 (essentially equivalent to claim 1).
Schroeder as modified teaches the system of claim 1, further comprising:
a second bearing (75/10) rotatably supporting the shaft (73) for rotation about the rotational axis (71), the second bearing (75/10) being spaced apart along the rotational axis (71) from the bearing 75/10 (Schroeder Par. 0030); and
a second sensor (12) provided in operative association with the second bearing (75/10), the second sensor (12) being configured to generate second data indicative of the bearing-related parameter for the second bearing (75/10), wherein the computing system (110/14) is further configured to:
receive the second data generated by the second sensor 12 (Thomson fig. 2, S100; Thomson claim 1);
convert the second data to the frequency domain using the spectral analysis technique (e.g., Fourier Transform; Thomson fig. 2, S101; Thomson claim 1); and
identify when the second bearing (75) is experiencing the bearing failure condition based at least in part on an evaluation of the second data converted to the frequency domain (Thomson fig. 2, S107; Thomson claim 1).
7. Schroeder as modified teaches the system of claim 1, wherein the spectral analysis technique is Fourier transformation (Thomson fig. 2, S101).
8. Schroeder as modified teaches the system of claim 1, wherein the sensor comprises a draft load sensor, the data being indicative of a load on the bearing (such a “load” in broadly interpreted as vibration loading taught by Thomson. See discussion above in claim 1).
9. Schroeder as modified teaches the system of claim 1, wherein the sensor (12) directly contacts the bearing (as is apparent from at least Thomson fig. 1).
10. Schroeder as modified teaches the system of claim 1, wherein the computing system (110) is configured to perform a control action associated with the agricultural implement (10) when the bearing is identified as experiencing the bearing failure condition (as is obvious per Schroeder Pars. 0019; 0053-0034).
11-15, 17-18 and 20 (essentially equivalent to claims 1-5, 7-8 and 10).
Schroeder as modified teaches a method for detecting a bearing failure condition for a disk gang assembly (44) of an agricultural implement (10), the disk gang assembly (44) comprising a shaft (73), a bearing (75) rotatably supporting the shaft (73) for rotation about a rotational axis (71), and a plurality of disks (46) supported on the shaft (73) for rotation with the shaft (73) about the rotational axis (71), the method comprising all the recited features (See discussions above in claims 1-5, 7-8 and 10).
19. Schroeder as modified teaches the method of claim 11, wherein performing the control action comprises controlling an operation of a user interface 23 (Schroeder figs. 1, 4) associated with the agricultural implement (10) to indicate that the bearing (75) is identified as experiencing the bearing failure condition (as is obvious per Schroeder Par. 0053).
Allowable Subject Matter
Claims 6 and 16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following would be a statement for indication of an allowable subject matter:
With respect to claims 6 and 16, prior art of record doesn’t teach, suggest, or render obvious the total combination of the recited features, including the following allowable subject matter (or an equivalent): “wherein the bearing is a first bearing, wherein the sensor is a first sensor, and the data generated by the first sensor is first data, and wherein the computing system is configured to identify that the one of the first bearing or the second bearing is experiencing the bearing failure condition based at least in part on a comparison of the first data converted to the frequency domain and the second data converted to the frequency domain.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nguyen (Wyn) Q. Ha whose telephone number is (571) 272-2863, email: nguyenq.ha@uspto.gov. The examiner can normally be reached Monday - Friday 8 am - 4:30 pm (Eastern Time).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen Meier can be reached at (571) 272-2149. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Nguyen Q. Ha/Primary Examiner, Art Unit 2853 February 20, 2026