DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of Claims
This Office Action is in response to applicant’s amendments and remarks filed on February 20, 2026. Claims 1-3, 7, 9, 10, 14, 15, 17, and 18 have been amended. No claims have been newly added or cancelled. Accordingly, Claims 1-7 and 9-20 are currently pending.
Response to Remarks/Arguments
Applicant’s amendments and remarks, filed on February 20, 2026, with respect to the previous 35 U.S.C. 101 rejections have been fully considered and are persuasive. Therefore, the previous 35 U.S.C. 101 rejections have been withdrawn.
Applicant’s amendments and remarks, filed on February 20, 2026, with respect to the previous 35 U.S.C. 103 rejections have been fully considered and are persuasive, therefore the previous 35 U.S.C. 103 rejections have been withdrawn, and a new ground(s) of 35 U.S.C. 103 rejection has been made.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 9-11, 15, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Dybro et al. (Publication Number US20160084987A1; hereinafter Dybro) in view of Boufleur et al. (Publication Number US20220279706A1; hereinafter Boufleur), Bogdan et al. (Publication Number US20210267117A1; hereinafter Bogdan) and Reusch et al. (Publication Number US20250234798A1; hereinafter Reusch).
Regarding Claim 9 (which is substantially similar to Claims 1 and 17), Dybro discloses a self-propelled windrower (See at least Abstract; Paragraph 0072, “Although harvester 422 is described as a rotary combine, in other implementations, harvester 422 may comprise… windrowers”) comprising:
a chassis; a tractive element coupled to the chassis (Figure 7 and Paragraph 0068, “Harvester 422 comprises a chassis 512 which is supported and propelled by ground engaging wheels 514”),
a header coupled to the chassis (Figure 7 and Paragraph 0021, “…aggregate yield allocation system 20 takes into account different travel times for crops from different portions of a harvester head to an aggregate sensor when allocating the aggregate yield”),
the header including a rotatable cutting element configured to cut plant material (Paragraph 0061 describes components that reasonably include rotatable cutting elements, “Examples of components across the harvesting width of harvester 22 for which power characteristics are be sensed include, but are not limited to, a snap roller, a stalk chopper, and a cutter bar”);
a header sensor configured to provide header data indicative of a rotation rate of the rotatable cutting element and header torque (Paragraph 0138, “Processor 1142 comprises one or more processing units that follow program logic or code contained in a non-transitory computer readable medium or memory 1143”; Paragraphs 0135-0136, “Torque sources 1135 supply torque to rotatably drive each of the knives 1146…Power characteristic sensors 1136 sense power characteristics of torque sources 1135...Power characteristic sensors 1136 comprise one or more of voltage sensors, current sensors, torque sensors, rotational speed sensors, phase sensors, or other appropriate sensors. Sensors 1136 output signals which are transmitted to processor 1142”);
a controller operatively coupled to the header sensor (Figure 18 shows processor 1142 operatively coupled to header sensors (e.g. “120a”, “120b”, “120c”)), the controller configured to:
receive, from the header sensor, the header data indicative of the rotation rate of the rotatable cutting element and the header torque (Paragraph 0136, “Power characteristic sensors 1136 sense power characteristics of torque sources 1135…Power characteristic sensors 1136 comprise one or more of voltage sensors, current sensors, torque sensors, rotational speed sensors, phase sensors, or other appropriate sensors. Sensors 1136 output signals which are transmitted to processor 1142”);
compare the header data indicative of the rotation rate to a threshold indicative of a field anomaly (Paragraph 0118 describes comparing header data (e.g. “power characteristics”) with predefined thresholds in order to determine field and/or crop conditions (“…condition detection module 856 directs processor 830 to carry out one or more algorithms and/or mathematical equations using a directly sensed power characteristic value…to further compare the resulting calculation to one or more predefined thresholds to identify a field and/or crop condition”), wherein field and/or crop conditions reasonably indicate field anomalies (“Examples of such field/crop conditions include, but are not limited to, the absence of plants, a field washout condition, an area of the field having yields suffering from wheel compaction beyond a predetermined threshold, the existence of a weed patch, the existence of yield loss due to inappropriate chemical application, and/or the like”));
calculating crop yield in the field based on header torque (Paragraph 0139, “Processor 1142 processes data from sensors 1136 and optionally from geo-referencing system 1140 and data source 1170. Data source 1170 comprises supplemental data used by processor 1142 to [derive], determine or estimate crop attributes, such as biomass yield or grain yield”);
identify the anomaly at a location in the field when the header data indicative of the rotation rate reaches the threshold (Paragraph 0137 describes linking the anomaly (e.g. field conditions derived from power characteristics) with a location (“Geo-referencing system 1140 provides geo-referenced data to processor 1142 to associate sensed power characteristics and derived or determined crop attributes, such as biomass yield or grain yield, to particular geo-referenced regions…In another implementation, geo-referencing system 1140 provides time-stamp data linking or associating particular regions of a field to sensed power characteristics and/or derived or determined crop attributes as harvester 1122 traverses a field”)).
While Dybro further discloses features that would reasonably indicate the threshold as representing a field anomaly that is below a normal rate (Paragraph 0125 describes an indication that the implement is operating below a normal operation rate (“…processor 830 stores the crop attribute values derived from the sensed power characteristic in data storage portion 852…In some implementations, a visible or audible alert or notice may be output by display 824 in response to the derived crop attribute value for a particular portion satisfying a predefined threshold. For example, if a derived crop yield for a particular portion P, such as a particular row unit of head 834, falls below a predefined threshold, the operator may be provided with an alert or notice possibly indicating problems with the operation of the particular row unit”)), Dybro does not explicitly recite defining the threshold value itself as being set below a normal operation rate; wherein the rotatable cutting element has an operation rate and wherein the threshold is below the operation rate; nor a controller operatively coupled to a drive motor configured to drive the tractive element to propel the windrower through a field.
Nevertheless, Boufleur teaches features for controlling an agricultural vehicle (see at least Abstract) comprising features for defining a threshold value itself at:
below a normal operation rate (Paragraph 0100, “Plugging condition detection logic 576 is configured to detect a plugging condition for any of row units 110 based on the speed thresholds generated by logic 572, and any compensation performed by compensation logic 574. Illustratively, a plugging condition is detected when a speed threshold is reached (e.g., the rotational speed of a ground-engaging element falls below the speed threshold). This can include situations in which a ground-engaging element ceases rotation or is rotating at a relatively low speed”; Paragraph 0110 describes the speed threshold as a value below normal (e.g. reference) rate (“A speed threshold for a particular ground-engaging element on a row unit 110 can be defined as a difference relative to a first or reference speed. To illustrate, in one example, a speed threshold for furrow opener 162 (or other ground-engaging element) is ninety percent of the reference speed. In another example, the speed threshold is seventy five percent of the reference speed…”));
wherein the rotatable cutting element has an operation rate and wherein the threshold is below the operation rate (Paragraph 0098 describes an operation (reference) rate (“In one example, the reference speed includes a first or normal operating speed of the particular ground-engaging element, when the element is in an unplugged state”)); Paragraph 0100, “Plugging condition detection logic 576 is configured to detect a plugging condition for any of row units 110 based on the speed thresholds generated by logic 572, and any compensation performed by compensation logic 574. Illustratively, a plugging condition is detected when a speed threshold is reached (e.g., the rotational speed of a ground-engaging element falls below the speed threshold). This can include situations in which a ground-engaging element ceases rotation or is rotating at a relatively low speed”; Paragraph 0110 describes the speed threshold as a value below normal (e.g. reference) rate (“A speed threshold for a particular ground-engaging element on a row unit 110 can be defined as a difference relative to a first or reference speed. To illustrate, in one example, a speed threshold for furrow opener 162 (or other ground-engaging element) is ninety percent of the reference speed. In another example, the speed threshold is seventy five percent of the reference speed…”)); and
a controller operatively coupled to a drive motor configured to drive the tractive element to propel the windrower through a field (Figure 3 and Paragraph 0022, “FIG. 1 is a top view of one example of an agricultural machine 100…Towing machine 104 can include a propulsion system, such as an engine, housed in engine compartment 112, ground-engaging elements 114, such as wheels or tracks…”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Dybro invention to expand the features for identifying field anomalies based on a comparison between header data and a predefined threshold (Paragraph 0118) to include setting the threshold value itself as being less than a normal operation rate, as taught by Boufleur, for the benefit of determining whether an agricultural vehicle is performing within preset expectations (e.g. not plugging) (Boufleur, Paragraph 0100).
Dybro as currently modified still does not explicitly teach: revise the calculated crop yield for the location of the identified field anomaly.
Nevertheless, Bogdan teaches features for mapping operational abnormalities in an agricultural field (see at least Abstract) comprising:
revise the calculated crop yield for the location of the identified field anomaly (Paragraph 0047 describes determining crop yield of the agricultural field and revising (omitting) yield values at locations associated with the identified anomalies (“…receiving yield data for the agricultural field; using the map of operational abnormalities, generating updated yield data for the agricultural field; and generating a yield analysis for the agricultural field excluding the data identified using the map of operational abnormalities”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to expand the features for yield mapping (Paragraph 0054, “Yield mapping module 56 comprises software, code, circuitry and/or program logic providing instructions for directing processor 32 to map the allocation of aggregate yield to the different geo-referenced regions traversed by harvester 22”) to include identification of an operational anomaly for yield revision, as taught by Bogdan, for the benefit of improving performance tracking (Bogdan, Paragraphs 0068, “…identifies locations that were flagged as including operational abnormalities”; Paragraph 0127, “Flagged locations may be removed from analyses of the agricultural field, thereby improving the agricultural intelligence computer system's abilities to monitor the agricultural field and/or react to monitored information of the agricultural field”).
While Dybro further discloses that the harvester may perform responsive controls based on yield data (Paragraph 0053, “Machine control module 54…adjust operational settings or parameters of machine control 24 of harvester 22 based upon the allocation of aggregate yield to different geo-referenced regions”), Dybro still does not explicitly recite condition soil in the field responsive to the revised calculated crop yield.
Nevertheless, Reusch teaches features for corrective conditioning based on yield data (see at least Abstract and Paragraph 0007, “a fertilizer recommendation taking into account in-field variabilities due to soil properties and long-term dynamics is achieved”) comprising:
condition soil in the field responsive to the revised calculated crop yield (Paragraph 0006, “…processing the yield data to determine a nutrient specific correction for the fertilizer recommendation and adjusting the fertilizer recommendation based on the nutrient specific correction”; Paragraph 0081, “The method of the current disclosure further comprises processing 1300 the yield data. In an embodiment, the method of the current disclosure comprises processing the yield data to obtain an absolute value of the position dependent yield data for a given pixel/location and is further adapted to determine a nutrient specific correction based on the absolute value of the position dependent yield data for the at least one prior crop for a given pixel. In a further embodiment, determining a nutrient specific correction based on the absolute value of the position dependent yield data may comprise a specific correction for phosphorus and potassium”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to expand the features for adjusting controls based on yield data (Paragraph 0053) to include soil conditioning, as taught by Reusch, for the benefit of improving application of fertilizer in order to increase yield.
Regarding Claims 2, 10 and 18, Dybro as currently modified teaches claims 1, 9 and 17. Dybro does not explicitly disclose: receiving, from a location sensor, location data indicative of the location of the windrower where the field anomaly was identified; and presenting an indicator representing the field anomaly on a map corresponding to the location of the windrower where the field anomaly was identified.
Nevertheless, Bogdan further teaches:
receiving, from a location sensor, location data indicative of the location of the windrower where the field anomaly was identified (Paragraph 0093, “Position sensors may comprise GPS receivers or transceivers, or Wi-Fi-based position or mapping apps that are programmed to determine location based upon nearby Wi-Fi hotspots, among others”; Paragraph 0038, “In an embodiment, a method comprises receiving time-series data captured from an agricultural implement performing an agronomic activity on an agricultural field, the time-series data including, for each of a plurality of timestamps, a location of the agricultural implement; identifying a plurality of passes in the time-series data; using the identified plurality of passes, identifying a plurality of location on the agricultural field in which the activity performed by the agricultural implement included a particular operational abnormality…”) and
presenting an indicator representing the field anomaly on a map corresponding to the location of the windrower where the field anomaly was identified (Paragraph 0038, “…generating a map of operational abnormalities for the agricultural field, the map of operational abnormalities including the plurality of locations on the agricultural field in which the activity performed by the agricultural implement included the particular operational abnormality”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to expand features that allow mapping (Paragraph 0054) to include identification of an operational anomaly, as taught by Bogdan, for the benefit of improved performance tracking (Bogdan, Paragraphs 0067 and Paragraph 0127).
Regarding Claims 3 and 15, Dybro as currently modified teaches claims 1 and 9. Dybro does not explicitly disclose: wherein the threshold is a value corresponding to 50 revolutions per minute below the operation rate
Nevertheless, Boufleur further teaches:
wherein the threshold is a value corresponding to below the operation rate (Paragraph 0100, “Plugging condition detection logic 576 is configured to detect a plugging condition for any of row units 110 based on the speed thresholds generated by logic 572, and any compensation performed by compensation logic 574. Illustratively, a plugging condition is detected when a speed threshold is reached (e.g., the rotational speed of a ground-engaging element falls below the speed threshold). This can include situations in which a ground-engaging element ceases rotation or is rotating at a relatively low speed”; Paragraph 0110 describes the speed threshold as a value below normal (e.g. reference) rate (“A speed threshold for a particular ground-engaging element on a row unit 110 can be defined as a difference relative to a first or reference speed. To illustrate, in one example, a speed threshold for furrow opener 162 (or other ground-engaging element) is ninety percent of the reference speed. In another example, the speed threshold is seventy five percent of the reference speed…”)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Dybro invention to expand the features for identifying field anomalies based on a comparison between header data and a predefined threshold (Paragraph 0118) to include setting the threshold value itself as being less than a normal operation rate, as taught by Boufleur, for the benefit of determining whether an agricultural vehicle is performing within preset expectations (e.g. not plugging) (Boufleur, Paragraph 0100).
While Dybro as currently modified teaches a threshold corresponding to a specific value below the operation rate, Dybro as currently modified still does not explicitly recite that the threshold value corresponds to 50 revolutions per minute below the operation rate. However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to set the threshold to a value corresponding to 50 revolutions per minute below the operation rate, since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art (see at least Re Aller, 105 USPQ 233).
Regarding Claims 4, 11 and 19, Dybro as currently modified teaches claims 1, 9 and 17. Dybro further discloses:
receiving, from a location sensor, location data indicative of the location of the windrower; and determining the crop yield at the location further based on the location data received from the location sensor (Paragraph 0137, “Geo-referencing system 1140 provides geo-referenced data to processor 1142 to associate sensed power characteristics and derived or determined crop attributes, such as biomass yield or grain yield, to particular geo-referenced regions. In one implementation, geo-referencing system 1140 comprises a global navigation satellite system (GNSS). Geo-referencing system 1140 provides data such as global position, speed, heading, time”; Examiner notes that as currently claimed, associating crop yield with location data is reasonably indicating that crop yield is at least in part based on location data).
Claims 5-7, 12-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Dybro in view of Boufleur, Bogdan, Reusch, and Duke et al. (Publication Number US20190075727A1; hereinafter Duke).
Regarding Claims 5, 12 and 20, Dybro as currently modified teaches claims 4, 11 and 17. Dybro does not explicitly teach: determining a first crop yield at a first location adjacent a first side of an anomaly detection location where the header data indicative of the rotation rate reaches the threshold; determining a second crop yield at a second location adjacent a second side of the anomaly detection location where the header data indicative of the rotation rate reaches the threshold; determining an anomaly detection yield at the anomaly detection location based on the first crop yield and the second crop yield.
While Dybro further discloses an anomaly detection location where the header data indicative of the rotation rate reaches the threshold (Paragraph 0137 describes linking the anomaly (e.g. field conditions derived from power characteristics) with a location (“Geo-referencing system 1140 provides geo-referenced data to processor 1142 to associate sensed power characteristics and derived or determined crop attributes, such as biomass yield or grain yield, to particular geo-referenced regions…In another implementation, geo-referencing system 1140 provides time-stamp data linking or associating particular regions of a field to sensed power characteristics and/or derived or determined crop attributes as harvester 1122 traverses a field”)), Dybro as currently modified does not explicitly teach determining a first crop yield at a first location adjacent a first side [of a location]; determining a second crop yield at a second location adjacent a second side [of a location]; determining an anomaly detection yield at [a location] based on the first crop yield and the second crop yield.
Nevertheless, Duke teaches an agricultural yield map (Abstract, “A yield model generates a yield map for an agricultural field”) comprising:
determining a first crop yield at a first location adjacent a first side [of a location]; determining a second crop yield at a second location adjacent a second side [of a location]; determining an anomaly detection yield at [a location] based on the first crop yield and the second crop yield (Paragraph 0057, “By way of illustration, a yield mapping function F has a criteria for mapping yield points y to a cell g of the field array G to generate a mapped yield array Ym. The criteria defines that, for a region of the agricultural field associated with a particular cell gi of a field array G, the corresponding cell in the mapped yield array Ym has a yield value if that cell includes at least one yield point y. That is, a cell of a mapped yield array Ym has a yield value if the region of the agricultural field represented by that cell includes at least one yield point. Additionally, here, for each cell of a mapped yield array Ym, the yield mapping function F creates a yield value for the cell that is the average value of all yield points y within that cell. That is, a yield value for a cell in a mapped yield array Ym is an average of all yield points measured within the corresponding region of the field”).
Duke is considered analogous art to the claimed invention because it is reasonably pertinent to the problem determining a yield at a location based on a plurality of yields at adjacent locations. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to incorporate the teachings of Duke by including features that allow an anomaly detection yield to be calculated based on a plurality of adjacent crop yields for the benefit of a more robust calculation of yield (Duke, Paragraph 0057).
Regarding Claims 6 and 13, Dybro as currently modified teaches claims 5 and 12. Dybro does not explicitly disclose: determining the anomaly detection yield at the anomaly detection location by averaging the first crop yield and the second crop yield.
While Dybro discloses the anomaly detection location (Paragraph 0137 describes linking the anomaly (e.g. field conditions derived from power characteristics) with a location (“Geo-referencing system 1140 provides geo-referenced data to processor 1142 to associate sensed power characteristics and derived or determined crop attributes, such as biomass yield or grain yield, to particular geo-referenced regions…In another implementation, geo-referencing system 1140 provides time-stamp data linking or associating particular regions of a field to sensed power characteristics and/or derived or determined crop attributes as harvester 1122 traverses a field”)), Dybro as currently modified does not explicitly teach determining the anomaly detection yield at [a location] by averaging the first crop yield and the second crop yield.
Nevertheless, Duke further teaches:
determining the anomaly detection yield at [a location] by averaging the first crop yield and the second crop yield (Paragraph 0057, “For each cell of a mapped yield array Ym, the yield mapping function F creates a yield value for the cell that is the average value of all yield points y within that cell. That is, a yield value for a cell in a mapped yield array Ym is an average of all yield points measured within the corresponding region of the field”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to incorporate the teachings of Duke by including features that allow an anomaly detection yield to be calculated based on an average between a plurality of adjacent crop yields for the benefit of a more robust calculation (Duke, Paragraph 0057).
Regarding Claims 7 and 14, Dybro as currently modified teaches claims 4 and 11. Dybro further discloses:
assembling the crop yield for each of a plurality of locations within the field (Paragraph 0137, “Geo-referencing system 1140 provides geo-referenced data to processor 1142 to associate sensed power characteristics and derived or determined crop attributes, such as biomass yield or grain yield, to particular geo-referenced regions. In one implementation, geo-referencing system 1140 comprises a global navigation satellite system (GNSS). Geo-referencing system 1140 provides data such as global position, speed, heading, time”).
While Dybro as currently modified teaches when the header data indicative of the rotation rate reaches the threshold, the identified field anomaly (Paragraph 0137 describes linking the anomaly (e.g. field conditions derived from power characteristics) with a location (“Geo-referencing system 1140 provides geo-referenced data to processor 1142 to associate sensed power characteristics and derived or determined crop attributes, such as biomass yield or grain yield, to particular geo-referenced regions…In another implementation, geo-referencing system 1140 provides time-stamp data linking or associating particular regions of a field to sensed power characteristics and/or derived or determined crop attributes as harvester 1122 traverses a field”)), Dybro does not explicitly disclose: presenting the crop yield on a map corresponding to the plurality of locations within the field, the crop yield at each of the plurality of locations based on the location data received from the location sensor, the header data indicative of crop yield.
Nevertheless, Duke further teaches:
presenting the crop yield on a map corresponding to the plurality of locations within the field, the crop yield at each of the plurality of locations based on the location data received from the location sensor, the header data indicative of crop yield (Paragraph 0044, “The yield model 112 generates 240 a yield map using the indicators. In this example, the yield map is a field raster indicating a determined yield and/or a measured yield for areas in the field based on the satellite image, the nitrogen dataset, and the measured yield values. The yield map is configured for display as a heat map on the client system 110 such that the operator can easily visualize different areas and regions of determined yield”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to incorporate the teachings of Duke by including features that allow crop yield for a plurality of locations to be determined and mapped for the benefit of a more robust determination of the yield for an agricultural field (Duke, Paragraph 0044).
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Dybro in view of Brofleur, Bogdan, Reusch, and Paquet et al. (Patent Number US5704199A; hereinafter Paquet).
Regarding Claim 16, Dybro as currently modified teaches claim 9. Dybro does not explicitly disclose: wherein the header sensor is at least one of a tachometer that senses the rotation rate directly or a pressure sensor that senses the rotation rate indirectly.
Nevertheless, Paquet teaches a control system for an agricultural vehicle (Column 2, Lines 36-38, “FIG. 1 schematically illustrates an automatic control system for the adjustment of a shearbar relative to a rotating cutterhead”) comprising:
wherein the header sensor is at least one of a tachometer that senses the rotation rate directly or a pressure sensor that senses the rotation rate indirectly (Column 3, Lines 19-23, “A tachometer 114 senses rotation of the cutterhead shaft and produces a sequence of pulses indicating the cutterhead speed which is applied to an electrical control circuit 116”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the Dybro invention to incorporate the teachings of Paquet by including a tachometer to sense a rotational rate. Doing so would allow for more accurate measurements of speed for rotating elements (Paquet, Column 3, Lines 19-23).
Conclusion
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/EISEN YIM/Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
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