Harvester grain yield data management system and method

Abstract

The invention discloses a harvester grain yield data management system and method, and relates to the technical field of grain yield data management. The system comprises a feeding stage management module, a discharging stage management module, a measurement precision management module and a yield data uploading and storing module. Through feeding stability detection, basic data support is provided for follow-up discharging control, the continuity and reliability of yield measurement are improved from the source, and discharging amount abnormity or measurement errors caused by feeding fluctuation are avoided. Furthermore, dynamic association is established between feeding and discharging, self-adaptive discharging adjustment is achieved, and the stability and response precision of the measurement process are effectively improved. On the basis, the authenticity and timeliness of the yield data are ensured through linkage of data uploading and precision judgment, so that the reliability of yield data management is further improved, precision control and management of the whole process from feeding to data uploading are realized, and the credibility of the grain yield data of the harvester is remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of grain yield data management, in particular to a harvester grain yield data management system and method. BACKGROUND

[0002] As an important part of agricultural machinery, the effective management of harvester grain yield data is crucial for optimizing agricultural production. In the prior art, harvester grain yield data management generally includes data collection, data processing, data storage and analysis display, etc. Specifically, during operation, photoelectric sensors, flow sensors and other sensors provided on the harvester will collect raw data such as grain quantity and flow in real time. Subsequently, the collected raw data is preprocessed by filtering, denoising and outlier rejection, and the processed data is stored in the harvester control terminal or mobile storage device according to time, location and yield, etc. and uploaded to the background through wireless network or data interface after the operation is completed to realize the storage and visual management of grain yield data.

[0003] For example, the Chinese patent application with publication number CN114331289A discloses a warehouse management system and method based on big data, which includes a big data platform, a warehouse unit, a consumption unit, and a production unit. The consumption unit is used to collect the consumption of grain in the market and make predictions for the next cycle consumption. The production unit is used to collect various grain yields and quality levels of the farmers. The warehouse unit is used to adjust the inventory proportion of different types of grain.

[0004] For example, the Chinese invention patent with publication number CN115222305B discloses a wheat yield data management and early warning method, which includes collecting environmental data of grid areas by remote sensing satellites, dividing the wheat fields into several grid areas, analyzing the environmental data of the grid areas collected by remote sensing satellites, marking each grid area as a wheat grid, warning the yield of the wheat grid, marking the low-yield wheat grid as a low-yield wheat grid, and marking the over-yield wheat grid as an over-yield wheat grid. The position of the maximum priority analysis value pre-analysis grid is displayed on the mobile terminal of the staff.

[0005] The above-mentioned technology at least has the following technical problems: Due to the inconsistent size of grain particles, some larger kernels may not be able to flow smoothly, while smaller kernels may overlap and flow in, causing inaccurate identification by photoelectric sensors and affecting the accuracy of yield data measurement. At the same time, when the grain is accumulated too much, the response of the piston plate blocking mechanism for regulating the feeding is delayed, and the grain inflow speed cannot be controlled in time, which easily causes excessive accumulation inside the discharge pipe, affecting the measurement real-time and discharge efficiency, and further leading to continuous expansion of measurement error.

[0006] In addition, it is also necessary to consider that the photoelectric sensor is used to detect the number of grain seeds in the discharging process for feedback, however, in the case of high flow, there may be a problem of response time delay and insufficient signal processing capacity, resulting in that the yield calculation is not timely, and it is difficult to realize high-precision and intelligent management of the harvester yield data. SUMMARY

[0007] In order to solve the technical problem that the low accuracy of yield data measurement in the prior art leads to the difficulty in realizing high-precision and intelligent management of the harvester yield data, the embodiments of the present application provide a harvester grain yield data management system and method, and the technical solutions are as follows: On the one hand, a harvester grain yield data management system is provided, which comprises: a feeding stage management module for detecting the feeding stability of the harvester in the feeding stage in the working process to obtain a feeding management detection result, and feeding back to a discharging stage management module; the discharging stage management module is used for judging whether to trigger a discharging management strategy adjustment for improving the accuracy of the harvester grain yield measurement according to the received feeding management detection result, if the discharging management strategy adjustment is not triggered, the operation of a measurement precision management module is triggered, if the discharging management strategy adjustment is triggered, the operation of the measurement precision management module is judged after the discharging management strategy adjustment is performed; the measurement precision management module is used for judging the measurement precision of the yield data of the harvester in the discharging stage in the working process to obtain a yield measurement precision judgment result; and a yield data uploading and storing module is used for judging the uploading and storing of the yield data in combination with the yield measurement precision judgment result.

[0008] On the other hand, a harvester grain yield data management method is provided, which comprises: detecting the feeding stability of the harvester in the feeding stage in the working process to obtain a feeding management detection result, and feeding back; judging whether to trigger a discharging management strategy adjustment for improving the accuracy of the harvester grain yield measurement according to the feeding management detection result, if not, judging the measurement precision of the yield data of the harvester in the discharging stage in the working process to obtain a yield measurement precision judgment result, if yes, judging whether to obtain the yield measurement precision judgment result after the discharging management strategy adjustment is performed; and judging the uploading and storing of the yield data in combination with the yield measurement precision judgment result.

[0009] The technical solutions provided by the embodiments of the present application have at least the following beneficial effects: 1. The present application comprises a feeding stage management module, a discharging stage management module, a measurement accuracy management module, and a yield data uploading and storage module. Compared with the prior art, through the synergistic effect between the modules, a closed-loop data management structure is constructed throughout the whole process from feeding to discharging to data storage, and the accuracy of yield measurement and the intelligence of data management are realized as a whole. Specifically, the feeding stage management module is used for detecting the feeding stability of the harvester in the feeding stage during the operation process, quantitatively calculating the feeding fluctuation rate by obtaining parameters such as feeding amount standard deviation and average feeding amount, obtaining feeding management detection results for reflecting the uniformity of feeding, and feeding the detection results to the discharging stage management module to realize the feedforward control of the discharging stage operation state. Through the setting of this module, the uneven feeding, blockage or transient fluctuation can be identified in real time at the beginning of the operation, and the reliability of the feeding data is improved from the source, providing a basis for subsequent discharging adjustment and measurement accuracy improvement. The discharging stage management module judges whether the discharging management strategy needs to be adjusted according to the received feeding management detection results. If the feeding stability is good, the original discharging parameters are maintained and the measurement accuracy management module is directly triggered for detection; if the feeding stability is poor, adaptive adjustment of the discharging speed, flow or pipe pressure is performed to improve the stability of the discharging process, and then it is judged again whether the measurement accuracy management module is triggered. Through the setting of this module, dynamic correlation control of the feeding and discharging process can be realized, so that the discharging flow remains stable, thereby reducing the measurement signal fluctuation caused by uneven grain flow and improving the accuracy and response consistency of the overall yield measurement. The measurement accuracy management module is used for determining the measurement accuracy of the yield data in the discharging stage. By analyzing parameters such as the phase lag delay value of the discharging signal, the sensor response consistency and the data deviation rate, the yield measurement accuracy determination result is obtained. The setting of this module can realize real-time monitoring of the performance of the measurement system, timely find abnormal conditions caused by sensor drift, data delay or blockage, and ensure the accuracy and reliability of the yield data. The yield data uploading and storage module is used to comprehensively determine the uploading and storage of yield data in combination with the yield measurement accuracy determination result. Only when the measurement accuracy meets the set threshold value, the uploading and storage operation is performed to ensure that the data stored in the cloud or database is real and effective. The setting of this module enables the system to automatically select high-quality data, avoid the interference of error data on the statistical and analysis results, and improve the reliability of overall data management and decision support. Overall, through the synergistic linkage of feeding detection, discharging adjustment, accuracy determination and data storage, a closed-loop control mechanism for grain yield data management of the harvester is constructed, the stability and accuracy control of the data acquisition process are realized, the accuracy and real-time performance of the yield measurement in the harvesting operation stage are improved, and the accuracy control and management efficiency of the whole process from feeding to data uploading are effectively improved.

[0010] 2、In the process of harvester operation, firstly, based on the feeding amount data collected in the feeding time interval, the feeding amount standard deviation and the average feeding amount are calculated, and the inverse proportional result of the feeding fluctuation rate is taken as the feeding stability representation value. At the same time, in order to eliminate the influence of the operation speed change on the detection result, the cutting table working speed is further obtained, the operation speed factor is introduced to correct the feeding stability representation value, so as to improve the accuracy and robustness of the detection. Compared with the existing technology which only makes single judgment based on the feeding instantaneous amount or time average amount, the present application introduces the feeding fluctuation rate index and combines the cutting table speed deviation correction mechanism to realize the comprehensive evaluation of the dynamic stability of the feeding process, and effectively identifies the abnormal feeding state caused by uneven feeding, blockage or operation speed change, so as to provide real and effective input data for the subsequent unloading stage control, improve the coordination and precision of the whole operation, at the same time, significantly improve the dynamic response ability and anti-interference performance of the feeding detection, overcome the limitation that the traditional scheme cannot distinguish the speed change and the feeding fluctuation, ensure that the measurement result is more stable and more reliable. On this basis, through intelligent discrimination of the feeding state, a hierarchical response type unloading control mechanism is realized, so that the system can execute differentiated adjustment strategies according to different degrees of feeding fluctuation, thereby avoiding the problem of excessive adjustment or response lag, and improving the adaptability and stability of the whole system. In the prior art, unloading adjustment usually depends on fixed parameters or periodic correction, and cannot dynamically respond to real-time feeding state. The hierarchical triggering logic based on the feeding detection result is realized in the present application, which significantly improves the pertinence and intelligent level of unloading adjustment. Further, the introduction of the feeding management strategy benchmark adjustment mechanism can effectively reduce the subsequent measurement deviation caused by excessive feeding amount fluctuation, ensure the continuity and uniformity of the grain inflow process, and provide stable input conditions for the accurate control of the subsequent unloading stage. Compared with the feeding control method in the prior art which depends on fixed threshold or single monitoring parameter, the present application can realize adaptive adjustment based on real-time data, and significantly improve the dynamic response performance and operation adaptability of the feeding stage. At the same time, the existing technology usually only makes single-point adjustment when obvious blockage occurs, and lacks continuous feedback. The unloading management strategy optimization adjustment mechanism further introduces real-time monitoring of key parameters such as unloading pipeline pressure and flow on this basis, realizes accurate adjustment of the flow state in the unloading stage, prevents blockage, accumulation or empty flow phenomenon, effectively improves the consistency of grain flow and the stability of measurement signal, overcomes the problems of traditional lag reaction and misadjustment, greatly improves the dynamic control precision of the unloading stage, and realizes the intelligent, accurate and high-robustness production data management process.

[0011] 3、In the discharging stage, the phase delay characteristics of the discharging amount signal are extracted, the discharging phase lag delay value is calculated, and the preset discharging delay lag maximum limit value is compared to determine whether there is a phase response lag problem in the current measurement process. If the lag value is out of limit, it is considered that the measurement accuracy is abnormal; if it is within the normal range, the signal high-frequency gain is further detected to determine the response sensitivity of the sensor to high-frequency signal changes. Through the phase delay and high-frequency gain dual parameter judgment mechanism, the comprehensive accuracy evaluation of the yield measurement signal in the time response and amplitude response two dimensions can be realized, which is more comprehensive than the single threshold judgment method to reflect the sensor state and signal sampling quality, thereby effectively avoiding the misjudgment caused by single-point noise, delay drift and other factors. On this basis, the yield data upload storage judgment mechanism realizes the linkage control of data upload and accuracy judgment, prevents abnormal measurement data from being directly uploaded to cause subsequent analysis distortion, and ensures the effectiveness of the uploaded data. Compared with the traditional real-time upload method without judgment mechanism, the data quality control ability and self-correction ability of the system are improved. When detecting the measurement accuracy abnormality, the yield measurement acquisition strategy optimization is introduced to realize the adaptive adjustment of the sampling frequency, so that the data acquisition strategy can be dynamically optimized according to the real-time measurement error, avoiding the sampling distortion and delay error accumulation under the fixed sampling frequency. Compared with the prior art, through the cooperative closed loop of the measurement accuracy judgment, data upload judgment and acquisition strategy optimization in the discharging stage, the whole process dynamic monitoring and adaptive correction of the yield measurement data are realized, the measurement accuracy, data reliability and system adaptive ability of the discharging stage of the harvester are significantly improved, and the high credibility and high stability of the yield data acquisition process are ensured. BRIEF DESCRIPTION OF DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creating labor.

[0013] Figure 1 A structural schematic diagram of a harvester grain yield data management system provided by the embodiment of the present application; Figure 2 A feeding stability detection flowchart of a harvester grain yield data management system provided by the embodiment of the present application; Figure 3 A measurement accuracy judgment logic diagram of a harvester grain yield data management system provided by the embodiment of the present application; Figure 4 A flowchart of a harvester grain yield data management method provided by the embodiment of the present application. DETAILED DESCRIPTION

[0014] The technical solutions in the present application will be described below with reference to the drawings.

[0015] To make the technical problems, technical solutions and advantages of the present application clearer, specific embodiments will be described in detail below with reference to the drawings.

[0016] In agricultural production, the harvester as an important agricultural machinery undertakes the work of harvesting grain crops. In order to improve the efficiency of agricultural production, optimize resource allocation and realize fine management, the grain yield data management of the harvester becomes particularly important.

[0017] As shown in Figure 1 The structure schematic diagram of a grain yield data management system of a harvester provided by the embodiment of the present application, the system comprises: a feeding stage management module, a discharging stage management module, a measurement accuracy management module and a yield data uploading and storage module. Through the linkage of the above-mentioned modules, the whole process closed-loop management from feeding monitoring, discharging adjustment to data accuracy control and storage determination is realized, wherein the logical linkage of detection, feedback and determination between the modules realizes the unity of data flow and control flow, in addition, the data interaction between the modules forms a real-time feedback mechanism, the feeding detection result directly drives the discharging strategy adjustment, the discharging adjustment result provides a more stable environment for the measurement accuracy determination, and finally the accuracy result controls the data uploading and storage. The hierarchical linkage between the modules not only improves the response speed of the system, but also forms a closed-loop self-optimizing intelligent control system, realizing the whole process, whole chain quality control of the grain yield data of the harvester.

[0018] Specifically, the feeding stage management module is used for detecting the feeding stability of the harvester in the feeding stage during the operation process to obtain a feeding management detection result, and feeding the feeding management detection result to the discharging stage management module; by detecting the feeding stability of the harvester in the feeding stage during the operation process, the fluctuation of the feeding process can be quantified in real time, and the yield measurement error source caused by uneven feeding can be found in time; and then the feeding stability detection result is fed back to the discharging stage management module, providing a basis for the adaptive adjustment of the subsequent discharging strategy, and improving the stability and reliability of the whole yield measurement process from the source.

[0019] Reference Figure 2 As shown in Figure 2As shown, a feeding stability detection flow chart of the grain yield data management system provided by the embodiment of the present application, the corresponding logic is: based on the obtained feeding amount standard deviation and average feeding amount, the feeding stability characteristic value is obtained, if the feeding stability characteristic value is greater than the feeding stability reference limit value, the feeding management detection result is recorded as feeding detection standard, the discharge management strategy adjustment is not triggered, and the feeding stability characteristic value continues to be monitored, if the feeding stability characteristic value is not greater than the feeding stability set limit value, the feeding stability characteristic value is compared with the feeding control reference interval, if the feeding stability characteristic value is in the feeding control reference interval, the feeding management detection result is recorded as feeding detection qualified, the feeding management strategy reference adjustment is triggered, otherwise, the feeding management detection result is recorded as feeding detection unqualified, the discharge management strategy optimization adjustment is triggered. The feeding stability of the harvester in the feeding stage during the operation process is detected, and the specific steps are as follows: S1, based on the feeding amount data obtained by the flow sensor built in the feeding channel of the harvester in the feeding time interval, the feeding amount standard deviation and the average feeding amount are obtained, and the feeding stability correlation quantization is performed on the two to obtain the feeding fluctuation rate, the feeding stability correlation quantization is ratio operation, and the result of inverse proportion processing of the feeding fluctuation rate is taken as the feeding stability characteristic value for characterizing the feeding stability.

[0020] S2, the numerical relationship between the feeding stability characteristic value and the stored feeding stability reference limit value is judged; the feeding stability reference limit value is stored in the grain yield management database, and the grain yield management database is a database specially used to store core configuration information when designing a harvester grain yield data management system. Various limits and mapping sets necessary for the operation of the system are saved in the database, such as the feeding stability reference limit value. The initial setting of these limits is not randomly specified, and the technical personnel can manually set, adjust or fine-tune them at any time according to the specific performance of the system in actual test.

[0021] S3, if the feeding stability characteristic value is greater than the feeding stability reference limit value, the feeding management detection result is recorded as feeding detection standard, and the obtained feeding stability characteristic value continues to be monitored.

[0022] S4, if the feeding stability characteristic value is not greater than the feeding stability set limit value, the feeding stability characteristic value is compared with the stored feeding control reference interval, specifically: if the feeding stability characteristic value is in the feeding control reference interval, the feeding management detection result is recorded as feeding detection qualified, otherwise, the feeding management detection result is recorded as feeding detection unqualified; the feeding control reference interval is a closed interval corresponding to the feeding stability reference limit value to the feeding stability set limit value.

[0023] The standard deviation of the feeding amount calculated based on the accurate feeding amount data and the average feeding amount can more truly represent the fluctuation characteristics of the feeding stage, so that the feeding fluctuation rate and the feeding stability representation value calculated subsequently are more representative and reliable, thereby providing an accurate basis for the dynamic adjustment of the discharging stage management module. Thus, the quantitative detection and real-time feedback of the feeding stability are realized, and the front-end data quality of the whole machine yield measurement and the intelligent level of the system response are effectively improved.

[0024] As a further scheme, during the harvesting machine operation process, the feeding stability is not only affected by the change of the grain flow, but also closely related to the header working speed. When the header speed changes, the feeding amount entering the threshing mechanism will change synchronously or with a lag, thereby causing the feeding fluctuation rate to deviate. If the influence of the header speed is not corrected, the feeding stability representation value may be misjudged, causing the mis-triggering or missing-triggering of the discharging stage adjustment strategy. Therefore, it is necessary to correct the feeding stability representation value to eliminate the interference of the operation speed change on the detection result of the feeding stability. Specifically, the feeding stability of the harvesting machine in the feeding stage during the operation process is detected, and the method further includes: Q1, obtaining the header working speed of the harvesting machine during the operation process in the feeding time interval through the built-in driving speed sensor of the harvesting machine, quantifying the deviation of the header working speed from the stored operation reference speed to obtain a header working speed deviation value, which is the absolute value of the difference between the two.

[0025] Q2, judging the numerical relationship between the header working speed deviation value and the stored header speed deviation interval, which is a closed interval corresponding to the set speed minimum deviation to the set speed maximum deviation, obtained from the grain yield management database.

[0026] Q3, if the header working speed deviation value is within the header speed deviation interval, the feeding stability representation value is not processed, otherwise, the feeding stability representation value is corrected, specifically: the feeding stability representation value is corrected based on the introduced operation speed factor, and the correction processing is the product operation of the operation speed factor and the feeding stability representation value; the feeding stability representation value is updated according to the result of the correction processing, and the operation speed factor is used to correct the influence of the header working speed on the feeding stability detection, which is set by professionals according to the standards in the field.

[0027] By introducing the analysis of the header working speed in the process of the feed stability detection, the dynamic correction of the feed fluctuation rate can be realized, and the feed fluctuation error caused by the change of the harvester traveling speed can be effectively compensated. At the same time, the judgment of the deviation value and the deviation interval of the header working speed can filter out the data interval belonging to the normal working state, so as to avoid the misjudgment of the feed stability representation value in the non-stable working state. With the introduction of the working speed factor, the feed stability representation value can more accurately reflect the stability of the grain flow itself rather than being disturbed by the change of the working speed, and the accuracy of the feed detection result is further improved.

[0028] The downfeed stage management module is used to judge whether to trigger the downfeed management strategy adjustment for improving the measurement accuracy of the grain yield of the harvester according to the received feed management detection result. If the downfeed management strategy adjustment is not triggered, the operation of the measurement precision management module is triggered. If the downfeed management strategy adjustment is triggered, it is judged whether to trigger the operation of the measurement precision management module after the downfeed management strategy adjustment. The setting of this module can intelligently determine whether to trigger the downfeed management strategy adjustment according to the feed management detection result fed back in the feed stage, so as to automatically optimize and adjust the corresponding parameters of the downfeed process under the condition of unstable feed, reduce the flow fluctuation in the downfeed stage, and ensure the matching of the grain flow and the sensor detection. Under the condition of stable feed, invalid adjustment can be avoided, and the overall working efficiency and measurement accuracy of the harvester are improved.

[0029] As a further scheme, it is judged whether to trigger the downfeed management strategy adjustment according to the received feed management detection result. The downfeed management strategy adjustment includes the feed management strategy reference adjustment for controlling the feeding speed and the feeding flow to dynamically optimize the stability of the feed stage, and the downfeed management strategy optimization adjustment for controlling the downfeed speed and the downfeed flow to dynamically optimize the stability of the downfeed stage. The specific process is as follows: M1, it is judged whether the feed management detection result is the feed detection up to standard. If yes, the downfeed management strategy adjustment is not triggered.

[0030] M2, otherwise, it is judged whether the feed management detection result is the feed detection qualified. Specifically, if the feed management detection result is the feed detection qualified, the feed management strategy reference adjustment is triggered. If not, the downfeed management strategy optimization adjustment is triggered.

[0031] It should be noted that the feed management strategy reference adjustment has the following specific process: Firstly, the input of the feed stability characterization value into the feeding speed mapping table outputs the header feeding adjustment speed, and the header feeding speed adjustment prompt is sent according to the output header feeding adjustment speed; the feeding speed mapping table is obtained by pre-setting the historical feed stability characterization value and the header feeding adjustment speed set by the professional personnel according to the experience rule; the header feeding speed is adjusted adaptively according to the real-time fluctuation of the feed stage, so that the grain flow entering the threshing and discharging mechanism is more uniform and stable, the feed stage flow dynamics is realized, the unstable factors in the early stage of operation are eliminated, and the stability and accuracy of the subsequent discharging and measurement process are ensured.

[0032] Secondly, after adjusting the header feeding speed, the feed management detection result in the next feed time interval is obtained, and the judgment is made, and the specific judgment method is as follows: If the feed management detection result in the next feed time interval is that the feed detection meets the standard, the operation of the measurement accuracy management module is triggered.

[0033] If the feed management detection result in the next feed time interval is that the feed detection is qualified, the corresponding feed stability characterization values in the two feed time intervals are coupled and input into the feeding flow mapping table to output the feeding adjustment flow, and the initial feeding flow is set according to the output feeding adjustment flow, that is, the feeding adjustment flow is set as the initial feeding flow; the feeding flow mapping table is obtained by pre-setting the historical feed stability characterization value and the feeding adjustment flow set by the professional personnel according to the experience rule; by comprehensively considering the feed stability trend in the continuous operation interval, the flow adjustment result has smoothness and trend guiding property, and frequent adjustment or repeated oscillation caused by single detection fluctuation is avoided. In addition, by dynamically correcting the initial feeding flow, the grain density and flow state entering the discharging channel can be further stabilized, the discharging pressure fluctuation and signal noise interference caused by instantaneous flow mutation are reduced, and the repeatability and reliability of the measurement signal in the discharging stage are improved. At the same time, the adjustment strategy can realize the balance control between the feeding flow and the feed stability under the premise of maintaining the operation efficiency, so that the dynamic optimization closed loop is formed from the feed to the discharging link in the operation process.

[0034] If the feed management detection result in the next feed time interval is that the feed detection is abnormal, the header feeding speed adjustment abnormal prompt is sent, the header feeding speed before adjustment is returned, and the discharging management strategy optimization adjustment is triggered.

[0035] It should be further pointed out that the discharging management strategy optimization adjustment has the following specific process: Firstly, if the feed management strategy benchmark adjustment is triggered, the feed stability characterization value is updated, otherwise, the feed stability characterization value is directly used as the updated feed stability characterization value, which is input into the discharge speed mapping table to output the discharge adjustment speed, and the discharge speed is adjusted according to the output discharge adjustment speed, that is, the discharge adjustment speed is set as the discharge speed; the discharge speed mapping table is obtained by pre-setting the historical feed stability characterization value and the discharge adjustment speed set by the professional personnel according to the experience rule; the discharge speed is adjusted in real time according to the fluctuation of the feed stage, the dynamic matching of the feeding and discharging rates is realized, the uniformity and stability of the grain flow in the discharge pipe are significantly improved through the adaptive adjustment of the discharge speed, and a reliable flow basis is provided for pressure control and subsequent measurement accuracy. In addition, the discharge speed adjustment link can also effectively reduce the risk of pipe blockage and sensor data delay effect, thereby enhancing the dynamic response and reliability of the entire discharge stage.

[0036] Secondly, the average value of the discharge pipe pressure after the discharge speed adjustment is obtained through the pressure sensor built-in the discharge pipe of the harvester, if the average value of the discharge pipe pressure is within the set pressure control interval, the monitoring of the average value of the discharge pipe pressure continues, otherwise, it is judged whether the average value of the discharge pipe pressure is greater than the maximum value corresponding to the set pressure control interval.

[0037] If the average value of the discharge pipe pressure is greater than the maximum value corresponding to the set pressure control interval, it indicates that the discharge resistance increases and the accumulation trend appears, and the discharge flow is set down, the specific setting method is: the result of weighting processing of the updated feed stability characterization value and the average value of the discharge pipe pressure is input into the discharge flow down mapping set to output the discharge flow down value for setting down the discharge flow; the weighting processing is to add the product of the feed stability characterization value and the feed stability weight to the product of the average value of the discharge pipe pressure and the discharge pipe pressure weight; the discharge flow down mapping set is obtained by pre-setting the result of weighting processing of the historical feed stability characterization value and the average value of the discharge pipe pressure, and the discharge flow down value set by the professional personnel according to the experience rule, which is used to describe the mapping relationship between the result of weighting processing of the feed stability characterization value and the average value of the discharge pipe pressure and the discharge flow down value.

[0038] Conversely, it indicates that the discharging is insufficient, and the discharging flow is set to be increased. The specific setting method is that the updated feeding stability characteristic value and the result of the weighting processing of the average value of the discharging pipeline pressure are input into the discharging flow increase mapping set to output a discharging flow increase value for setting the discharging flow to be increased. The discharging flow increase mapping set is obtained by pre-setting the result of the weighting processing of the historical feeding stability characteristic value and the average value of the discharging pipeline pressure and the discharging flow increase value set by the professional personnel according to the experience rule, and is used to describe the mapping relationship between the result of the weighting processing of the feeding stability characteristic value and the average value of the discharging pipeline pressure and the discharging flow increase value. The discharging flow adjustment strategy effectively balances the relationship between the discharging speed and the pressure stability, and significantly improves the fluid dynamic stability and data measurement continuity in the discharging stage. Through real-time monitoring and judgment of the average value of the discharging pipeline pressure, adaptive optimization of the discharging flow can be realized. When it is detected that the average value of the pipeline pressure is higher than the upper limit of the set control interval, the discharging flow is set to be decreased, effectively relieving the pipeline accumulation and flow blockage problems; conversely, when the pressure is lower than the lower limit of the set interval, the discharging flow is increased based on the obtained discharging flow increase value, ensuring the discharging continuity and the integrity of the measurement signal.

[0039] In the discharging management strategy optimization adjustment process, the updated feeding stability characteristic value and the average value of the discharging pipeline pressure are analyzed in linkage to realize dynamic judgment and adaptive optimization control in the discharging stage. Through the double-layer adjustment mechanism, the speed and flow can be coordinated and linked and accurately controlled in the discharging stage, which not only effectively improves the flow stability and anti-blocking performance of the discharging process, but also significantly enhances the accuracy and data continuity of the yield measurement link, realizing intelligent closed-loop optimization control of the whole process from feeding to discharging to measurement.

[0040] The measurement accuracy management module is used to determine the measurement accuracy of the yield data of the harvester in the discharging stage during the operation process to obtain a yield measurement accuracy determination result. The module can dynamically determine the measurement accuracy of the yield data in the discharging stage, and evaluate the credibility of the yield data in real time by analyzing the phase delay, signal fluctuation rate and noise interference of the discharging signal. Thus, the measurement error caused by mechanical vibration, sensor delay or grain flow rate change can be effectively identified, and the final uploaded yield data can have higher accuracy and consistency.

[0041] Reference Figure 3 As Figure 3As shown, a measurement accuracy determination logic diagram of the grain yield data management system provided by the embodiment of the present application is provided, and the corresponding logic is as follows: whether the obtained unloading phase lag delay value is greater than the unloading delay lag maximum limit value is determined, if yes, the yield measurement accuracy determination result is determined to be measurement accuracy determination abnormal, the yield measurement collection strategy optimization for improving the yield measurement accuracy is performed first, and then the yield data uploading and storage determination is performed; otherwise, the yield measurement accuracy determination result is determined to be measurement accuracy determination normal, and the unloading amount signal high frequency gain is obtained, if the unloading amount signal high frequency gain is less than the set signal minimum gain, the yield measurement accuracy determination result is updated to be measurement accuracy determination abnormal, otherwise, the unloading phase lag delay value and the unloading amount signal high frequency gain continue to be monitored; wherein, the measurement accuracy of the yield data of the harvester in the unloading stage in the working process is determined, and the specific steps are as follows: N1, the unloading phase lag delay value for reflecting the phase delay of the unloading amount signal is obtained by a timing analysis tool (such as LabVIEW), and the numerical relationship between the unloading phase lag delay value and the stored unloading delay lag maximum limit value is determined.

[0042] N2, if the unloading phase lag delay value is greater than the unloading delay lag maximum limit value, the yield measurement accuracy determination result is determined to be measurement accuracy determination abnormal.

[0043] N3, otherwise, the yield measurement accuracy determination result is determined to be measurement accuracy determination normal, the unloading amount signal high frequency gain is obtained by a spectrum analyzer, and a judgment is made, specifically: if the unloading amount signal high frequency gain is less than the set signal minimum gain, the yield measurement accuracy determination result is updated to be measurement accuracy determination abnormal, otherwise, the unloading phase lag delay value and the unloading amount signal high frequency gain continue to be monitored.

[0044] The detection of the unloading phase lag delay value can accurately reflect the timing offset degree of the unloading signal, and timely discover the signal lag phenomenon caused by the fluctuation of grain flow rate, the blockage of unloading pipeline or mechanical vibration; the monitoring of the unloading amount signal high frequency gain can reveal the response amplitude and stability of the measurement signal, and ensure that the sensor can still effectively capture the instantaneous change under the condition of high-speed flow change. By determining the yield measurement accuracy by combining the above two signal characteristics, the measurement abnormality can be found in the early stage, the low-precision or abnormal data can be avoided to be included in the system database, and thus the credibility and usability of the yield data can be improved.

[0045] The yield data uploading and storage module is used for determining the yield data uploading and storage combined with the yield measurement accuracy determination result, and the specific steps are as follows: If the yield measurement accuracy determination result is measurement accuracy determination normal, the yield data uploading and storage is performed to transmit the yield data to the server.

[0046] If the yield measurement accuracy determination result is a measurement accuracy determination abnormality, the yield measurement data upload storage is performed after the yield measurement collection strategy optimization for improving the yield measurement accuracy.

[0047] It should be noted that the yield measurement collection strategy optimization has the following specific process: First, the optimized coupling result is obtained and input to the yield data collection frequency mapping table to obtain the yield optimization collection frequency after mapping. The optimized coupling result is the result of the arithmetic average of the downfeed phase lag delay value deviation and the downfeed amount signal high frequency gain deviation. The yield data is collected based on the yield optimization collection frequency to improve the response sensitivity of the downfeed signal. The downfeed phase lag delay value deviation is the result of the proportion operation of the absolute value of the difference between the downfeed delay lag maximum limit value and the downfeed phase lag delay value and the downfeed delay lag maximum limit value. The downfeed amount signal high frequency gain deviation is the result of the proportion operation of the difference between the downfeed amount signal high frequency gain and the signal minimum gain and the signal minimum gain. The yield data collection frequency mapping table is obtained by pre-setting the historical optimized coupling result and the yield optimization collection frequency set by the professional personnel according to the experience rule to describe the mapping relationship between the optimized coupling result and the yield optimization collection frequency. The yield optimization collection frequency is dynamically adjusted based on the optimized coupling result to automatically improve the sampling density when the signal fluctuation intensifies or the measurement delay increases, thereby reducing the data loss probability and ensuring the yield measurement signal integrity and continuity in the downfeed stage.

[0048] Secondly, the yield measurement accuracy determination result is reacquired. If the reacquired yield measurement accuracy determination result is a measurement accuracy determination normality, a measurement strategy optimization qualified prompt is sent. Otherwise, the optimized coupling result difference value before and after the yield measurement collection strategy optimization is input to the collection frequency optimization mapping table to output the collection frequency optimization multiple. The optimized coupling result difference value is the difference between the optimized coupling results before and after the yield measurement collection strategy optimization. The collection frequency optimization mapping table is obtained by pre-setting the historical optimized coupling result difference value and the collection frequency optimization multiple set by the professional personnel according to the experience rule. The collection frequency multiple is adjusted by calculating the optimized coupling result difference value before and after the yield measurement collection strategy optimization and inputting it, thereby realizing the adaptive optimization closed-loop adjustment of the collection frequency. When the measurement accuracy abnormality is detected, the sampling strategy can be automatically adjusted until the set accuracy condition is met or the abnormality prompt is triggered, thereby ensuring that the system can maintain a stable and reliable collection state under different working conditions.

[0049] It is judged whether the yield optimization collection frequency is greater than the set collection frequency maximum limit value. If yes, a yield data collection frequency adjustment abnormality prompt is sent. Otherwise, the yield optimization collection frequency is adjusted by the collection frequency optimization multiple until the yield data collection frequency adjustment abnormality prompt is sent or the yield data upload storage is performed.

[0050] The introduction of the yield measurement acquisition strategy optimization can realize adaptive optimization adjustment of the yield data acquisition frequency on the unloading signal characteristics, significantly improve the signal response capability and measurement accuracy of the harvester in the yield data measurement process, reduce the data distortion risk, and ensure the authenticity and reliability of the yield data acquisition.

[0051] As shown in Figure 4 The method includes: feed stage management, unloading stage management, and yield data management. Specifically, the feed stage management: detecting the feed stability of the harvester in the feed stage during the operation to obtain a feed management detection result, and feeding back; the unloading stage management: determining whether to trigger the unloading management strategy adjustment for improving the yield measurement accuracy of the harvester according to the feed management detection result, if not, determining the measurement accuracy of the yield data of the harvester in the unloading stage during the operation to obtain a yield measurement accuracy determination result, if yes, determining whether to determine the measurement accuracy of the yield data of the harvester in the unloading stage during the operation to obtain a yield measurement accuracy determination result after the unloading management strategy adjustment; and the yield data management: determining the yield data uploading and storage according to the yield measurement accuracy determination result.

[0052] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0053] The present application is described with reference to flowcharts and / or block diagrams of the system, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks.

[0054] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0056] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to cover all such additional variations and modifications as fall within the scope of the present application.

[0057] It is apparent that a person skilled in the art could make various changes and modifications to the application without departing from the spirit and scope thereof. Thus, if these modifications and changes fall within the scope of the claims and their equivalents, it is intended to include them in the scope of the application.

[0058] The above merely illustrates the specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A harvester grain yield data management system characterized by, The system comprises: The feeding stage management module is used for detecting the feeding stability of the harvester in the feeding stage during the operation process to obtain a feeding management detection result, and feeding back to the discharging stage management module; The discharging stage management module is used for judging whether to trigger a discharging management strategy adjustment for improving the measurement accuracy of the grain yield of the harvester according to the received feeding management detection result, if not triggering the discharging management strategy adjustment, triggering the operation of the measurement precision management module, if triggering the discharging management strategy adjustment, judging whether to trigger the operation of the measurement precision management module after the discharging management strategy adjustment is performed; The measurement precision management module is used for judging the measurement precision of the yield data of the harvester in the discharging stage during the operation process to obtain a yield measurement precision judgment result; The yield data uploading and storage module is used for judging the uploading and storage of the yield data in combination with the yield measurement precision judgment result.

2. A harvester grain yield data management system according to claim 1 wherein, The detection of the feeding stability of the harvester in the feeding stage during the operation process comprises the following specific steps: Based on the feeding amount data obtained in the feeding time interval, the feeding amount standard deviation and the average feeding amount are obtained, the feeding stability correlation quantity is quantified by feeding the two, the feeding fluctuation rate is obtained, and the result of inverse proportion processing is taken as the feeding stability representation value for representing the feeding stability; Judging the numerical relationship between the feeding stability representation value and the stored feeding stability reference limit value; If the feeding stability representation value is greater than the feeding stability reference limit value, the feeding management detection result is recorded as feeding detection up to standard, and the obtained feeding stability representation value is continuously monitored; If the feeding stability representation value is not greater than the feeding stability set limit value, the feeding stability representation value is compared with the stored feeding control reference interval, specifically: if the feeding stability representation value is within the feeding control reference interval, the feeding management detection result is recorded as feeding detection qualified, otherwise, the feeding management detection result is recorded as feeding detection not up to standard; The feeding control reference interval is a closed interval corresponding to the feeding stability reference limit value to the feeding stability set limit value.

3. A harvester grain yield data management system according to claim 2, wherein, The detection of the feeding stability of the harvester in the feeding stage during the operation process further comprises: Obtaining the header working speed of the harvester during the operation process in the feeding time interval, and quantifying the deviation of the header working speed from the stored operation reference speed to obtain a header working speed deviation value; Judging the numerical relationship between the header working speed deviation value and the stored header speed deviation interval, the header speed deviation interval is a closed interval corresponding to the set speed minimum deviation to the set speed maximum deviation; If the header working speed deviation value is within the header speed deviation interval, the feeding stability representation value is not processed, otherwise, the feeding stability representation value is processed, specifically: the feeding stability representation value is processed based on the introduced operation speed factor, the feeding stability representation value is updated according to the processing result, and the operation speed factor is used to correct the influence of the header working speed on the feeding stability detection.

4. A harvester grain yield data management system according to claim 2, wherein, The specific process of judging whether to trigger the discharging management strategy adjustment for improving the measurement accuracy of the grain yield of the harvester according to the received feeding management detection result is as follows: determining whether the feeding management detection result is up to standard; if yes, not triggering the discharge management strategy adjustment; if no, triggering the feeding management strategy benchmark adjustment, and triggering the discharge management strategy optimization adjustment. The discharge management strategy adjustment includes the feeding management strategy benchmark adjustment for dynamically optimizing the feeding stage stability by controlling the feeding speed and the feeding flow, and the discharge management strategy optimization adjustment for dynamically optimizing the discharge stage stability by controlling the discharge speed and the discharge flow.

5. A harvester grain yield data management system according to claim 4 wherein, The feeding management strategy benchmark adjustment includes the following steps: inputting the feeding stability characterization value into the feeding speed mapping table to output the header feeding adjustment speed, and sending a prompt for adjusting the header feeding speed according to the output header feeding adjustment speed; after adjusting the header feeding speed, obtaining the feeding management detection result in the next feeding time interval, and determining whether the feeding management detection result in the next feeding time interval is up to standard, and triggering the measurement accuracy management module if yes; if the feeding management detection result in the next feeding time interval is up to standard, triggering the measurement accuracy management module; if the feeding management detection result in the next feeding time interval is up to standard, performing arithmetic coupling processing on the feeding stability characterization values corresponding to the two feeding time intervals, inputting the feeding stability characterization values into the feeding flow mapping table to output the feeding adjustment flow, and setting the initial feeding flow according to the output feeding adjustment flow; if the feeding management detection result in the next feeding time interval is abnormal, sending a prompt for adjusting the header feeding speed, returning to the header feeding speed before adjustment, and triggering the discharge management strategy optimization adjustment.

6. A harvester grain yield data management system according to claim 4 wherein, The discharge management strategy optimization adjustment includes the following steps: if the feeding management strategy benchmark adjustment is triggered, updating the feeding stability characterization value, otherwise, directly using the feeding stability characterization value as the updated feeding stability characterization value, inputting the updated feeding stability characterization value into the discharge speed mapping table to output the discharge adjustment speed, and adjusting the discharge speed according to the output discharge adjustment speed; obtaining the average discharge pipeline pressure after adjusting the discharge speed, if the average discharge pipeline pressure is within the set pressure control interval, continuing to monitor the average discharge pipeline pressure, otherwise, determining whether the average discharge pipeline pressure is greater than the maximum value corresponding to the set pressure control interval; if the average discharge pipeline pressure is greater than the maximum value corresponding to the set pressure control interval, indicating that the discharge is in the accumulation trend, and the discharge flow is set down, and the specific setting method is: inputting the result of weighting the updated feeding stability characterization value and the average discharge pipeline pressure into the discharge flow down mapping set to output the discharge flow down value for setting the discharge flow down; otherwise, indicating that the discharge is insufficient, and the discharge flow is set up, and the specific setting method is: inputting the result of weighting the updated feeding stability characterization value and the average discharge pipeline pressure into the discharge flow up mapping set to output the discharge flow up value for setting the discharge flow up.

7. A harvester grain yield data management system according to claim 4 wherein, The measurement accuracy of the harvester yield data in the discharge stage during the working process is determined, and the specific steps are as follows: acquire a discharging phase lag delay value reflecting a phase delay of the discharging amount signal, and determine a numerical relationship between the discharging phase lag delay value and a stored maximum limit value of the discharging delay lag; if the discharging phase lag delay value is greater than the maximum limit value of the discharging delay lag, the measurement accuracy determination result is determined to be abnormal; otherwise, the measurement accuracy determination result is determined to be normal, and a high-frequency gain of the discharging amount signal is acquired and determined, specifically: if the high-frequency gain of the discharging amount signal is less than a set minimum gain of the signal, the measurement accuracy determination result is updated to be abnormal, otherwise, the discharging phase lag delay value and the high-frequency gain of the discharging amount signal continue to be monitored.

8. A harvester grain yield data management system according to claim 7, wherein, The determination of uploading and storing the yield data in combination with the yield measurement accuracy determination result includes the following steps: if the yield measurement accuracy determination result is normal, the yield data is uploaded and stored to transmit the yield data to the server; if the yield measurement accuracy determination result is abnormal, the yield measurement collection strategy optimization for improving the yield measurement accuracy is performed before the determination of uploading and storing the yield data.

9. A harvester grain yield data management system according to claim 8, wherein, The yield measurement collection strategy optimization includes the following steps: an optimized coupling result is acquired and input to a yield data collection frequency mapping table for mapping to obtain a yield optimized collection frequency, the optimized coupling result is the result of the arithmetic average of the discharging phase lag delay value deviation and the high-frequency gain deviation of the discharging amount signal, and the yield data is collected based on the yield optimized collection frequency to improve the response sensitivity to the discharging signal; if the newly acquired yield measurement accuracy determination result is normal, a measurement strategy optimization qualified prompt is sent, otherwise, the difference value between the optimized coupling results before and after the yield measurement collection strategy optimization is input to a collection frequency optimization mapping table to output a collection frequency optimization multiple, and it is determined whether the yield optimized collection frequency is greater than a set maximum limit value of the collection frequency, if yes, a yield data collection frequency adjustment abnormal prompt is sent, otherwise, the yield optimized collection frequency is adjusted by the collection frequency optimization multiple until the yield data collection frequency adjustment abnormal prompt is sent or the yield data is uploaded and stored.

10. A method for managing grain yield data of a harvester, applied to the system for managing grain yield data of a harvester according to any one of claims 1 to 9, characterized by, The method includes the following steps: detect the feeding stability of the harvester in the feeding stage during the operation to acquire a feeding management detection result, and feed back the result; determine whether to trigger a discharging management strategy adjustment for improving the accuracy of the grain yield measurement of the harvester according to the feeding management detection result, if not, determine the measurement accuracy of the yield data of the harvester in the discharging stage during the operation to acquire a yield measurement accuracy determination result, if yes, determine whether to determine the measurement accuracy of the yield data of the harvester in the discharging stage during the operation to acquire a yield measurement accuracy determination result after the discharging management strategy adjustment; determine the uploading and storing of the yield data in combination with the yield measurement accuracy determination result.

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