Corn seeding monitoring method and equipment for no-tillage corn planter

Abstract

This application relates to the technical field of corn seeding monitoring, specifically to a corn seeding monitoring method and device for no-till corn planters, which specifically includes: collecting the initial time and end time when infrared rays are blocked by corn each time during the fall of corn in the no-till corn planter based on infrared sensing technology; obtaining normal data in the infrared blocking duration based on the differences between elements in the infrared blocking duration sequence and elements in the corresponding neighborhood; constructing a corn seeding detection sequence based on the normal data, calculating the rotation period of the wheel groove, and dividing the corn seeding detection sequence to obtain each subsequence; calculating the faulty seeding amount of each subsequence by analyzing the element changes in each subsequence; and intelligently monitoring the missed seeding and repeated seeding situations during the corn seeding process through the faulty seeding amount, avoiding the inability to monitor the time of missed seeding in the existing corn seeding monitoring methods, and being able to effectively improve the accuracy and efficiency of corn seeding monitoring.

Description

Technical Field

[0001] This application relates to the technical field of corn sowing monitoring, and specifically to a corn sowing monitoring method and device for no-till corn planters. Background Art

[0002] Agriculture is one of the most important cornerstones of a country. In the central region of our country, crops are usually planted twice a year. The growth cycle of corn is from mid-May to September of the current year, and the growth cycle of wheat is from October of the previous year to early May of the next year. For corn planting, it is usually carried out with stubble sowing after wheat harvesting, implementing no-till planting of corn. However, due to the wheat stubble, when carrying out side-position trenching and sowing, it is easy to cause poor soil covering in the sowing trench, and the soil covering depth of the seeds is uneven, resulting in a low emergence rate of corn seeds. Therefore, it is necessary to monitor the sowing of corn seeds to avoid replanting corn later.

[0003] For traditional detection techniques of corn sowing, generally when corn seeds are sown, the missing sowing rate of corn seeds is calculated by the ratio of the corn seed sowing amount to the sowing time to achieve the detection of missing sowing during corn sowing. However, when a no-till corn planter is sowing, sowing may not only be missing due to being stuck in the wheel groove recess, but also repeated sowing may occur due to damage to the sowing device. As a result, when the traditional technique is used to detect corn sowing, it is impossible to accurately detect the time of missing sowing and repeated sowing, leading to inaccurate detection results when detected by the traditional technique. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a corn sowing monitoring method and device for no-till corn planters, and the specific technical solutions adopted are as follows:

[0005] In the first aspect, an embodiment of this application provides a corn sowing monitoring method for a no-till corn planter, and this method includes the following steps:

[0006] Collect the initial moment and the end moment when infrared rays are blocked by corn each time during the fall of corn in the no-till corn planter through an infrared sensor, and use them as the blocking time period when infrared rays are blocked each time;

[0007] Obtain the infrared blocking duration each time infrared rays are blocked, and construct an infrared blocking duration sequence; construct the time length difference value of each infrared blocking duration based on the difference between each element in the infrared blocking duration sequence and the elements in the corresponding neighborhood;

[0008] Obtain the normal data in the infrared blocking duration based on the time length difference values of each infrared blocking duration, and construct a corn sowing detection sequence based on the blocking time periods corresponding to the normal data;

[0009] Calculate the rotation period of the wheel groove based on the element size distribution in the corn seeding detection sequence and the number of grooves on the seeding machine wheel groove; segment the corn seeding detection sequence based on the rotation period of the wheel groove to obtain each subsequence;

[0010] Calculate the seeding recommendation amount for each subsequence based on the element change range in each subsequence; construct the faulty seeding amount for each subsequence based on the numerical relationship between the seeding recommendation amount and the number of elements in each subsequence, in combination with the number of grooves on the wheel groove;

[0011] Monitor corn seeding based on the faulty seeding amount of each subsequence.

[0012] In one embodiment, the expression for the difference value of the duration of each infrared blocking is:

[0013] , where represents the difference value of the duration of the i-th infrared blocking; represents the median function; represents the infrared blocking duration sequence; represents the i-th infrared blocking duration; n represents the number of elements in the neighborhood of the i-th infrared blocking duration; represents the j-th element in the neighborhood of the i-th infrared blocking duration.

[0014] In one embodiment, the process of obtaining the normal data in the infrared blocking duration is:

[0015] Take all the difference values of the duration of the infrared blocking as the input of the threshold segmentation algorithm, and the output is the segmentation threshold; record the infrared blocking duration with the difference value less than the segmentation threshold as normal data.

[0016] In one embodiment, the corn seeding detection sequence is: the sequence composed of the initial moments of all the blocking time periods corresponding to the normal data.

[0017] In one embodiment, the process of obtaining the rotation period of the wheel groove is:

[0018] Calculate the difference amount between two adjacent initial moments in the corn seeding detection sequence; take the mode of all the difference amounts in the corn seeding detection sequence as the seeding time interval during normal corn seeding; multiply the seeding time interval by the number of grooves on the wheel groove as the rotation period of the wheel groove.

[0019] In one embodiment, the process of obtaining each subsequence is:

[0020] In the corn seeding detection sequence, each segmentation point is obtained. Based on each segmentation point, each subsequence is obtained. Specifically, the obtaining of the segmentation point is as follows: the time difference between the segmentation point and the starting element is greater than or equal to the grooved wheel rotation period, and the time difference between the previous element of the segmentation point and the starting element is less than the grooved wheel rotation period. The obtained segmentation point is repeatedly used as the starting element, and the elements after the latest segmentation point are traversed to obtain the remaining segmentation points. When obtaining the first segmentation point, the starting element is the first element in the corn seeding detection sequence.

[0021] In one embodiment, the expression of the seeding recommendation amount is:

[0022] , where represents the seeding recommendation amount of the k-th subsequence; and respectively represent the last element and the first element in the k-th subsequence; t is the seeding time interval; represents the function of rounding to the absolute value.

[0023] In one embodiment, the expression of the faulty seeding amount is:

[0024] , where represents the faulty seeding amount of the k-th subsequence; represents the seeding recommendation amount of the k-th subsequence; represents the number of elements in the k-th subsequence; B represents the number of grooves on the grooved wheel.

[0025] In one embodiment, the process of monitoring corn seeding based on the faulty seeding amounts of each subsequence is as follows:

[0026] If the faulty seeding amount of each subsequence is positive, the seeding time periods corresponding to all elements in each subsequence are marked as missed seeding; if the faulty seeding amount of each subsequence is 0, the seeding time periods corresponding to all elements in each subsequence are marked as no abnormality; if the faulty seeding amount of each subsequence is negative, the seeding time periods corresponding to all elements in each subsequence are marked as repeated seeding.

[0027] In a second aspect, the embodiments of the present application further provide a corn seeding monitoring device for a no-till corn planter, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0028] The embodiments of the present application at least have the following beneficial effects:

[0029] The present application collects the initial and end times of each time when the infrared rays are blocked by corn when the corn falls in a corn no-till planter based on infrared sensing technology, so as to analyze the dynamic characteristics of corn seed sowing; obtains normal data in the infrared blocking time based on the difference between each element in the infrared blocking time sequence and the elements in the corresponding neighborhood, thereby avoiding the influence of noise data caused by vibration interference and the like, and improving the accuracy of subsequent data processing results; constructs a corn sowing detection sequence based on normal data, calculates the wheel groove rotation period, and divides the corn sowing detection sequence into subsequences, which is helpful to identify missed sowing and repeated sowing phenomena under different environmental conditions; calculates the faulty sowing amount of each subsequence by analyzing the changes in elements in each subsequence, evaluates the sowing quality of seeds, and can effectively distinguish between reseeding and missed sowing of seeds; performs intelligent monitoring of missed sowing and repeated sowing in the corn sowing process through the faulty sowing amount, thereby improving the search speed of abnormal sowing time periods, thereby improving the accuracy and efficiency of corn sowing monitoring under various operating conditions, avoiding the inability to monitor the time when missed sowing occurs in the corn sowing monitoring method in the prior art, and can effectively improve the accuracy and efficiency of corn sowing monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A flowchart of a method for monitoring corn sowing of a corn no-tillage planter provided in accordance with an embodiment of the present application;

[0032] Figure 2 Schematic diagram of the process of obtaining the wheel groove rotation period. DETAILED DESCRIPTION

[0033] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the corn sowing monitoring method and device of the corn no-tillage planter proposed in the present application, its specific implementation method, structure, features and effects are described in detail as follows in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0034] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0035] The following specifically describes the specific solutions of the corn seeding monitoring method and device for the no-till corn planter provided by this application in conjunction with the accompanying drawings.

[0036] Please refer to Figure 1 , which shows the step flowchart of the corn seeding monitoring method for the no-till corn planter provided by an embodiment of this application. The method includes the following steps:

[0037] Step S1, collect the initial moment and the end moment when the infrared ray is blocked by the corn each time when the corn falls in the no-till corn planter through the infrared sensor, and use them as the blocking time period when the infrared ray is blocked each time.

[0038] The no-till corn planter includes a straw crushing cutter shaft, a seeding furrow opener, a fertilizer furrow opener, and a corn seeder. Among them, the straw crushing cutter shaft is used to crush the straw in the soil to prevent the straw from blocking the planter; the seeding furrow opener is used to open a furrow in the soil for seeding the seeds; the fertilizer furrow opener is used to open a furrow in the soil for spreading the chemical fertilizer; the corn seeder is used to seed the corn seeds.

[0039] In order to monitor the corn seeding situation of the no-till corn planter, an infrared sensor is installed on the seeding tube of the planter. The transmitting end of the infrared sensor emits infrared rays, and the receiving end receives the infrared rays. When the corn seeds are being sown, the falling corn seeds will block the infrared ray reception of the receiving end. Record the initial moment and the end moment when the infrared ray is blocked each time to obtain the time period when the infrared ray is blocked each time, which is recorded as each blocking time period; for example, if the initial moment when a certain infrared ray is blocked is the 3rd second and the end moment is the 4th second, then the blocking time period for this time is the 3 - 4th second.

[0040] Arrange all the blocking time periods of the infrared ray in ascending order according to the corresponding time, and the formed sequence is recorded as the seeding detection sequence.

[0041] Step S2, obtain the infrared blocking duration when the infrared ray is blocked each time, and construct an infrared blocking duration sequence; construct the time length difference value of each infrared blocking duration based on the difference between each element in the infrared blocking duration sequence and the elements in the corresponding neighborhood.

[0042] For the seeding of the no-till corn planter, since corn needs sufficient sunlight during the growth process, therefore, in the seeding of corn, repeated seeding will cause the nutrients to be divided, resulting in a reduction in corn yield; missed seeding will directly lead to a decrease in yield.

[0043] During the process of sowing corn, the corn to be sown is stored in the seed box of the seeder. Then, the corn seeds are grabbed through the wheel groove of the seed metering device in the seeder, and the corn seeds are transported to the sowing tube through the rotating wheel groove. Since a no-till corn planter is usually mounted on a tractor, during the process of sowing corn seeds, the machine will vibrate, resulting in vibration interference in the data collected by the infrared sensor. However, the vibration interference is usually short-term or instantaneous, while the blocking effect time of corn seeds on the infrared sensor is relatively long.

[0044] Therefore, for each blocking time period of the infrared sensor, the end time of the blocking time period is subtracted from the start time to obtain the infrared blocking duration; for example, if the blocking time period of a certain infrared ray is from the 3rd second to the 4th second, then the infrared blocking duration of this time is 1 second.

[0045] Arrange all the infrared blocking durations in ascending order of time according to the corresponding blocking time periods, and the obtained sequence is denoted as the infrared blocking duration sequence. In the infrared blocking duration sequence, construct the neighborhood of each element. Preferably, in an embodiment of the present application, the neighborhood of each element is set to the 5 elements closest to each element. As other embodiments of the present application, the implementer can set the neighborhood of each element according to the actual situation.

[0046] Used to characterize the change characteristics of the blocking time of the blocking time period. When the element in the infrared blocking duration sequence is formed by vibration interference, its value is quite different from the infrared blocking duration formed by corn. Therefore, calculate the time length difference value of each infrared blocking duration through the time difference set of the infrared blocking durations. The expression is:

[0047] ;

[0048] In the formula, represents the time length difference value of the i-th infrared blocking duration; represents the median function; represents the infrared blocking duration sequence; represents the i-th infrared blocking duration; n represents the number of elements in the neighborhood of the i-th infrared blocking duration; represents the j-th element in the neighborhood of the i-th infrared blocking duration.

[0049] If the difference between the infrared blocking duration and each element in its neighborhood is large, it indicates that this infrared blocking duration is formed by vibration interference. This is because when vibration interference occurs, the duration is short. Therefore, the difference between the infrared blocking duration formed by vibration interference and the normal infrared blocking duration will be large. Therefore, has a large value; at the same time, the difference between the noise infrared blocking duration generated by vibration interference and the normal infrared blocking duration The value will be relatively large, resulting in a relatively large difference in the length of the infrared blocking duration. By using the local feature differences and overall feature differences of the infrared blocking duration, it is possible to effectively avoid the situation where all elements in the time difference set are caused by vibration interference in extreme cases, making the identification of whether the infrared blocking duration is normal or caused by vibration interference more accurate.

[0050] Step S3: Obtain the normal data in the infrared blocking duration based on the difference values of the lengths of each infrared blocking duration, and construct a corn sowing detection sequence based on the blocking time periods corresponding to the normal data.

[0051] The difference value of the length of the infrared blocking duration in the case of vibration interference is much larger than that of the normal infrared blocking duration. Therefore, taking the difference values of the lengths of all infrared blocking durations as the input of the maximum inter-class variance algorithm, the output segmentation threshold is denoted as the vibration interference recognition threshold, which is used to segment the infrared blocking data of corn sowing and the infrared blocking data of vibration interference. Among them, the maximum inter-class variance algorithm is a well-known technology, and the specific process will not be elaborated here.

[0052] It should be noted that for the acquisition of the segmentation threshold of the difference values of the lengths of all infrared blocking durations, this application only provides a threshold segmentation method. There are many existing threshold segmentation methods, and implementers can also use other threshold segmentation algorithms to obtain the segmentation threshold of the difference values of the lengths of all infrared blocking durations. This application does not make specific restrictions.

[0053] The infrared blocking durations with difference values of the length greater than or equal to the vibration interference recognition threshold are recorded as vibration interference data, and the infrared blocking durations less than the vibration interference recognition threshold are recorded as normal data.

[0054] Delete the blocking time periods corresponding to all vibration interference data from the sowing detection sequence to obtain a new sequence; denote the sequence composed of the initial moments corresponding to all blocking time periods in this new sequence in order as the corn sowing detection sequence.

[0055] Step S4: Calculate the wheel groove rotation period based on the element size distribution in the corn sowing detection sequence and the number of grooves on the sowing machine wheel groove; segment the corn sowing detection sequence based on the wheel groove rotation period to obtain each subsequence.

[0056] When the sowing machine is affected by vibration and the wheel groove fails to successfully grasp the seeds, it can be observed that the initial time interval between two seeds passing through the infrared sensor is abnormally extended. In addition, if the wheel groove is stuck by corn seeds, this will prevent the normal passage of the seeds, resulting in a significant increase in the time interval detected by the infrared sensor between the seeds. And the phenomenon of missed sowing caused by vibration usually lasts for a short time, while the missed sowing caused by the wheel groove being stuck by seeds may last for a long time.

[0057] During the operation of the seeder, since there are multiple grooves designed on the wheel groove, every time the wheel groove completes a full rotation, multiple corn seeds can be sown. If a certain groove in the wheel groove fails to sow corn seeds successfully due to a malfunction or an obstacle, that is, a missed sowing phenomenon occurs. However, due to the large number of grooves on the wheel groove, the normally sown corn seeds still account for the vast majority. Therefore, for the interval differences between the initial moments of all adjacent two corn blockages in the corn sowing detection sequence, the mode is generated by normal corn sowing.

[0058] Therefore, calculate the difference amount between two adjacent initial moments in the corn sowing detection sequence, denoted as the first difference amount. In the embodiments of the present application, the first difference amount is the absolute value of the difference between the two adjacent initial moments; take the mode of all the first difference amounts in the corn sowing detection sequence as the sowing time interval during normal corn sowing, denoted as t.

[0059] Denote the number of grooves on the wheel groove as m, then the time for the wheel groove to rotate one week is , and denote this time as the wheel groove rotation period.

[0060] Segment the corn sowing detection sequence according to this wheel groove rotation period to obtain each subsequence, denoted as each corn sowing component sequence. Specifically:

[0061] In the corn sowing detection sequence, obtain each segmentation point therein. Based on each segmentation point, obtain each subsequence. Among them, the acquisition of the segmentation point is specifically: the segmentation point satisfies that the time difference from the starting element is greater than or equal to the wheel groove rotation period, and the element before the segmentation point satisfies that the time difference from the starting element is less than the wheel groove rotation period. Take the obtained segmentation point as the starting element repeatedly, and traverse the elements after the latest segmentation point to obtain the remaining segmentation points. Among them, when obtaining the first segmentation point, the starting element is the first element in the corn sowing detection sequence. Denote each subsequence as each corn sowing component sequence. This segmentation method helps to identify missed sowing and repeated sowing phenomena under different environmental conditions.

[0062] Step S5, calculate the sowing recommendation amount for each subsequence based on the element change range in each subsequence; based on the numerical relationship between the sowing recommendation amount and the number of elements in each subsequence, combined with the number of grooves on the wheel groove, construct the faulty sowing amount for each subsequence.

[0063] Under normal circumstances, the number of elements in each corn sowing component sequence should be the same as the number of grooves on the wheel groove of the corn seeder. If the number of elements in each corn sowing component sequence is less than the number of grooves on the wheel groove, it indicates that a missed sowing phenomenon has occurred in the corn seeder; when the number of elements in the corn sowing component sequence is greater than the number of grooves on the wheel groove, it indicates that a repeated sowing phenomenon has occurred in the corn seeder.

[0064] Therefore, based on the above analysis, calculate the seeding recommendation amount for each corn seeding component sequence, and the expression is:

[0065] ;

[0066] In the formula, represents the seeding recommendation amount for the k-th corn seeding component sequence; , respectively represent the last element and the first element in the k-th corn seeding component sequence; t is the seeding time interval when the corn is normally sown; represents the function of rounding to the absolute value.

[0067] Furthermore, calculate the faulty seeding amount for each corn seeding component sequence, and the expression is:

[0068] ;

[0069] In the formula, represents the faulty seeding amount for the k-th corn seeding component sequence; represents the seeding recommendation amount for the k-th corn seeding component sequence; represents the number of elements in the k-th corn seeding component sequence; B represents the number of grooves on the sheave.

[0070] When the corn seeder has missed seeding or repeated seeding, the difference between the number of elements in the corn seeding component sequence of the corn seeder and the number B of the grooves is relatively large. When the time difference between the last element and the first element in the corn seeding component sequence and the seeding time interval t when the corn is normally sown is larger, it indicates that the value of the seeding recommendation amount is larger within the seeding time period of the corn seeding component sequence. When the value of the seeding recommendation amount within this time period is greater than or equal to the number of elements in the corn seeding component sequence, it indicates that the number of missed seeding within this time period is more. Therefore, the difference between the seeding recommendation amount and the standard seeding amount of the corn seeder is larger, indicating that the possibility of being blocked during corn seeding is greater. When the seeding recommendation amount of the corn seeding component sequence is less than the number of elements in the corn seeding component sequence, that is , it indicates that the phenomenon of repeated seeding occurs in the corn seeder within this time period, which may be due to excessive single seeding amount caused by damage to the seed metering of the seeder.

[0071] Step S6, perform corn seeding monitoring based on the faulty seeding amounts of each subsequence.

[0072] For the faulty seeding amount in the above corn seeding component sequence, the calculation result of the faulty seeding amount directly reflects the abnormal situation during the seeding process: when the faulty seeding amount is positive, it indicates that within the time period of this corn seeding component sequence, the number of seeds sown by the seeder is less than expected, that is, there is a missing seeding phenomenon, which may be caused by insufficient seed supply or mechanical failure; when the faulty seeding amount is zero, it means that the number of seeds sown by the seeder within this time period is consistent with the expectation, and the seeding process is normal without any abnormality; while when the faulty seeding amount is negative, it indicates that within this time period, the number of seeds sown by the seeder is more than expected, that is, double seeding has occurred, which may be caused by improper adjustment or operation error of the seeding machinery.

[0073] Therefore, the seeding time periods of the corn seeding component sequence are marked as missing seeding, normal, and double seeding respectively. If the faulty seeding amount of each subsequence is positive, the seeding time periods corresponding to all elements in each subsequence are marked as missing seeding; if the faulty seeding amount of each subsequence is 0, the seeding time periods corresponding to all elements in each subsequence are marked as no abnormality; if the faulty seeding amount of each subsequence is negative, the seeding time periods corresponding to all elements in each subsequence are marked as double seeding. Thus, the detection of corn seeding is realized.

[0074] The schematic diagram of the acquisition process of the grooved wheel rotation period is as Figure 2 shown.

[0075] Based on the same inventive concept as the above method, the embodiment of the present application also provides a corn seeding monitoring device for a corn no-till seeder, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above corn seeding monitoring methods for the corn no-till seeder.

[0076] In summary, the embodiment of the present application provides a maize seeding monitoring method for a no-till maize planter. By using infrared sensing technology, the initial and end times when infrared rays are blocked by maize each time during the fall of maize in the no-till maize planter are collected, which are used to analyze the dynamic characteristics of maize seed sowing. Based on the differences between the elements in the infrared blocking duration sequence and the elements in the corresponding neighborhood, the normal data in the infrared blocking duration are obtained, avoiding the influence of noise data caused by vibration interference, etc., and improving the accuracy of subsequent data processing results. Based on the normal data, a maize seeding detection sequence is constructed, the rotation period of the wheel groove is calculated, and the maize seeding detection sequence is divided into each subsequence, which helps to identify missed seeding and repeated seeding phenomena under different environmental conditions. By analyzing the element changes in each subsequence, the faulty seeding amount of each subsequence is calculated, and the seeding quality of the seeds is evaluated, which can effectively distinguish between reseeding and missed seeding of the seeds. Through the faulty seeding amount, the missed seeding and repeated seeding situations during the maize seeding process are intelligently monitored, improving the search speed for abnormal seeding periods, thereby enhancing the accuracy and efficiency of maize seeding monitoring under various operating conditions, avoiding the situation in the prior art maize seeding monitoring method where the time of missed seeding cannot be monitored, and effectively improving the accuracy and efficiency of maize seeding monitoring.

[0077] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of the present application have been described. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0078] Each embodiment in the present application is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key point of each embodiment is to illustrate the differences from other embodiments.

[0079] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principle of the present application shall be included in the protection scope of the present application.

Claims

1. A corn sowing monitoring method for a corn no-tillage seeder, characterized in that: The method comprises the following steps: The infrared sensor is used to collect the initial time and the end time of each time when the infrared rays are blocked by the corn when the corn falls in the corn no-tillage planter, as the blocking time period of each time when the infrared rays are blocked; Obtain the infrared blocking duration each time the infrared rays are blocked, and construct an infrared blocking duration sequence; construct the time difference value of each infrared blocking duration based on the difference between each element in the infrared blocking duration sequence and the elements in the corresponding neighborhood, wherein the neighborhood is a preset number of elements closest to each element; Based on the difference value of each infrared blocking time, normal data in the infrared blocking time is obtained, and a corn sowing detection sequence is constructed based on the blocking time period corresponding to the normal data; Calculate the difference between two adjacent initial moments in the corn sowing detection sequence, and use the mode of all the differences as the sowing time interval during normal corn sowing; and use the product of the sowing time interval and the number of grooves on the wheel groove as the wheel groove rotation period; Obtain each segmentation point in the corn sowing detection sequence, specifically: the segmentation point satisfies that the time difference between the segmentation point and the starting element is greater than or equal to the wheel groove rotation period, and the previous element of the segmentation point satisfies that the time difference between the segmentation point and the starting element is less than the wheel groove rotation period, and the obtained segmentation point is repeatedly used as the starting element, and the elements after the latest segmentation point are traversed to obtain the remaining segmentation points, wherein when the first segmentation point is obtained, the starting element is the first element in the corn sowing detection sequence; Based on each segmentation point, each subsequence is obtained; Calculate the recommended sowing amount for each subsequence, the expression is: , where represents the recommended seeding amount for the kth subsequence; , represent the last element and the first element in the kth subsequence respectively; t is the sowing time interval; represents the rounding absolute value function; the expression for constructing the fault seeding amount of each subsequence is: , where represents the fault seeding amount of the kth subsequence; represents the recommended seeding amount for the kth subsequence; represents the number of elements in the kth subsequence; B represents the number of grooves on the wheel groove; If the fault seeding amount of each subsequence is positive, the seeding time period corresponding to all elements in each subsequence is marked as missed seeding; if the fault seeding amount of each subsequence is 0, the seeding time period corresponding to all elements in each subsequence is marked as normal; if the fault seeding amount of each subsequence is negative, the seeding time period corresponding to all elements in each subsequence is marked as repeated seeding.

2. The corn sowing monitoring method of the corn no-tillage seeder according to claim 1, characterized in that: The expression for the difference in the duration of each infrared blocking time is: , where Indicates the time difference value of the i-th infrared blocking duration; Represents the median function; Indicates infrared blocking duration sequence; represents the i-th infrared blocking duration; n represents the number of elements in the neighborhood of the i-th infrared blocking duration; Represents the jth element in the neighborhood of the i-th infrared blocking duration.

3. The corn sowing monitoring method of the corn no-tillage seeder according to claim 1, characterized in that: The process of obtaining normal data during the infrared blocking time is as follows: The time difference values ​​of all infrared blocking durations are used as the input of the threshold segmentation algorithm, and the output is the segmentation threshold; the infrared blocking duration whose time difference value is less than the segmentation threshold is recorded as normal data.

4. The corn sowing monitoring method of the corn no-tillage seeder according to claim 1, characterized in that: The corn sowing detection sequence is a sequence composed of the initial moments of the blocking time periods corresponding to all normal data.

5. A corn sowing monitoring device for a corn no-tillage planter, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

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