Intelligent brake method, system and fishing reel

Abstract

The application discloses an intelligent brake method, system and fishing reel. The method comprises the following steps: collecting real-time casting data of the fishing reel when casting; identifying a current casting posture and / or a current bait type according to the real-time casting data, and confirming a current brake mode; calculating a required current brake gear under the current brake mode according to the real-time casting data, and outputting corresponding real-time brake force. In the application, based on the collected real-time casting data, the current casting posture and the current bait type are identified first to confirm the current brake mode, and then the required current brake gear and the real-time brake force under the current brake mode are confirmed based on the real-time casting data; the user does not need to manually adjust the brake mode and the brake gear, the whole brake process is automatically completed, and the user experience is better.

Description

A smart braking method, system and fishing reel Technical Field

[0001] This invention relates to the field of fishing data processing technology, and in particular to an intelligent braking method, system and fishing reel. Background Technology

[0002] The existing braking system for fishing reels calculates braking force based on three factors: casting type, braking gear, and braking stage. Different casting types have different braking gears, and each gear has a preset braking force for matching according to the braking stage.

[0003] This braking system requires manual adjustment of the braking mode and gear, which is not intelligent enough and thus affects the user experience. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent braking method, system, and fishing reel, which aims to solve the problem of poor user experience caused by the need to manually adjust the braking mode and braking gear during the casting process of existing fishing reels.

[0005] In a first aspect, embodiments of the present invention provide an intelligent braking method applied to a fishing reel, comprising:

[0006] Collect real-time casting data from fishing vessels during casting;

[0007] Identify the current casting posture and / or the current lure type based on real-time casting data, and confirm the current braking mode;

[0008] Calculate the required braking gear under the current braking mode based on real-time throwing data, and output the corresponding real-time braking force.

[0009] Secondly, embodiments of the present invention provide an intelligent braking system applied to a fishing reel, comprising:

[0010] The data acquisition unit is used to collect real-time casting data from the fishing vessel during casting.

[0011] Braking mode confirmation unit is used to identify the current casting posture and / or the current lure type based on real-time casting data, and to confirm the current braking mode;

[0012] The braking force calculation unit is used to calculate the current braking gear required under the current braking mode based on real-time throwing data, and output the corresponding real-time braking force.

[0013] Thirdly, embodiments of the present invention provide a fishing reel, including the intelligent braking system described above.

[0014] The beneficial effects of this invention are as follows: when casting, based on the collected real-time casting data, the current casting posture and the current bait type are first identified to confirm the current braking mode. Then, based on the real-time casting data, the required current braking gear and real-time braking force under the current braking mode are confirmed. Users do not need to manually adjust the braking mode and braking gear. The entire braking process is completed automatically, resulting in a better user experience.

[0015] Based on the function of automatically adjusting the braking mode and braking gear, fishing reels can be designed in different styles with or without knobs, adding more diverse options to the product. The knobless style can make the fishing reel look simpler, while the style with knobs retains the traditional knob adjustment operation habit of fishing reels, meeting the needs of different users. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 is a flowchart illustrating the intelligent braking method provided in an embodiment of the present invention.

[0018] Figure 2 is a schematic diagram of the sub-process of step S101 provided in an embodiment of the present invention.

[0019] Figure 3 is a schematic diagram of the sub-process of step S102 provided in an embodiment of the present invention.

[0020] Figure 4 is a schematic diagram of the sub-process of step S103 provided in an embodiment of the present invention.

[0021] Figure 5 is a schematic diagram of the sub-process of step S403 provided in an embodiment of the present invention.

[0022] Figure 6 is a schematic flowchart of the flight phase division method provided in an embodiment of the present invention.

[0023] Figure 7 is a schematic block diagram of the intelligent braking system provided in an embodiment of the present invention.

[0024] Figure 8 is an example diagram of the real-time rotational speed and the corresponding real-time rotational speed change rate during a single throwing process provided by an embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0027] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0028] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0029] Please refer to Figure 1, which is a flowchart illustrating the intelligent braking method provided in an embodiment of the present invention;

[0030] As shown in Figure 1, the method includes steps S101 to S103.

[0031] S101. Collect real-time casting data of fishing vessels during casting;

[0032] In this step, various sensors built into the fishing reel can collect real-time casting data during casting.

[0033] S102. Identify the current casting posture and / or the current bait type based on real-time casting data, and confirm the current braking mode;

[0034] In this step, different casting postures and bait types correspond to different braking force modes, thereby achieving intelligent control of the fishing reel's braking force.

[0035] S103. Calculate the required braking gear under the current braking mode based on the real-time throwing data, and output the corresponding real-time braking force;

[0036] In this step, after confirming the current braking mode, the required current braking gear is further confirmed by real-time throwing data. Then, under the current braking gear, the corresponding real-time braking force is automatically calculated using real-time throwing data to perform real-time braking control.

[0037] Based on steps S101 to S103, when the fishing reel is casting, the current casting posture and the current bait type are first identified based on the collected real-time casting data to confirm the current braking mode. Then, based on the real-time casting data, the required current braking gear and real-time braking force under the current braking mode are confirmed. Users do not need to manually adjust the braking mode and braking gear; the entire braking process is completed automatically, resulting in a better user experience.

[0038] Based on the function of automatically adjusting the braking mode and braking gear, fishing reels can be designed in different styles with or without knobs, adding more diverse options to the product. The knobless style can make the fishing reel look simpler, while the style with knobs retains the traditional knob adjustment operation habit of fishing reels, meeting the needs of different users.

[0039] In this embodiment, the real-time braking force during throwing can be characterized in different ways, such as by the duty cycle. The larger the duty cycle, the greater the real-time braking force. The real-time braking force mentioned later refers to the duty cycle. However, it is obvious that other data indicators can be used to characterize the braking force in other embodiments, and such substitutions or modifications fall within the scope of protection of this application.

[0040] In one embodiment, as shown in FIG2, step S101 includes:

[0041] S201. The three-axis angular acceleration data of the fishing reel during the casting process are collected by the motion sensor installed on the fishing reel to obtain real-time motion data;

[0042] S202. The speed detection module installed on the fishing reel collects the spool rotation speed during the casting process to obtain real-time rotation data.

[0043] In this embodiment, step S201 can collect three-axis angular acceleration data during the casting process of the fishing reel using a motion sensor; and extract real-time motion data from the three-axis angular acceleration data; wherein, the motion data includes: positive angle change, negative angle change, maximum angular acceleration and minimum angular acceleration of the y-axis, and positive angle change, negative angle change, maximum angular acceleration and minimum angular acceleration of the z-axis.

[0044] In this embodiment, step S202 can detect the rotation speed of the spool using a speed detection module installed on the fishing reel, thereby obtaining real-time rotation data. Specifically, during casting, the magnet on the spool rotates with the spool. The rotation data of the magnet is detected by the speed detection module. Each rotation generates a square wave periodic pulse signal. The square wave periodic pulse signal changes from high to low and then back to high. When the signal goes low, interrupt 1 is triggered and a timer starts counting. When the signal goes from low to high, interrupt 2 is triggered and a count is completed. In this way, real-time rotation data can be obtained.

[0045] The following describes three implementation methods for confirming the current braking mode in step S102:

[0046] Example 1:

[0047] The braking mode matching based on throwing posture specifically includes: inputting real-time motion data into a posture classification model to predict the throwing posture and outputting the current throwing posture; matching the braking mode corresponding to the current throwing posture in a preset first braking mode table and using it as the current braking mode.

[0048] In this first embodiment, the posture classification model can be the XGBoost model. The XGBoost model is trained using the historical motion dataset of historical casting. The real-time motion data of the fishing reel at the time of the current casting is input into the trained XGBoost model to output the current casting posture. The casting posture can include six postures: over-the-shoulder casting, side casting, swing casting, long casting, skipping, and catapult casting.

[0049] In this first embodiment, the first braking mode table is shown in Table 1 below.

[0050] Table 1

[0051] Throwing posture, braking mode, over-the-shoulder throw, general-purpose side throw, general-purpose long throw, long throw, swing throw, swing throw, skipping, skipping, catapult, catapult. surface

[0052] Based on this, after the current throwing posture is output by the posture classification model, the corresponding current braking mode can be determined from Table 1.

[0053] Example 2:

[0054] The braking mode matching based on bait type specifically includes: inputting real-time rotation data into the bait classification model to predict the bait type and outputting the current bait type; matching the braking mode corresponding to the current bait type in the preset second braking mode table and using it as the current braking mode.

[0055] In this second embodiment, the input to the bait classification model is the rotation data in the rising phase of the real-time rotation data, which mainly includes 11 features as shown in Table 2 below:

[0056] Table 2

[0057]

[0058] Input the features in Table 2 into the bait classification model to predict the bait type, and the current bait type will be output. Then, based on the second braking mode table (Table 3) below, the corresponding current braking mode can be determined.

[0059] Table 3

[0060] Lure type, braking mode, general-purpose lure, general-purpose light lure, light lure, wind resistance lure. surface

[0061] Example 3:

[0062] Please refer to Figure 3. The braking mode is matched based on the casting posture and bait type, specifically including:

[0063] S301. Input real-time motion data into the posture classification model to predict the throwing posture and output the current throwing posture.

[0064] S302. Input the real-time rotation data into the bait classification model to predict the bait type and output the current bait type.

[0065] S303. Obtain the current braking mode based on the current casting posture and the current bait type.

[0066] In this embodiment, the posture classification model in step S301 is the same as in embodiment one, and the xgboost model can be used. It can also output the six postures of over-the-shoulder throw, side throw, swing throw, long throw, skipping, and catapult.

[0067] In this embodiment, the bait classification model in step S302 is mainly used to predict the bait type under the two casting postures of over-the-shoulder casting and side casting. Specifically, when the casting posture is over-the-shoulder casting or side casting, the rotation data in the rising phase of the real-time rotation data (i.e., the 11 features in Table 2 above) is input into the bait classification model to predict the bait type, and the current bait type can be output. Among them, the bait types corresponding to over-the-shoulder casting and side casting include general bait, wind resistance bait, and light bait. As for the four casting postures of swaying casting, long casting, skipping, and catapult casting, there is no need to identify the bait type, and the corresponding braking mode can be directly matched. For details, please refer to the third braking mode table shown in Table 4 below.

[0068] Table 4

[0069]

[0070]

[0071] Based on this, after identifying the corresponding current casting posture and bait type through the posture classification model and bait type classification model, the corresponding current braking mode can be identified from Table 4.

[0072] In one embodiment, as shown in FIG4, step S103 includes:

[0073] S401. Input the speed data in the rising phase of the real-time rotation data into the linear model of the gear corresponding to the current braking mode for fitting processing, and output the current braking gear required in the current braking mode.

[0074] S402. Obtain the current preset braking force coefficient corresponding to the current braking gear in the current braking mode;

[0075] S403. Calculate the braking force based on the current preset braking force coefficient and real-time rotation data, and output the corresponding real-time braking force.

[0076] In step S401 of this embodiment, each braking mode corresponds to a gear linear model. Taking the above-mentioned embodiment three for confirming the current braking mode as an example, the seven braking modes correspond to seven gear linear models. By inputting the features in the current real-time rotation data corresponding to the above-mentioned Table 1 into the corresponding gear linear model for fitting processing, the current braking gear required under the current braking mode can be output.

[0077] In step S402 of this embodiment, preset braking force coefficient data corresponding to each braking gear in each braking mode is pre-built. Once the current braking mode and the current braking gear are confirmed, the corresponding preset braking force coefficient can be called.

[0078] In step S403 of this embodiment, based on the preset braking force coefficient confirmed in step S402, the preset braking force coefficient and real-time rotation data are processed by a software algorithm to automatically calculate a suitable real-time braking force, thereby controlling the braking process of the fishing reel casting.

[0079] In one embodiment, as shown in FIG5, step S403 includes:

[0080] S501. During the upward phase of the casting, the real-time braking force output is converted into a fixed braking force, wherein the braking duty cycle of the fixed braking force is selected within the range of [0%, 10%].

[0081] S502. During the descent phase of the throw, the current preset braking force coefficient and real-time rotation data are input into the braking force algorithm to calculate the real-time braking force and output the real-time braking force corresponding to the descent phase.

[0082] In this embodiment, the casting process of the fishing reel has different flight stages (i.e., the ascent stage and the descent stage). Different flight stages require corresponding braking forces. By outputting different braking forces in different flight stages, the rotation speed of the fishing reel's spool is controlled, thereby braking control of the casting process of the fishing reel.

[0083] Specifically, as shown in Figure 6, the flight phase of the fishing boat casting can be divided into steps S601 to S605.

[0084] S601. Obtain the real-time rotation speed and real-time rotation speed change rate from the real-time rotation data;

[0085] S602, Set the casting phase from the start of casting to the maximum rate of change of rotation speed as the accelerated upward phase in the upward phase;

[0086] S603, Set the throwing stage from the maximum speed change rate to the maximum speed as the deceleration rising stage in the rising stage;

[0087] S604. Set the throwing phase from the maximum speed to the predicted throwing end speed as the continuous descent phase in the descent phase.

[0088] S605, The predicted drop end speed to the actual drop end time is set as the tail flight phase in the descent phase.

[0089] Based on steps S601 to S605, to facilitate understanding of the different flight stages of this embodiment, the casting data illustrated in Figure 8 can be used as a reference. The ascent stage can include an accelerated ascent stage T1 and a decelerated ascent stage T2, while the descent stage can include a continuous descent stage T3 and a tail-end flight stage T4. In the ascent stage of casting, the inertial force of the bait being thrown drives the spool of the fishing reel to rotate and release line. The spool speed in this stage follows the bait's casting speed. Therefore, the real-time rotation data (mainly referring to the real-time speed of the fishing reel) from stage T1 to T2 changes from an accelerated ascent followed by a decelerated ascent until the maximum speed of this casting is reached (i.e., the speed change rate is zero). Then, the continuous descent stage T3 begins. At this time, the inertial force of the bait being thrown continuously decreases, requiring a certain braking force to be applied to the spool of the fishing reel to prevent the reel speed from exceeding the line release speed and causing line breakage. By applying braking force, the reel continuously decreases from its maximum speed to the predicted casting end speed, then enters the tail-end flight stage T4 until the actual casting ends, completing the identification and division of the casting stages.

[0090] Based on the four phases, the acceleration and ascent phase T1 and the deceleration and ascent phase T2 do not require excessive braking force on the fishing reel spool. Therefore, the braking force corresponding to the ascent phase can be set to a fixed braking force, for example, a fixed braking force selected from the range of braking force duty cycles of [0%, 10%]. Preferably, to avoid interfering with the calculation of subsequent braking gears, the fixed braking force corresponding to the ascent phase can be set to 0%. However, the descent phase T3 and the tail flight phase T4 require real-time braking force on the fishing reel spool to achieve intelligent braking control, as detailed in the two embodiments below for calculating the real-time braking force.

[0091] Furthermore, the predicted throw end speed in step S604 can be obtained through a pre-trained throwing model. Each throwing posture corresponds to one throwing model. The specific method for calculating the predicted throw end speed is as follows:

[0092] The linear model is pre-trained based on the casting force, casting angle, and maximum speed of the fishing reel. The formula for the linear model is: throw_end_speed = throw_force*a + throw_angle*b + max_speed*c + b.

[0093] Here, throw_end_speed represents the predicted end speed of this throw.

[0094] Throw_force represents the maximum value of the triaxial resultant acceleration calculated by the motion sensor during the actual throw, which represents the throwing force.

[0095] Throw_angle represents the angle between the fishing rod and the ground when the line is first released during casting, which can be calculated from the data of the motion sensor;

[0096] Max_speed represents the maximum rotational speed generated during actual throwing.

[0097] Based on the casting model obtained after training, taking Figure 8 as an example, the predicted casting speed at the end of the casting can be obtained by the above formula as 150. However, due to various factors, the fishing reel is still out of the line during the actual casting. The subsequent stage is the T4 stage, also known as the tail flight stage.

[0098] The following describes two implementation methods for calculating the real-time braking force during the descent phase in calculation step S502.

[0099] Example 1:

[0100] In one embodiment, step S502 includes:

[0101] The real-time braking force G_descent of the fishing vessel during the descent phase is calculated using the following formula:

[0102] G 下降 =v / max(v)*Fi+K,G 下降 ∈(H i H j );

[0103] Where v represents the real-time rotational speed of the fishing reel during the descent phase, max(v) represents the maximum rotational speed for this casting, and F i This indicates the descent coefficient corresponding to the current braking mode and current braking gear; K represents the anti-burst cable protection value; H represents... i and H j This indicates the lower and upper limits of braking force corresponding to the current braking gear in the current braking mode.

[0104] In this embodiment, during the descent phase of the throw, a preset braking force coefficient (F) is determined based on the current braking mode and the current braking gear. i K, H i and H j Substituting the real-time rotation data (i.e., v and max(v)) into the above formula to calculate the braking force, the real-time braking force G corresponding to the descent phase during the throw can be output. 下降 .

[0105] Example 2:

[0106] In one embodiment, step S502 includes:

[0107] The real-time braking force G_descent of the fishing vessel during the descent phase is calculated using the following formula:

[0108] G 下降 =v*v i +a*a i +v / max(v)*F i +K, G 下降 ∈(H i H j );

[0109] Where v represents the real-time rotational speed of the fishing reel during the descent phase. i This represents the frequency coefficient corresponding to the current braking gear in the current braking mode, and 'a' represents the real-time rate of change of the fishing reel's rotational speed during the descent phase. i The frequency change coefficient corresponding to the current braking gear in the current braking mode is represented by max(v), which represents the maximum rotational speed of this throw. i This indicates the descent coefficient corresponding to the current braking mode and current braking gear; K represents the anti-burst cable protection value; H represents... i and H j These represent the lower limit and upper limit of braking force corresponding to the current braking gear in the current braking mode, respectively.

[0110] In this embodiment, during the descent phase of the throw, a preset braking force coefficient determined based on the current braking mode and current braking gear is applied to the preset braking force coefficient (i.e., v). i a i F i K, H i and H j Substituting the real-time rotation data (i.e., v, a, and max(v)) into the above formula to calculate the braking force, the real-time braking force G corresponding to the descent phase during the throw can be output. 下降 .

[0111] The real-time braking force algorithms in Embodiments 1 and 2 described above have different applications in different scenarios. For example, in the wind resistance braking mode corresponding to wind resistance bait, the change in fishing reel speed is more obvious, and the algorithm of Embodiment 2 can be used to calculate the braking effect, resulting in a better braking effect. Conversely, in the braking mode where the fishing reel speed is relatively stable, the algorithm of Embodiment 1 can be applied to calculate the real-time braking force, resulting in a better braking effect.

[0112] Based on the algorithms of Embodiment 1 and Embodiment 2 above, the real-time braking force obtained during the casting and descent phase of the fishing reel changes linearly, which solves the problem of sudden changes in braking force during casting and makes casting smoother.

[0113] This invention also provides an intelligent braking system for performing any of the aforementioned intelligent braking methods. Specifically, please refer to FIG7, which is a schematic block diagram of the intelligent braking system provided in this invention.

[0114] As shown in Figure 7, the intelligent braking system 700 includes: a data acquisition unit 701, a braking mode confirmation unit 702, and a braking force calculation unit 703.

[0115] The data acquisition unit 701 is used to collect real-time casting data of the fishing vessel during casting.

[0116] Braking mode confirmation unit 702 is used to identify the current casting posture and / or the current bait type based on real-time casting data, and to confirm the current braking mode;

[0117] The braking force calculation unit 703 is used to calculate the current braking gear required under the current braking mode based on real-time throwing data, and output the corresponding real-time braking force.

[0118] In this system, when the fishing reel is casting, based on the collected real-time casting data, the current casting posture and the current bait type are first identified to determine the current braking mode. Then, based on the real-time casting data, the required current braking gear and real-time braking force under the current braking mode are determined. The magnitude of the real-time braking force changes linearly during the casting process, solving the problem of sudden changes in braking force and making casting smoother. Users do not need to manually adjust the braking mode and braking gear; the entire braking process is completed automatically, resulting in a better user experience.

[0119] Based on the function of automatically adjusting the braking mode and braking gear, fishing reels can be designed in different styles with or without knobs, adding more diverse options to the product. The knobless style can make the fishing reel look simpler, while the style with knobs retains the traditional knob adjustment operation habit of fishing reels, meeting the needs of different users.

[0120] This invention also provides a fishing reel, including the intelligent braking system described above.

[0121] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0122] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A smart braking method applied to a fishing reel, characterized in that, include: Collect real-time casting data of the fishing reel during casting, including real-time motion data and real-time rotation data; Identify the current casting posture and / or the current bait type based on real-time casting data, and confirm the current braking mode; input the rotation speed data during the upward phase from the real-time rotation data into the linear model corresponding to the current braking mode for fitting processing, and output the current braking gear required under the current braking mode; obtain the current preset braking force coefficient corresponding to the current braking gear under the current braking mode; calculate the braking force based on the current preset braking force coefficient and real-time rotation data, and output the corresponding real-time braking force; wherein, the step of calculating the braking force based on the current preset braking force coefficient and real-time rotation data and outputting the corresponding real-time braking force includes: during the descent phase of casting, inputting the current preset braking force coefficient and real-time rotation data into the braking force algorithm for real-time braking force calculation, and outputting the real-time braking force corresponding to the descent phase; calculate the real-time braking force G of the fishing reel during the descent phase according to the following formula. 下降 :G 下降 =v*v i +a*a i +v / max(v)*F i +K, G 下降 ∈ (H i H j ); where v represents the real-time rotational speed of the fishing reel during the descent phase, v i This represents the frequency coefficient corresponding to the current braking gear in the current braking mode, and 'a' represents the real-time rate of change of the fishing reel's rotational speed during the descent phase. i The frequency change coefficient corresponding to the current braking gear in the current braking mode is represented by max(v), which represents the maximum rotational speed of this throw. i This indicates the descent coefficient corresponding to the current braking mode and current braking gear; K represents the anti-burst cable protection value; H represents... i and H j These represent the lower limit and upper limit of braking force corresponding to the current braking gear in the current braking mode, respectively.

2. The intelligent braking method according to claim 1, characterized in that, The real-time casting data of the fishing reel during casting includes: collecting the three-axis angular acceleration data of the fishing reel during casting through a motion sensor installed on the fishing reel to obtain real-time motion data; and collecting the spool rotation speed of the fishing reel during casting through a speed detection module installed on the fishing reel to obtain real-time rotation data.

3. The intelligent braking method according to claim 2, characterized in that, The step of identifying the current casting posture and / or the current bait type based on real-time casting data and confirming the current braking mode includes: inputting real-time motion data into a posture classification model to predict the casting posture and outputting the current casting posture; matching the braking mode corresponding to the current casting posture in a preset first braking mode table and using it as the current braking mode.

4. The intelligent braking method according to claim 2, characterized in that, The step of identifying the current casting posture and / or the current bait type based on real-time casting data and confirming the current braking mode includes: inputting real-time rotation data into a bait classification model to predict the bait type and outputting the current bait type; matching the braking mode corresponding to the current bait type in a preset second braking mode table and using it as the current braking mode.

5. The intelligent braking method according to claim 2, characterized in that, The step of identifying the current casting posture and / or the current bait type based on real-time casting data and confirming the current braking mode includes: inputting real-time motion data into a posture classification model to predict the casting posture and outputting the current casting posture; inputting real-time rotation data into a bait classification model to predict the bait type and outputting the current bait type; and matching the corresponding braking mode in a preset third braking mode table based on the current casting posture and the current bait type and using it as the current braking mode.

6. The intelligent braking method according to claim 1, characterized in that, The step of calculating the braking force based on the current preset braking force coefficient and real-time rotation data and outputting the corresponding real-time braking force further includes: during the upward phase of the throwing process, outputting the real-time braking force as a fixed braking force, wherein the braking duty cycle of the fixed braking force is selected within the range of [0%, 10%].

7. The intelligent braking method according to claim 2, characterized in that, Also includes: Acquire real-time rotational speed and real-time rotational speed change rate from real-time rotational data; set the throwing phase from the start of the throw to the maximum rotational speed change rate as the acceleration ascent phase in the ascent phase; set the throwing phase from the maximum rotational speed change rate to the maximum rotational speed as the deceleration ascent phase in the ascent phase; set the throwing phase from the maximum rotational speed to the predicted throwing end speed as the continuous descent phase in the descent phase; set the throwing phase from the predicted throwing end speed to the actual throwing end time as the tail flight phase in the descent phase.

8. A smart braking method applied to a fishing reel, characterized in that, include: Collect real-time casting data of the fishing reel during casting, including real-time motion data and real-time rotation data; Identify the current casting posture and / or the current bait type based on real-time casting data, and confirm the current braking mode; input the rotation speed data during the upward phase from the real-time rotation data into the linear model corresponding to the current braking mode for fitting processing, and output the current braking gear required under the current braking mode; obtain the current preset braking force coefficient corresponding to the current braking gear under the current braking mode; calculate the braking force based on the current preset braking force coefficient and real-time rotation data, and output the corresponding real-time braking force; wherein, the step of calculating the braking force based on the current preset braking force coefficient and real-time rotation data and outputting the corresponding real-time braking force includes: during the descent phase of casting, inputting the current preset braking force coefficient and real-time rotation data into the braking force algorithm for real-time braking force calculation, and outputting the real-time braking force corresponding to the descent phase; calculate the real-time braking force G of the fishing reel during the descent phase according to the following formula. 下降 :G 下降 =v / max(v)*F i +K, G 下降 ∈ (H i H j ); where v represents the real-time rotational speed of the fishing reel during the descent phase, max(v) represents the maximum rotational speed for this casting, and F i This indicates the descent coefficient corresponding to the current braking mode and current braking gear; K represents the anti-burst cable protection value; H represents... i and H j These represent the lower limit and upper limit of braking force corresponding to the current braking gear in the current braking mode, respectively.

9. An intelligent braking system applied to a fishing reel, characterized in that, include: The data acquisition unit is used to collect real-time casting data of the fishing reel during casting, including real-time motion data and real-time rotation data. A braking mode confirmation unit is used to identify the current casting posture and / or the current bait type based on real-time casting data, and confirm the current braking mode. A braking force calculation unit is used to input the rotation speed data during the upward phase of the real-time rotation data into the linear model corresponding to the current braking mode for fitting processing, and output the current braking gear required under the current braking mode; obtain the current preset braking force coefficient corresponding to the current braking gear under the current braking mode; calculate the braking force based on the current preset braking force coefficient and real-time rotation data, and output the corresponding real-time braking force; wherein, the calculation of the braking force based on the current preset braking force coefficient and real-time rotation data, and outputting the corresponding real-time braking force, includes: during the descent phase of casting, inputting the current preset braking force coefficient and real-time rotation data into a braking force algorithm for real-time braking force calculation, and outputting the real-time braking force corresponding to the descent phase; calculating the real-time braking force G of the fishing reel during the descent phase according to the following formula. 下降 :G 下降 =v*v i +a*a i +v / max(v)*F i +K, G 下降 ∈ (H i H j ); where v represents the real-time rotational speed of the fishing reel during the descent phase, v i This represents the frequency coefficient corresponding to the current braking gear in the current braking mode, and 'a' represents the real-time rate of change of the fishing reel's rotational speed during the descent phase. i The frequency change coefficient corresponding to the current braking gear in the current braking mode is represented by max(v), which represents the maximum rotational speed of this throw. i This indicates the descent coefficient corresponding to the current braking mode and current braking gear; K represents the anti-burst cable protection value; H represents... i and H j These represent the lower limit and upper limit of braking force corresponding to the current braking gear in the current braking mode, respectively.

10. A fishing reel, characterized in that, Including the intelligent braking system as described in claim 9 above.

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