Photoelectric adaptive detection system, modeling and control method of yarn information

Abstract

The application discloses a yarn information photoelectric adaptive detection system, modeling and control method, and belongs to the technical field of textile machinery. The yarn information photoelectric adaptive detection system and the modeling method of the application realize integrated modeling of the yarn information photoelectric adaptive detection system by constructing an exponential diode model, an infrared light-emitting tube characteristic model, a light intensity transmission model, a linear fitting model and a signal conversion model, and further provide a basis for parameter setting of actual photoelectric adaptive detection system design by combining with a simulation method to analyze rules and performance. Meanwhile, the adaptive control method of the application can realize real-time adjustment of the reference voltage deviation caused by the reduction of the reflector efficiency and the signal amplitude change caused by the yarn specification change, so that the yarn detection has higher anti-interference and adaptability, and is more suitable for high-speed and harsh environment loom application.

Description

Technical Field

[0001] This invention relates to a photoelectric adaptive detection system, modeling and control method for yarn information, belonging to the field of textile machinery technology. Background Technology

[0002] The weft feeder is an indispensable key component of knitting machines such as sock knitting machines. Traditional weft feeders generally use asynchronous motors as drive elements. For example, Chinese patent CN211698662U discloses a simplified air-jet knitting machine electrical control system, which uses an asynchronous motor as its drive motor. It has advantages such as simple structure and low cost, but its drive system has low efficiency and slow response. Existing weft feeder systems are more suitable for applications with slow yarn feeding. With the continuous improvement of digital technology and industrial automation, textile machinery has put forward higher requirements for the feeding performance and efficiency of weft feeders. Weft feeder drive motors are developing towards permanent magnet synchronous motors. For example, Chinese patent CN218812416U discloses an ESDP electronic weft feeder with restraint function, which uses a permanent magnet synchronous motor as its drive element. The motor speed during operation of the weft feeder is usually as high as 6000-8000 rpm, and the operating efficiency and reliability are significantly improved. At this point, high-precision and high-response detection of yarn information is closely related to the operating efficiency and reliability of the weft feeder, and is a crucial technology essential for the development of this type of weft feeder. One effective solution is to use photoelectric sensors. For example, patent CN107083607A discloses a photoelectric technology-based weft feeder that uses an infrared transmitter and receiver to detect yarn information. This method monitors the movement state of the weft yarn on the weft feeder and the number of weft unwinding turns. Simultaneously, the infrared transmitter and receiver solves the problems of uneven tension and easy weft breakage caused by contact with the weft yarn in traditional contact detection devices.

[0003] However, current yarn information detection systems require setting multiple control parameters in the early design stage, often requiring repeated debugging, which takes a long time. Furthermore, the detection accuracy of yarn will decrease when the environment or yarn specifications change, which in turn affects the working efficiency of the weft feeder and the processing quality of the loom.

[0004] The information disclosed in this background section is only for understanding the background of the inventive concept, and therefore may include information that does not constitute prior art. Summary of the Invention

[0005] To address the aforementioned problems or one of the aforementioned problems, the present invention aims to provide a photoelectric adaptive detection system for yarn information. This system comprises a controllable power supply module, a photoelectric sensor mathematical modeling module, an amplifier circuit module, a conditioning circuit module, a comparison circuit module, an ARM controller, and a photoelectric sensor module. This solves the problems of low environmental interference resistance and weak adaptability to changes in yarn specifications found in existing weft feeder yarn information detection systems.

[0006] To address the aforementioned problems or one of the aforementioned problems, the second objective of this invention is to provide a modeling method for a photoelectric adaptive detection system for yarn information. This method constructs an exponential diode model, an infrared light-emitting diode characteristic model, a light intensity transmission model, a linear fitting model, and a signal conversion model, thereby solving the problems of time-consuming and labor-intensive processes caused by the need for repeated on-site debugging of photoelectric sensor parameters in traditional methods.

[0007] To address the aforementioned problems or one of them, the third objective of this invention is to provide a control method for a photoelectric adaptive detection system for yarn information. By analyzing key factors affecting the yarn signal through mathematical models, a reference voltage control method based on fuzzy PI is constructed, solving the reference voltage offset problem caused by reduced mirror efficiency. Simultaneously, by analyzing the influence of yarn thickness and color on the yarn signal, a comparator voltage control method for adaptive yarn specification adjustment is constructed, solving the problem of detection signal amplitude changes caused by variations in yarn specifications.

[0008] To achieve one of the above objectives, the first technical solution of the present invention is as follows:

[0009] A photoelectric adaptive detection system for yarn information includes: a controllable power supply module, a photoelectric sensor mathematical modeling module, an amplifier circuit module, a conditioning circuit module, a comparator circuit module, an ARM controller, and a photoelectric sensor module;

[0010] The input to the controllable power supply module is the analog voltage U output by the ARM controller. DA ,

[0011] The input to the mathematical modeling module for the photoelectric sensor is the voltage U output from the controllable power supply module. The photoelectric sensor module converts the collected yarn information into a photocurrent signal I0.

[0012] The input signal to the amplifier circuit module is the photocurrent signal I0 from the photoelectric sensor module.

[0013] The input to the conditioning circuit module is the yarn amplified signal voltage U output from the amplifier circuit module. S ,

[0014] The comparator circuit module has two inputs: the yarn detection signal voltage U1 output from the conditioning circuit module, and the calculated comparison voltage U1 output from the ARM controller. C ,

[0015] The ARM controller has two inputs, which are acquired by sampling the amplified signal U output from the amplifier circuit module using an analog-to-digital converter (AD) method. S , and the pulse signal U2 output by the comparison circuit module through IO detection;

[0016] The photoelectric sensor module includes an infrared LED, a photoelectric receiver, a reflector, and a light-blocking body. Its parameters include the reflector's reflectivity η. m Installation height h and installation angles θ1 and θ2.

[0017] This invention constructs a photoelectric adaptive detection system for yarn information by setting up a controllable power supply module, a photoelectric sensor mathematical modeling module, an amplifier circuit module, a conditioning circuit module, a comparator circuit module, an ARM controller, and a photoelectric sensor module. This system uses a mathematical model to study the influence of key factors such as the reflectivity of the reflector and the yarn specification on the yarn signal in the photoelectric adaptive detection device. It can effectively improve the detection accuracy of yarn, thereby improving the working efficiency of the weft feeder and the processing quality of the loom. Therefore, it can solve the problems of low environmental anti-interference performance and weak adaptability to changes in yarn specification in existing weft feeder yarn information detection systems.

[0018] To achieve one of the above objectives, the second technical solution of the present invention is as follows:

[0019] A modeling method for a photoelectric adaptive detection system for yarn information, applied to the aforementioned photoelectric adaptive detection system for yarn information, includes the following steps:

[0020] Step 1: Using a pre-built exponential diode model, based on the output voltage U of the ARM controller... DA Calculate the infrared LED current I;

[0021] Step two: Using a pre-built characteristic model of the infrared LED, the radiation intensity I of the infrared LED is calculated based on the current I of the infrared LED. e :

[0022] Step 3: Using a pre-constructed light intensity transmission model, based on the infrared LED radiation intensity I... e The irradiance E of the photodetector tube was calculated. e ;

[0023] Step four: Using a pre-built linear fitting model, the irradiance E of the photodetector tube is calculated. e The photocurrent I0 of the photodetector is obtained through processing.

[0024] Step 5: Based on the pre-built signal conversion model, determine the relationship between the photocurrent I0 of the photodetector tube and the reference voltage, obtain the reference voltage U0 for the yarn signal, and realize the modeling of the photoelectric adaptive detection system for yarn information.

[0025] Through continuous exploration and experimentation, this invention constructs an exponential diode model, an infrared LED characteristic model, a light intensity transmission model, a linear fitting model, and a signal conversion model to obtain a reference voltage U0 for yarn signals. This enables the modeling of a photoelectric adaptive detection system for yarn information, solving the problems of time-consuming and labor-intensive processes caused by repeated on-site debugging of photoelectric sensor parameters in traditional methods. It also reduces the workload of initial design for weft feeder yarn detection. By optimizing the design through pre-modeling and simulation, and then conducting physical verification, it effectively reduces trial-and-error costs, saving time and effort.

[0026] Furthermore, the modeling method for the photoelectric adaptive detection system of yarn information in this invention uses a mathematical model to model the sensing system and studies the variable factors in the photoelectric detection device: the reflectivity of the reflector and the influence of different yarn specifications on the yarn signal. At the same time, it also provides an optimal reference voltage range for detecting the yarn signal, and then combines simulation methods to analyze the laws and performance, thereby providing a basis for parameter setting for the design of actual photoelectric adaptive detection systems, saving research time and effort. The solution is scientific, reasonable, and feasible.

[0027] As a preferred technical measure:

[0028] Step 1: Using a pre-built exponential diode model, based on the output voltage U of the ARM controller... DA The method for calculating the infrared LED current I is as follows:

[0029] Since the light-emitting diode is an exponential diode connected in series with a current sensor, based on the characteristics of an exponential diode, the diode current I and diode voltage U are constructed as part of the exponential diode model. DA The calculation formula is as follows:

[0030]

[0031] Where q is the elementary charge of the electron, with a value of 1.602176 × 10⁻⁶. -19 Coulomb, k is the Boltzmann constant, with a value of 1.3806503 × 10⁻⁶. -23 J / K; IS is the saturation current, N is the emission coefficient, T m1 These are the temperature parameters of the diode;

[0032] The formula for calculating the saturation current IS is as follows:

[0033]

[0034] Where [V1, I1] and [V2, I2] are two parameter points;

[0035] The formula for calculating the emission coefficient N is as follows:

[0036]

[0037] Where V t =kT m1 / q,

[0038] By calculating the relationship and based on the output voltage U of the ARM controller DA Calculate the current I of the infrared LED.

[0039] As a preferred technical measure:

[0040] Step two: Using a pre-built characteristic model of the infrared LED, the radiation intensity I of the infrared LED is calculated based on the current I of the infrared LED. e The method is as follows:

[0041] Based on the characteristics of infrared LEDs, the radiation intensity I of the infrared LED is created. e The proportional relationship between the current I and the given current is calculated using the following formula:

[0042] I e =K1×I

[0043] Where K1 is the proportionality coefficient, which is obtained by linearly fitting the radiation intensity I. e The relationship with current I is obtained, and the fitting process is as follows:

[0044] Take I e - The n coordinate points in the I relationship diagram: A1(I e1 ,I1),A2(I e2 ,I2),……A n (I en I n );

[0045] A linear fit was performed on the coordinate points at the origin;

[0046] The distance L from the fitted line to each point is calculated using the following formula:

[0047]

[0048] Among them, I ei Let I be the radiation intensity at the i-th coordinate point. i Let be the current at the i-th coordinate point;

[0049] After substituting the data for each coordinate point, the proportionality coefficient K1 is solved by minimizing L.

[0050] Substituting the solved proportionality coefficient K1 and the current I of the infrared LED into the formula for calculating the proportional relationship, the radiation intensity I is calculated. e .

[0051] As a preferred technical measure:

[0052] Step 3: Using a pre-constructed light intensity transmission model, based on the infrared LED radiation intensity I... e The irradiance E of the photodetector tube was calculated. e The method is as follows:

[0053] Based on the light transmission path emitted by the infrared LED, the factors affecting the irradiance E of the photodetector are screened. e The relevant variables include angle θ1, angle θ2, installation height h, and reflectivity η. m And the yarn diameter d and color detected by the sensor;

[0054] The infrared light emitted by the infrared LED travels a certain distance before reaching the photodetector, and the light intensity attenuates during transmission. This attenuation is related to the installation height h between the two components. Based on this, a formula for calculating the transmission distance L is constructed as follows:

[0055]

[0056] Since θ1 and θ2 are both very small, tanθ1 and tanθ2 are approximately equal to 1, and according to the formula for calculating transmission distance, the transmission distance is 2h.

[0057] Radiation intensity I e It refers to the radiative flux per unit solid angle Ω in a given direction. The calculation formula is as follows:

[0058]

[0059] Radiance E e It refers to the radiative flux per unit area S. The calculation formula is as follows:

[0060]

[0061] According to geometric relationships, the solid angle is the ratio of the projected area S to the square of the sphere's radius r, and its calculation formula is as follows:

[0062]

[0063] Based on the sphere radius r corresponding to a transmission distance of 2h, construct the irradiance E of the photoelectric receiver tube.e The formula for calculating the first illuminance is as follows:

[0064]

[0065] Based on the first calculation formula, the irradiance E of the photoelectric receiver tube is analyzed. e Influence characteristics;

[0066] The influencing characteristics include the following:

[0067] Photodetector irradiance E e The intensity of radiation is inversely proportional to twice the square of the installation height (2h). The higher the installation height, the farther the distance between the infrared emitter and the photoelectric receiver, and the lower the radiation intensity received by the photoelectric receiver. When installing the sensor, the installation height is already determined and is a fixed value.

[0068] Based on the influencing characteristics and the effects of emission angle and incident angle on optical transmission efficiency η θ Create the photoelectric receiver tube irradiance E with fixed parameters for angle and height during installation. e The effect expression, i.e., the formula for calculating the second illuminance, is as follows:

[0069]

[0070] The light emitted by the infrared emitter must pass through a reflector before being reflected to the photoelectric receiver. The reflectivity η of the reflector... m This also affects light intensity transmission efficiency. Therefore, the second illuminance calculation formula is optimized to obtain the third illuminance calculation formula, which is as follows:

[0071]

[0072] Since the shading of yarn also affects the change in light intensity, the third illuminance calculation formula is optimized to obtain the fourth illuminance calculation formula, which is as follows:

[0073]

[0074] S0=x×y

[0075] S1=y×d

[0076] Among them, E e0 The infrared emitting tube emits light that is not blocked or interfered with by any yarn, and the photoelectric receiving tube receives the irradiance, E. e1 S1 represents the irradiance of the photoelectric receiver tube after the yarn is blocked when it passes through, d is the diameter of the yarn, S0 is the area of ​​the light source being detected in the entire system, x is the length of the detected surface, y is the width of the detected surface, and S1 is the area blocked by the yarn to be tested.

[0077] As a preferred technical measure:

[0078] Step four: Using a pre-built linear fitting model, the irradiance E of the photodetector tube is calculated. e The method for processing and obtaining the photocurrent I0 of the photodetector is as follows:

[0079] Based on the characteristics of the photodetector, the relationship between the photocurrent I0 and the irradiance E of the photodetector is established. e The formula for calculating the proportional relationship is as follows:

[0080] I0 = K2 × E e

[0081] The K2 proportionality coefficient is obtained by fitting the photocurrent I0 and the irradiance E. e The relationship was established.

[0082] As a preferred technical measure:

[0083] Step 5: Based on the pre-built signal conversion model, determine the relationship between the photocurrent I0 of the photodetector and the reference voltage, and obtain the reference voltage U0 for the yarn signal as follows:

[0084] Based on the fact that the signal generated by the photodetector is a current signal and is very weak, a calculation formula for a transimpedance amplifier circuit is constructed to convert the current signal into a voltage signal and amplify the signal. The specific expression of the calculation formula for the transimpedance amplifier circuit is as follows:

[0085] U S =U ref -I0(R1+R2)

[0086] Among them, U S U is the voltage of the ARM controller's AD sampling and amplification signal. ref R1 is the reference voltage at the positive input terminal of the amplifier, R2 is the current-limiting resistor on the feedback network, and R2 is the variable resistor connected in series with R1.

[0087] Based on the calculation formula for the transimpedance amplifier circuit, construct the infrared LED voltage U. DA Adjustment and amplification of yarn sampling signal voltage U S The voltage transformation relationship between the actual voltage of the yarn signal is as follows:

[0088]

[0089] Based on the voltage transformation formula, by substituting the recommended photocurrent and typical irradiance value of a specific photodetector, a range of reference voltage U0 is calculated, so that the yarn signal can achieve the best detection effect when running under this reference voltage.

[0090] To achieve one of the above objectives, the third technical solution of the present invention is as follows:

[0091] A control method for a photoelectric adaptive detection system for yarn information is applied to the aforementioned photoelectric adaptive detection system for yarn information, which includes a reference voltage control method based on fuzzy PI and a comparator voltage control method based on adaptive adjustment of yarn specifications.

[0092] A reference voltage control method is used to adjust the reference voltage deviation caused by the reduction in mirror efficiency in real time;

[0093] A comparator voltage control method is used to adjust the signal amplitude in real time according to the changes in yarn specifications.

[0094] Compared to traditional yarn detection, the adaptive control method in this invention can adjust the reference voltage deviation caused by the reduction in the efficiency of the reflector in real time, and adjust the signal amplitude change caused by the change in yarn specifications in real time. This makes the yarn detection more resistant to interference, more flexible and more accurate, and is especially suitable for complex and ever-changing loom environments, meeting the increasingly diverse textile needs.

[0095] As a preferred technical measure:

[0096] The reference voltage control method based on fuzzy PI includes the following:

[0097] The calculated reference voltage value U0 is used as the target voltage value of the fuzzy PI controller, and the amplified yarn signal U is sampled by the AD converter of the ARM controller. S U obtained after filtering f The feedback voltage U of the fuzzy PI controller f Feedback voltage U f The voltage error value e is obtained by subtracting the voltage from the target reference voltage U0, and the error rate e is obtained by differentiating the error. c The data is input into the fuzzy controller, where it is fuzzified and closed-loop control is used to ensure that the photoelectric sensor and the detection circuit operate in the optimal state.

[0098] Or / and, the comparator voltage control method based on yarn specification adaptive adjustment includes the following:

[0099] The signal U is amplified by sampling the yarn using an ARM controller's AD converter. S This signal is used as the basis for calculating the comparison voltage in the subsequent comparison circuit module. Through circuit analysis, the transfer functions of the conditioning circuit input and output are established, and the relationship between the change in yarn specifications and the comparison voltage is found, which includes the yarn amplification signal U. S Comparison voltage U CThe relationship formula is used to achieve real-time adjustment of the comparison voltage to adapt to changes in signal amplitude caused by different yarn specifications.

[0100] As a preferred technical measure:

[0101] The following method employs a fuzzy PI controller for processing and closed-loop control:

[0102] Voltage U based on light-emitting diode DA With the actual voltage U of the yarn signal S The relationship is used to construct a discrete formula for the fuzzy PI algorithm, which is then used to adjust the output U of the ARM controller. DA To adjust the reference voltage U0 of the yarn signal in real time;

[0103] The expression for the discrete formula of the fuzzy PI algorithm is as follows:

[0104]

[0105] Among them, K p and K i Here are the algorithm parameters, U(k) is the output voltage after fuzzy PI calculation, and e(k) is the error between the actual and theoretical values ​​of the reference voltage.

[0106] Meanwhile, seven linguistic variables for the fuzzy subset values ​​are set, including positive large PB, positive medium PM, positive small PS, zero ZO, negative small NS, negative medium NM, and negative large NB. The universe of discourse range (-6, 6) is set to correspond to the endpoints of the seven linguistic variables respectively. The range of the voltage error value e is set to (-1, 1), and it is mapped to the universe of discourse.

[0107] Then, its membership degree is determined using the trigonometric membership function;

[0108] Then, based on experience, a fuzzy rule table is established, and finally, K is obtained by defuzzification. p K i The change value of is expressed as follows:

[0109]

[0110] Where K p0 It is K p The initial value ΔK p It is K p The change value of K i0 It is K i The initial value ΔK i It is K i The change value is calculated using the fuzzy PI algorithm in ARM, and the result is output through U. DA The voltage of the infrared LED is controlled by simulating voltage, and the reflectivity η of the reflector is adjusted accordingly. mWhen decreasing, increase U DA To compensate for the offset of the reference voltage;

[0111] Finally, after amplification and filtering, the compensated reference voltage is used as the feedback voltage U. f This forms a closed-loop control.

[0112] Or / and, the following methods are used to adapt to changes in signal amplitude caused by different yarn specifications:

[0113] When no yarn passes through, the yarn signal serves as a reference voltage signal. When the yarn passes through, its obstruction affects the irradiance of the photodetector, and the photocurrent I affected by the yarn obstruction is calculated accordingly. Z The size, and its specific formula are as follows:

[0114]

[0115] Where I0 is the magnitude of the reference photocurrent without being blocked by the yarn, d is the yarn diameter, and x is the width of the surface of the light source being detected; amplified signal U S Represented as:

[0116]

[0117] Among them, U ref R1 is the reference voltage at the positive input terminal of the previous stage amplifier, R2 is the current limiting resistor on the feedback network of the previous stage operational amplifier, and R2 is the variable resistor connected in series with R1.

[0118] By analyzing the structure of the conditioning circuit, combined with virtual short and virtual open circuit analysis and capacitor dynamic circuit analysis, U is derived. S The transfer function relationship with U1;

[0119] Since the input network of the operational amplifier consists of capacitor C2 and resistor R3 in series, the input impedance Z in Represented as:

[0120]

[0121] Since the feedback network consists of resistor R4 and capacitor C3 connected in parallel, the feedback impedance is Z. f Represented as:

[0122]

[0123] According to the principle of operational amplifiers, the input current equals the feedback network current, U S The relationship with U1 is as follows:

[0124]

[0125] Among them, Uref1 The reference voltage of the operational amplifier in the conditioning circuit is ignored during the dynamic analysis of the circuit.

[0126] U S The transfer function G(s) of U1(s) and U1(s) is:

[0127]

[0128] Where s is the complex frequency variable in the Laplace transform;

[0129] Based on the ARM's sampling frequency and pulse width, set U h The appropriate voltage increment is expressed as follows:

[0130] U C =U 2min +U h

[0131] The final comparison voltage U C The relationship between yarn diameter and the diameter is shown in the following formula:

[0132]

[0133] Because it is difficult to acquire signals of yarn specification changes in practical applications, the amplified yarn signal U is acquired through acquisition. S To calculate the comparison voltage U C , then U S with U C The relationship is as follows:

[0134]

[0135] Finally, based on the above calculations and analysis, when the yarn specifications change, the amplified signal U from the sampled yarn is analyzed. S After calculation with ARM, the comparator can compare voltage U. C It adapts to changes in yarn specifications.

[0136] To achieve one of the above objectives, the fourth technical solution of the present invention is as follows:

[0137] An electronic device comprising:

[0138] One or more processors;

[0139] Storage device for storing one or more programs;

[0140] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described photoelectric adaptive detection system, modeling and control method for yarn information.

[0141] To achieve one of the above objectives, the fifth technical solution of the present invention is as follows:

[0142] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned photoelectric adaptive detection system, modeling, and control method for yarn information.

[0143] Compared with existing technical solutions, the present invention has the following beneficial effects:

[0144] This invention constructs a photoelectric adaptive detection system for yarn information by setting up a controllable power supply module, a photoelectric sensor mathematical modeling module, an amplifier circuit module, a conditioning circuit module, a comparator circuit module, an ARM controller, and a photoelectric sensor module. This system uses a mathematical model to study the influence of key factors such as the reflectivity of the reflector and the yarn specification on the yarn signal in the photoelectric adaptive detection device. It can effectively improve the detection accuracy of yarn, thereby improving the working efficiency of the weft feeder and the processing quality of the loom. Therefore, it can solve the problems of low environmental anti-interference performance and weak adaptability to changes in yarn specification in existing weft feeder yarn information detection systems.

[0145] Furthermore, through continuous exploration and experimentation, this invention has constructed an exponential diode model, an infrared light-emitting diode characteristic model, a light intensity transmission model, a linear fitting model, and a signal conversion model to obtain a reference voltage U0 for the yarn signal, thereby realizing the modeling of the yarn sensing system. This facilitates the debugging and testing of the yarn sensing system, allowing for more accurate setting of sensor parameters and saving research time and effort. The solution is scientific, reasonable, and feasible.

[0146] Furthermore, the modeling method of the photoelectric adaptive detection system for yarn information in this invention uses a mathematical model to model the sensing system and studies the variable factors in the photoelectric detection device: the reflectivity of the reflector and the influence of different yarn specifications on the yarn signal. At the same time, it also provides an optimal reference voltage range for detecting the yarn signal, thus realizing the simulation of weft feeder yarn detection, reducing the workload of the initial design of weft feeder yarn detection. Through pre-modeling and simulation optimization design, and then physical verification, the trial and error costs are effectively reduced, saving time and effort.

[0147] Furthermore, compared to traditional yarn detection, the adaptive control method of this invention adjusts the reference voltage deviation caused by the reduction in reflector efficiency in real time, and also adjusts the signal amplitude changes caused by changes in yarn specifications in real time. This makes yarn detection more resistant to interference, more flexible, and more accurate, especially suitable for complex and ever-changing loom environments, and meets the increasingly diverse textile needs. Attached Figure Description

[0148] Figure 1This is a principle block diagram of a photoelectric adaptive detection system, modeling and control method for yarn information according to the present invention;

[0149] Figure 2 for Figure 1 A block diagram illustrating the modeling process of a photoelectric sensor component in China;

[0150] Figure 3 for Figure 1 A schematic diagram of a physical part of the photoelectric sensor;

[0151] Figure 4 for Figure 1 A block diagram of a reference voltage control principle based on a fuzzy PI algorithm in the ARM processor section;

[0152] Figure 5 for Figure 1 Block diagram of comparator voltage control principle based on yarn specification adaptive adjustment in the ARM processor section;

[0153] Figure 6 for Figure 1 A detailed circuit diagram of the amplifier circuit section in the image;

[0154] Figure 7 for Figure 1 A detailed circuit diagram of the conditioning and comparator circuit sections. Detailed Implementation

[0155] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0156] Conversely, this invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of the invention as defined in the claims. Furthermore, to provide a better understanding of the invention, certain specific details are described in detail below. However, those skilled in the art will fully understand the invention even without these detailed descriptions.

[0157] Unless otherwise defined, 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 invention pertains. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. The term "or / and" as used herein includes any and all combinations of one or more of the associated listed items.

[0158] A first specific embodiment of the photoelectric adaptive detection system and modeling method for yarn information of the present invention:

[0159] A modeling method for a photoelectric adaptive detection system for yarn information includes the following steps:

[0160] Step 1: Using a pre-built exponential diode model, based on the output voltage U of the ARM controller... DA Calculate the infrared LED current I;

[0161] Step two: Using a pre-built characteristic model of the infrared LED, the radiation intensity I of the infrared LED is calculated based on the current I of the infrared LED. e :

[0162] Step 3: Using a pre-constructed light intensity transmission model, based on the infrared LED radiation intensity I... e The irradiance E of the photodetector tube was calculated. e ;

[0163] Step four: Using a pre-built linear fitting model, the irradiance E of the photodetector tube is calculated. e The photocurrent I0 of the photodetector is obtained through processing.

[0164] Step 5: Based on the pre-built signal conversion model, determine the relationship between the photocurrent I0 of the photodetector tube and the reference voltage, obtain the reference voltage U0 for the yarn signal, and realize the modeling of the photoelectric adaptive detection system for yarn information.

[0165] A specific embodiment of the photoelectric adaptive detection system modeling method for yarn information of the present invention:

[0166] A photoelectric adaptive detection system for yarn information includes:

[0167] Controllable power supply module; based on the reflective efficiency η of the reflector m The system includes: a mathematical modeling module for the photoelectric sensor with installation height h and installation angle θ1θ2; an amplifier circuit module; a conditioning circuit module; a comparator circuit module; and an ARM controller. See details in [link to documentation]. Figure 1 , Figure 1 The left side (within the red dashed box on the left) constitutes a closed-loop control algorithm, namely the first adaptive method: reference voltage control based on fuzzy PI. Figure 1 The right side (within the red dashed box on the right) constitutes another control algorithm, namely the second adaptive control method: comparator voltage control based on adaptive adjustment of yarn specifications. Its connection relationship is as follows:

[0168] The input to the controllable voltage power supply module is the analog voltage U output by the ARM controller. DAThe input to the photoelectric sensor mathematical modeling module is the voltage U output by the controllable power supply. The photoelectric sensor converts the collected yarn information into a photocurrent signal I0. The input signal to the amplifier circuit is the photocurrent signal I0 from the photoelectric sensor, and the input to the conditioning circuit is the amplified yarn signal voltage U output by the amplifier circuit. S The comparator circuit has two inputs: the yarn detection signal voltage U1 output from the conditioning circuit, and the calculated comparison voltage U1 output from the ARM controller. C The ARM has two inputs, which are acquired by sampling the output U of the amplifier circuit via AD sampling. S The sensor also detects and acquires the pulse signal U2 output by the comparison circuit via IO detection. Sensor components include an infrared LED, a photodetector, a reflector, and a light-blocking element. Key parameters include the reflector's reflectivity η. m Installation height h and installation angle θ1θ2.

[0169] like Figure 2 and Figure 3 As shown, this is the second specific embodiment of the photoelectric adaptive detection system and modeling method for yarn information of the present invention:

[0170] A modeling method for a photoelectric adaptive detection system for yarn information, the modeling process of which is as follows: the input voltage of the infrared LED is the analog voltage U output by the ARM controller. DA The magnitude of the current I of the infrared LED is calculated using an exponential diode model. Based on the characteristics of the infrared LED, and substituting the luminous coefficient of a specific model, the irradiance I can be calculated from the input current I. e The input to the photodetector is the irradiance E, which is either reflected by a mirror or blocked by yarn. e Based on the characteristics of the photodetector, a raw yarn current signal I0 is output. The operational amplifier input is the current signal I0, and the reference voltage U0 is obtained after calculation. The specific steps for the mathematical modeling of the photoelectric sensor are as follows:

[0171] Step 1: The output voltage U of the ARM controller DA The infrared LED current I is calculated, including the following:

[0172] A light-emitting diode (LED) can be viewed as an exponential diode connected in series with a current sensor. The exponential diode model includes the diode current I and diode voltage U. DA The formula for calculating the relationship between them is as follows:

[0173]

[0174] Where q is the elementary charge of the electron, with a value of 1.602176 × 10⁻⁶. -19Coulomb, k is the Boltzmann constant, with a value of 1.3806503 × 10⁻⁶. -23 J / K. Furthermore, IS is the saturation current, N is the emission coefficient, and T... m1 The temperature parameters of the diode are as follows. The saturation current, emission coefficient, and diode temperature parameters can all be obtained from the datasheet of the specific infrared LED model. If the datasheet does not provide the saturation current and emission coefficient parameters, they can be calculated from its current-voltage characteristic diagram. Take two parameter points [V1, I1] and [V2, I2] from the diagram in the datasheet. The formula for calculating the saturation current IS is as follows:

[0175]

[0176] The formula for calculating the emission coefficient N is as follows:

[0177]

[0178] Where V t =kT m1 / q, the voltage U output by the ARM controller can be obtained through formula (1). DA Calculate the current I of the infrared LED.

[0179] Step 2: Calculate the infrared LED radiation intensity I from the infrared LED current I. e It includes the following:

[0180] Based on the characteristics of infrared LEDs, the ideal radiation intensity I of an infrared LED is... e It is proportional to the current I, and the formula for calculating the relationship is as follows:

[0181] I e =K1×I(4)

[0182] The proportionality coefficient K1 can be found in the manual of the specific infrared LED model. If K1 is not directly given in the manual, the radiation intensity I can be obtained through linear fitting. e The proportionality coefficient is obtained by fitting the relationship between I and the current I. The fitting process is as follows: Take I... e - The coordinates of n points in the relationship graph, A1(Ie1, I1), A2(Ie2, I2), ... A n (Ie n I n A linear fit was performed on the coordinate points using the origin. Let L be the distance from the fitted line to each point, and its calculation formula is as follows:

[0183]

[0184] After substituting the data at each point, minimizing L will allow us to solve for K1. The radiation intensity I can then be calculated from the current I of the infrared LED using equation (4). e .

[0185] Step 3: Radiation intensity I from the infrared LED e Calculate the irradiance E of the photodetector tube. e It includes the following:

[0186] As mentioned earlier, the light emitted by the infrared LED is reflected by a mirror to the photodetector, and the illuminance E radiated by the photodetector... e With respect to angles θ1 and θ2, installation height h, and reflectivity η m And it is related to the yarn specifications (yarn diameter d and color) detected by the sensor.

[0187] The effects of the emission angle θ1 and the reception angle θ2 on light transmission efficiency can be obtained by referring to the orientation characteristic diagrams in the manuals of specific infrared LEDs and photodetectors. The emission efficiency is highest (100%) when the emission angle of the infrared LED is 0°. As the emission angle shifts towards ±90°, the emission efficiency gradually decreases. The same applies to the incident angle of the photodetector. When the sensor is installed, the emission angle θ1 and the reception angle θ2 are already determined and are fixed values.

[0188] The infrared light emitted by the infrared LED travels a certain distance before reaching the photodetector, and the light intensity attenuates during transmission. This attenuation is related to the installation height h between the two. The formula for calculating the transmission distance L is as follows:

[0189]

[0190] In general, θ1 and θ2 are very small, and tanθ1 and tanθ2 are approximately equal to 1, so the transmission distance can be approximated as 2h.

[0191] Radiation intensity I e It refers to the radiative flux per unit solid angle Ω in a given direction. The calculation formula is as follows:

[0192]

[0193] Radiance E e It refers to the radiative flux φ per unit area S, and its calculation formula is as follows:

[0194]

[0195] According to geometric relationships, the solid angle is the ratio of the projected area S to the square of the sphere's radius r, and its calculation formula is as follows:

[0196]

[0197] The transmission distance 2h corresponds to the sphere radius r, which is calculated using the following formula:

[0198]

[0199] This analysis yields the irradiance E of the photodetector. e The light transmission efficiency is inversely proportional to twice the square of the installation height (2h). The higher the installation height, the greater the distance between the infrared emitter and the photodetector, resulting in lower radiation intensity received by the photodetector. When installing the sensor, the installation height is fixed. Let η be the effect of the emission angle and the incident angle on the light transmission efficiency. θ So, the fixed parameters such as the angle and height during installation affect the irradiance E. e The formula for calculating the impact is as follows:

[0200]

[0201] The light emitted by the infrared emitter must pass through a reflector before it is reflected to the photoelectric receiver. The reflectivity η of the reflector... m It also affects light transmission efficiency. In actual production processes, reflectivity is often a variable factor, related to the actual production conditions. After the influence of reflectivity, the irradiance E... e The calculation formula is as follows:

[0202]

[0203] Furthermore, the shading effect of the yarn can also affect changes in light intensity. For example... Figure 3 As shown, let the diameter of the yarn be d, the area of ​​the light source being detected in the entire system be S0, x be the length of the detected surface, and y be the width of the detected surface. Then, it is easy to obtain S0 = xy. When no yarn passes through the detection system, the light emitted by the infrared emitting tube is not blocked or interfered with by any yarn and is received by the photoelectric receiving tube. Let the irradiance received by the photoelectric receiving tube at this time be E. e0 When the yarn passes through, let the area blocked by the yarn be S1. It is easy to obtain S1 = y × d. Then, the formula for calculating the irradiance Ee1 of the photoelectric receiver tube after being blocked is as follows:

[0204]

[0205] This shows that the thicker the yarn, the more the measured area is blocked, and the greater the light intensity attenuation.

[0206] Step 4: Based on the irradiance E of the photoelectric receiver tube e The photocurrent I0 of the photodetector is calculated, including the following:

[0207] Based on the characteristics of the photodetector, under ideal conditions, the photocurrent I0 of the photodetector is related to the irradiance E. e They are proportional, and the formula for calculating their relationship is as follows:

[0208] I0 = K2 × E e (14)

[0209] The proportionality coefficient K2 can be found in the datasheet of the specific photodetector model. If K2 is not directly given in the datasheet, it can be obtained by linear fitting of the photocurrent I0 and the irradiance E. e Relationship graph fitting.

[0210] Step 5: Construct the relationship between the photocurrent I0 of the photoreceiver tube and the reference voltage U0, which includes the following:

[0211] Since the signal generated by the photodetector is a current signal and is very weak, it needs to be converted into a voltage signal and amplified. The amplification circuit used is a transimpedance amplifier circuit, such as... Figure 4 As shown, U S The terminal represents the voltage signal sampled and amplified by the ARM controller's AD converter. It can be expressed as:

[0212] U S =U ref -I0(R1+R2)(15)

[0213] Therefore, by combining the above steps, the voltage U of the infrared LED can be derived. DA Adjustment and amplification of yarn sampling signal voltage U S The relationship between (i.e., the actual voltage of the yarn signal) is as follows:

[0214]

[0215] Step Six:

[0216] When the photodetector operates at its typical value, its sensitivity to changes in light intensity reaches its maximum. Based on this, an optimal yarn signal reference voltage U0 can be calculated. Combining this with steps four and five above, and incorporating the recommended photocurrent and typical irradiance value for a specific photodetector model, a range of reference voltages can be calculated. Maintaining the yarn signal operating at this reference voltage will achieve the best detection effect. For example, using an infrared LED of model HIR89-01C / 1R and a photodetector of model SH3600, when the photodetector receives infrared light with a wavelength of 950nm, the reverse bias voltage is 5V, and the irradiance E... e 0.1mW / cm 2The photocurrent I0 is 200uA, and the reference voltage U0 is approximately 1.43V.

[0217] A first specific embodiment of the control method of the photoelectric adaptive detection system for yarn information of the present invention:

[0218] A control method for a photoelectric adaptive detection system for yarn information is disclosed, which implements reference voltage control based on fuzzy PI. The specific process is as follows:

[0219] Based on the above mathematical model of the photoelectric sensor, it can be seen that among the key factors affecting the reference voltage of the yarn signal, the installation angles θ1 and θ2 and the installation height h are fixed values, requiring only one adjustment upon powering on the weft feeder. However, the reflective efficiency η of the reflector... m These are variable factors. Therefore, this method is a novel adaptive control method for real-time adjustment of the reference voltage offset caused by the reduction in mirror efficiency. From the model, we know that the voltage U of the light-emitting diode... DA With the actual voltage U of the yarn signal S The relationship is determined by adjusting the ARM output U. DA The reference voltage U0 of the yarn signal is adjusted in real time, mainly through a fuzzy PI algorithm.

[0220] Fuzzy PI is an algorithm that automatically adjusts the parameters Kp and Ki based on ordinary PI control. The discretized formula for the ordinary PI algorithm is as follows:

[0221]

[0222] In practical applications, control performance is often related to parameter adjustment; poor parameter adjustment leads to poor control. In simple operating environments, fixing the PI parameters after adjustment may maintain good performance. However, in complex and variable environments, keeping the parameters constant may not achieve optimal closed-loop performance. Therefore, fuzzy PI algorithms that can adjust PI parameters in real time can achieve excellent control results.

[0223] like Figure 4 As shown, the previously calculated reference voltage U0 is used as the target voltage value of the fuzzy PI controller. The ARM controller's AD sampling obtains the sampled and amplified signal voltage Us, which is then filtered by median to obtain U. f As the feedback voltage of the fuzzy PI, the feedback voltage U f The voltage error value e is obtained by subtracting the voltage from the target reference voltage U0, and the error rate e is obtained by differentiating the error. cThe input is fed into the fuzzy controller for fuzzification. During fuzzification, the fuzzy subset numerical range uses seven linguistic variables: positive large (PB), positive medium (PM), positive small (PS), zero (ZO), negative small (NS), negative medium (NM), and negative large (NB). The universe of discourse range (-6, 6) corresponds to the endpoints of these seven linguistic variables. The voltage error value e is set to a range of (-1, 1), mapped to the universe of discourse, and then its membership degree is determined using a membership function. A trigonometric membership function is used; for example, when the mapped value is -3.5, its membership value to NS is 0.25, and its membership value to NM is 0.75. Similarly, the error change rate e... c The membership degree is also determined. After fuzzification, a fuzzy rule table is established based on experience, and finally, the changes in Kp and Ki are obtained by defuzzification.

[0224]

[0225] The fuzzy PI algorithm is executed in an ARM processor, and the result is output via U. DA By simulating voltage, the voltage of the infrared LED is controlled. As discussed in the previous section on photoelectric sensor modeling, U DA It can affect the reference voltage U0, when the reflective efficiency η of the reflector... m When decreasing, increase U DA This is to compensate for the offset of the reference voltage. Finally, after amplification and filtering, the compensated reference voltage is used as the feedback voltage U. f This forms a closed-loop control.

[0226] like Figure 5 As shown, this is the second specific embodiment of the control method for the photoelectric adaptive detection system for yarn information of the present invention:

[0227] A control method for a photoelectric adaptive detection system for yarn information, based on comparator voltage control that adaptively adjusts yarn specifications. The specific process is as follows:

[0228] When no yarn passes through, the yarn signal serves as a reference voltage signal. When the yarn passes through, its obstruction affects the irradiance of the photodetector, and the photocurrent I affected by the yarn obstruction is calculated accordingly. Z The size, and its specific formula are as follows:

[0229]

[0230] Where I0 is the reference photocurrent without yarn obstruction, d is the yarn diameter, and x is the width of the detected light source surface. Therefore, when no yarn passes through the detection area, the photodetector receives the highest irradiance, resulting in the largest photocurrent. When yarn passes through, the irradiance decreases, and the photocurrent changes. The thicker and larger the yarn diameter, the lower the irradiance, and the greater the change in photocurrent, resulting in a stronger signal. Correspondingly, the yarn amplification signal U after amplification is generated. S The amplitude is thus larger. Similarly, different colors of yarn absorb and block infrared light to varying degrees, which also affects the amplified signal U of the yarn. S The amplitude. From Figure 6 Circuit analysis shows that the amplified signal U S It can be represented as

[0231]

[0232] Among them, U ref R1 is the reference voltage at the positive input terminal of the previous stage amplifier mentioned earlier, R2 is the current-limiting resistor on the feedback network of the previous stage operational amplifier, and R2 is a variable resistor connected in series with R1. By... Figure 7 Based on the structural analysis of the conditioning circuit, combined with the analysis of virtual short and virtual open circuits and capacitor dynamic circuits, the transfer function relationship between U1 and U2 is further derived. The input network of the operational amplifier is a series connection of capacitor C2 and resistor R3; therefore, the input impedance Z... in It can be represented as

[0233]

[0234] If the feedback network consists of resistor R4 and capacitor C3 connected in parallel, then the feedback impedance is Z. f It can be represented as

[0235]

[0236] According to the principle of operational amplifiers, the input current equals the feedback network current, and U can be listed as follows: S The relationship with U1:

[0237]

[0238] Among them, U ref1 The reference voltage of the operational amplifier in the conditioning circuit is ignored during the dynamic analysis of the circuit. Therefore, U is calculated. S The transfer function G(s) of U1(s) and U1(s) is:

[0239]

[0240] Where s is the complex frequency variable in the Laplace transform. Based on the above analysis, it can be deduced that the change in yarn diameter d when the yarn is blocked leads to the amplified signal U. S Following G1(s), the detection signal U1 is derived. Based on the minimum value U of the yarn detection signal U1... 1min To set the comparator's comparison voltage U C This allows for the detection of the yarn's pulse signal. When U C Greater than U 1min Too much of it will reduce the response speed of the yarn, when U C Greater than U 1min If the pulse width is too small, it will be less than the ARM's sampling frequency, making it impossible to detect the pulse signal. Therefore, considering the ARM's sampling frequency and pulse width, assuming U... h For a suitable voltage increment, the corresponding calculation formula is as follows:

[0241] U C =U 2min +U h (25)

[0242] The final comparison voltage U C The relationship between yarn diameter and the diameter is shown in the following formula:

[0243]

[0244] In practical applications, signals of yarn specification changes are often difficult to acquire. This can be addressed by acquiring U... S Amplify the signal to calculate the comparison voltage U C Launch U S with U C Relationship

[0245]

[0246] Finally, based on the above calculations and analysis, when the yarn specifications change, the amplified signal U... S After calculation with ARM, the comparator can compare voltage U. C It adapts to changes in yarn specifications.

[0247] In summary, this invention first proposes a mathematical model for a photoelectric sensor based on reflectivity, transmission and reception angles, and installation height. Using this mathematical model, it studies the variable factors in the photoelectric detection device: the reflectivity of the reflector and the influence of different yarn specifications on the yarn signal. Simultaneously, it provides an optimal reference voltage range for detecting the yarn signal.

[0248] Furthermore, based on the aforementioned photoelectric sensor mathematical model, this invention provides a novel adaptive control method for real-time adjustment of the reference voltage offset caused by reduced mirror efficiency. Further, the target voltage in this method is the reference voltage U0 calculated using the photoelectric sensor mathematical model, and the feedback voltage is the yarn signal U after amplification and filtering by the ARM processor through an AD sampling amplification circuit. f The closed-loop control algorithm is a fuzzy PI algorithm.

[0249] Meanwhile, based on the aforementioned mathematical model of the photoelectric sensor, this invention provides a novel adaptive control method to adjust the comparator voltage in real time to address signal amplitude changes caused by variations in yarn specifications. Furthermore, this method uses model simulation to find the relationship between the yarn signal amplitude and the comparator voltage U. C The relationship between the sampling voltage U of the ARM processor and the ARM processor. S The yarn width is extracted, and the output real-time adjustment comparison voltage U is calculated. C .

[0250] An embodiment of a device applying the method of the present invention:

[0251] An electronic device comprising:

[0252] One or more processors;

[0253] Storage device for storing one or more programs;

[0254] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described photoelectric adaptive detection system, modeling and control method for yarn information.

[0255] An embodiment of a computer medium applying the method of the present invention:

[0256] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned photoelectric adaptive detection system, modeling, and control method for yarn information.

[0257] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code.

[0258] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0259] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0260] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0261] The model in this application is an object that uses physical or virtual representation to objectively describe the form and structure. The object is not the same as a physical object, and is not limited to physical or virtual. It can be a data processing function, software program, processing mode, usage method, operation mode, workflow, application process, electronic hardware, circuit module, processing system, system imitation or simulation object.

[0262] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify or make equivalent substitutions to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A photoelectric adaptive detection system for yarn information, characterized in that: include: Controllable power supply module, photoelectric sensor mathematical modeling module, amplifier circuit module, conditioning circuit module, comparator circuit module, ARM controller and photoelectric sensor module; The input to the controllable power supply module is the analog voltage U output by the ARM controller. DA , The input to the mathematical modeling module for the photoelectric sensor is the voltage U output from the controllable power supply module. The photoelectric sensor module converts the collected yarn information into a photocurrent signal I0. The input signal to the amplifier circuit module is the photocurrent signal I0 from the photoelectric sensor module. The input to the conditioning circuit module is the yarn amplified signal voltage U output from the amplifier circuit module. S , The comparator circuit module has two inputs: the yarn detection signal voltage U1 output from the conditioning circuit module, and the calculated comparison voltage U1 output from the ARM controller. C , The ARM controller has two inputs: one is the amplified signal U output from the amplifier module, which is acquired via AD sampling. S , and the pulse signal U2 output by the comparison circuit module through IO detection; The photoelectric sensor module includes an infrared LED, a photoelectric receiver, a reflector, and a light-blocking body. Its parameters include the reflector's reflectivity η. m Installation height h and installation angles θ1 and θ2; The installation angle θ1 is the emission angle θ1 of the infrared emitting tube; The installation angle θ2 is the receiving angle θ2 of the photoelectric receiver tube.

2. A modeling method for a photoelectric adaptive detection system for yarn information, characterized in that: The photoelectric adaptive detection system for yarn information as described in claim 1 includes the following modeling method: Step 1: Using a pre-built exponential diode model, based on the output voltage U of the ARM controller... DA Calculate the infrared LED current I; Step two: Using a pre-built characteristic model of the infrared LED, the radiation intensity I of the infrared LED is calculated based on the current I of the infrared LED. e : Step 3: Using a pre-constructed light intensity transmission model, based on the infrared LED radiation intensity I... e The irradiance E of the photodetector tube was calculated. e ; Step four: Using a pre-built linear fitting model, the irradiance E of the photodetector tube is calculated. e The photocurrent I0 of the photodetector is obtained through processing. Step 5: Based on the pre-built signal conversion model, determine the relationship between the photocurrent I0 of the photodetector tube and the reference voltage, obtain the reference voltage U0 for the yarn signal, and realize the modeling of the photoelectric adaptive detection system for yarn information.

3. The modeling method for a photoelectric adaptive detection system for yarn information as described in claim 2, characterized in that: Step 1: Using a pre-built exponential diode model, based on the output voltage U of the ARM controller... DA The method for calculating the infrared LED current I is as follows: Since the light-emitting diode is an exponential diode connected in series with a current sensor, based on the characteristics of an exponential diode, the diode current I and diode voltage U are constructed as part of the exponential diode model. DA The calculation formula is as follows: Where q is the elementary charge of the electron, with a value of q / q. Coulomb, k is the Boltzmann constant, with a value of IS is the saturation current, N is the emission coefficient, and T is the emission coefficient. m1 These are the temperature parameters of the diode; The formula for calculating the saturation current IS is as follows: Where [V1, I1] and [V2, I2] are two parameter points; The formula for calculating the emission coefficient N is as follows: in , By calculating the relationship and based on the output voltage U of the ARM controller DA Calculate the current I of the infrared LED.

4. The modeling method for a photoelectric adaptive detection system for yarn information as described in claim 2, characterized in that: Step two: Using a pre-built characteristic model of the infrared LED, the radiation intensity I of the infrared LED is calculated based on the current I of the infrared LED. e The method is as follows: Based on the characteristics of infrared LEDs, the radiation intensity I of the infrared LED is created. e The proportional relationship between the current I and the given current is calculated using the following formula: Where K1 is the proportionality coefficient, which is obtained by linearly fitting the radiation intensity I. e The relationship with current I is obtained, and the fitting process is as follows: Take I e - The n coordinate points in the I relationship diagram: A1(I e1 ,I1),A2(I e2 ,I2),……A n (I en I n ); A linear fit was performed on the coordinate points at the origin; The distance L from the fitted line to each point is calculated using the following formula: Among them, I ei Let I be the radiation intensity at the i-th coordinate point. i Let be the current at the i-th coordinate point; After substituting the data for each coordinate point, the proportionality coefficient K1 is solved by minimizing L. Substituting the solved proportionality coefficient K1 and the current I of the infrared LED into the formula for calculating the proportional relationship, the radiation intensity I is calculated. e .

5. The modeling method for a photoelectric adaptive detection system for yarn information as described in claim 2, characterized in that: Step 3: Using a pre-constructed light intensity transmission model, based on the infrared LED radiation intensity I... e The irradiance E of the photodetector tube was calculated. e The method is as follows: Based on the light transmission path emitted by the infrared LED, the factors affecting the irradiance E of the photodetector are screened. e The relevant variables include angle θ1, angle θ2, installation height h, and reflectivity η. m And the yarn diameter d and color detected by the sensor; The infrared light emitted by the infrared LED travels a certain distance before reaching the photodetector, and the light intensity attenuates during transmission. This attenuation is related to the installation height h between the two components. Based on this, a formula for calculating the transmission distance L is constructed as follows: Since θ1 and θ2 are both very small, tanθ1 and tanθ2 are approximately equal to 1, and according to the formula for calculating transmission distance, the transmission distance is 2h. Radiation intensity I e It refers to the radiative flux φ per unit solid angle Ω in a given direction, and its calculation formula is as follows: Radiance E e It refers to the radiative flux φ per unit area S, and its calculation formula is as follows: According to geometric relationships, the solid angle is the ratio of the projected area S to the square of the sphere's radius r, and its calculation formula is as follows: Based on the sphere radius r corresponding to a transmission distance of 2h, construct the irradiance E of the photoelectric receiver tube. e The formula for calculating the first illuminance is as follows: Based on the first calculation formula, the irradiance E of the photoelectric receiver tube is analyzed. e Influence characteristics; The influencing characteristics include the following: Photodetector irradiance E e The intensity of radiation is inversely proportional to twice the square of the installation height (2h). The higher the installation height, the farther the distance between the infrared emitter and the photoelectric receiver, and the lower the radiation intensity received by the photoelectric receiver. When installing the sensor, the installation height is already determined and is a fixed value. Based on the influencing characteristics and the effects of emission angle and incident angle on optical transmission efficiency η θ Create the photoelectric receiver tube irradiance E with fixed parameters for angle and height during installation. e The effect expression, i.e., the formula for calculating the second illuminance, is as follows: The light emitted by the infrared emitter must pass through a reflector before being reflected to the photoelectric receiver. The reflectivity η of the reflector... m This also affects light intensity transmission efficiency. Therefore, the second illuminance calculation formula is optimized to obtain the third illuminance calculation formula, which is as follows: Since the shading of yarn also affects the change in light intensity, the third illuminance calculation formula is optimized to obtain the fourth illuminance calculation formula, which is as follows: Among them, E e0 The infrared emitting tube emits light that is not blocked or interfered with by any yarn, and the photoelectric receiving tube receives the irradiance, E. e1 S1 represents the irradiance of the photoelectric receiver tube after the yarn is blocked when it passes through, d is the diameter of the yarn, S0 is the area of ​​the light source being detected in the entire system, x is the length of the detected surface, y is the width of the detected surface, and S1 is the area blocked by the yarn to be tested.

6. The modeling method for a photoelectric adaptive detection system for yarn information as described in claim 2, characterized in that: Step four: Using a pre-built linear fitting model, the irradiance E of the photodetector tube is calculated. e The method for processing and obtaining the photocurrent I0 of the photodetector is as follows: Based on the characteristics of the photodetector, the relationship between the photocurrent I0 and the irradiance E of the photodetector is established. e The formula for calculating the proportional relationship is as follows: The K2 proportionality coefficient is obtained by fitting the photocurrent I0 and the irradiance E. e The relationship was established.

7. The modeling method for a photoelectric adaptive detection system for yarn information as described in claim 2, characterized in that: Step 5: Based on the pre-built signal conversion model, determine the relationship between the photocurrent I0 of the photodetector and the reference voltage, and obtain the reference voltage U0 for the yarn signal as follows: Based on the fact that the signal generated by the photodetector is a current signal and is very weak, a calculation formula for a transimpedance amplifier circuit is constructed to convert the current signal into a voltage signal and amplify the signal. The specific expression of the calculation formula for the transimpedance amplifier circuit is as follows: Among them, U S U is the voltage of the ARM controller's AD sampling and amplification signal. ref R1 is the reference voltage at the positive input terminal of the amplifier, R2 is the current-limiting resistor on the feedback network, and R2 is the variable resistor connected in series with R1. Based on the calculation formula for the transimpedance amplifier circuit, construct the infrared LED voltage U. DA With yarn sampling amplified signal voltage U S The relationship, namely the voltage transformation relationship between the actual voltages of the yarn signal, is as follows: Based on the voltage transformation formula, by substituting the recommended photocurrent and typical irradiance value of a specific photodetector, a range of reference voltage U0 is calculated, so that the yarn signal can achieve the best detection effect when running under this reference voltage.

8. A control method for a photoelectric adaptive detection system for yarn information, characterized in that: The photoelectric adaptive detection system for yarn information as described in claim 1 includes a reference voltage control method based on fuzzy PI and a comparator voltage control method based on adaptive adjustment of yarn specifications. A reference voltage control method is used to adjust the reference voltage deviation caused by the reduction in mirror efficiency in real time; A comparator voltage control method is used to adjust the signal amplitude in real time according to the changes in yarn specifications.

9. The control method for a photoelectric adaptive detection system for yarn information as described in claim 8, characterized in that: The reference voltage control method based on fuzzy PI includes the following: The calculated reference voltage value U0 is used as the target voltage value of the fuzzy PI controller, and the amplified yarn signal U is sampled by the AD converter of the ARM controller. S U obtained after filtering f The feedback voltage U of the fuzzy PI controller f Feedback voltage U f The voltage error value e is obtained by subtracting the voltage from the target reference voltage U0, and the error rate e is obtained by differentiating the error. c The data is input into the fuzzy controller, where it is fuzzified and closed-loop control is used to ensure that the photoelectric sensor and the detection circuit operate in the optimal state. Or / and, the comparator voltage control method based on yarn specification adaptive adjustment includes the following: The signal U is amplified by sampling the yarn using an ARM controller's AD converter. S This signal is used as the basis for calculating the comparison voltage in the subsequent comparison circuit module. Through circuit analysis, the transfer functions of the conditioning circuit input and output are established, and the relationship between the change in yarn specifications and the comparison voltage is found, which includes the yarn amplification signal U. S Comparison voltage U C The relationship formula is used to achieve real-time adjustment of the comparison voltage to adapt to changes in signal amplitude caused by different yarn specifications.

10. The control method for a photoelectric adaptive detection system for yarn information as described in claim 9, characterized in that: The following method employs a fuzzy PI controller for processing and closed-loop control: Voltage U based on light-emitting diode DA With the actual voltage U of the yarn signal S The relationship is used to construct a discrete formula for the fuzzy PI algorithm, which is then used to adjust the output U of the ARM controller. DA To adjust the reference voltage U0 of the yarn signal in real time; The expression for the discrete formula of the fuzzy PI algorithm is as follows: Among them, K p and K i Here are the algorithm parameters, U(k) is the output voltage after fuzzy PI calculation, and e(k) is the error between the actual and theoretical values ​​of the reference voltage. Meanwhile, seven linguistic variables for the fuzzy subset values ​​are set, including positive large PB, positive medium PM, positive small PS, zero ZO, negative small NS, negative medium NM, and negative large NB. The universe of discourse range (-6, 6) is set to correspond to the endpoints of the seven linguistic variables respectively. The range of the voltage error value e is set to (-1, 1), and it is mapped to the universe of discourse. Then, its membership degree is determined using the trigonometric membership function; Then, based on experience, a fuzzy rule table is established, and finally, K is obtained by defuzzification. p K i The change value of is expressed as follows: Where K p0 It is K p The initial value, ΔK p It is K p The change value of K i0 It is K i The initial value, ΔK i It is K i The change value is calculated using the fuzzy PI algorithm in ARM, and the result is output through U. DA The voltage of the infrared LED is controlled by simulating voltage, and the reflectivity η of the reflector is adjusted accordingly. m When decreasing, increase U DA To compensate for the offset of the reference voltage; Finally, after amplification and filtering, the compensated reference voltage is used as the feedback voltage U. f This forms a closed-loop control. Or / and, the following methods are used to adapt to changes in signal amplitude caused by different yarn specifications: When no yarn passes through, the yarn signal serves as a reference voltage signal. When the yarn passes through, its obstruction affects the irradiance of the photodetector, and the photocurrent I affected by the yarn obstruction is calculated accordingly. Z The size, and its specific formula are as follows: Where I0 is the magnitude of the reference photocurrent without being blocked by the yarn, d is the yarn diameter, and x is the width of the surface of the light source being detected; amplified signal U S Represented as: Among them, U ref R1 is the reference voltage at the positive input terminal of the previous stage amplifier, R2 is the current limiting resistor on the feedback network of the previous stage operational amplifier, and R2 is the variable resistor connected in series with R1. By analyzing the structure of the conditioning circuit, combined with virtual short and virtual open circuit analysis and capacitor dynamic circuit analysis, U is derived. S The transfer function relationship with U1; Since the input network of the operational amplifier consists of capacitor C2 and resistor R3 in series, the input impedance Z in Represented as: Since the feedback network consists of resistor R4 and capacitor C3 connected in parallel, the feedback impedance is Z. f Represented as: According to the principle of operational amplifiers, the input current equals the feedback network current, U S The relationship with U1 is as follows: in, U ref1 The reference voltage of the operational amplifier in the conditioning circuit is ignored during the dynamic analysis of the circuit. U S The transfer function G(s) of U1(s) and U1(s) is: Where s is the complex frequency variable in the Laplace transform; Based on the ARM's sampling frequency and pulse width, set U h The appropriate voltage increment is expressed as follows: The final comparison voltage U C The relationship between yarn diameter and the diameter is shown in the following formula: Because it is difficult to acquire signals of yarn specification changes in practical applications, the amplified yarn signal U is acquired through acquisition. S To calculate the comparison voltage U C , then U S with U C The relationship is as follows: Finally, based on the above calculations and analysis, when the yarn specifications change, the amplified signal U from the sampled yarn is analyzed. S After calculation with ARM, the comparator can compare voltage U. C It adapts to changes in yarn specifications.

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