Precision control method and system for photoelectric sensor of industrial internet and readable medium

Abstract

The invention relates to an industrial internet photoelectric sensor precision control method and system and a readable medium, and aims to solve the problems of signal instability and measurement precision reduction caused by interference of temperature, humidity, vibration and the like of a photoelectric sensor in a complex industrial environment. The method comprises the steps of signal acquisition, signal preprocessing, error compensation, dynamic optimization, feedback control and the like, wherein denoising processing is performed on signals through an adaptive filtering algorithm, and random noise is eliminated; calculating an error compensation factor based on the multi-dimensional environmental parameters, and correcting the external interference influence of the signal through a sensitivity model; and the gain and exposure time of the photoelectric sensor are dynamically adjusted by using a closed-loop control algorithm, so that signal output is optimized. Besides, the system adopts an industrial internet communication protocol and is deeply fused with a cloud platform, so that remote monitoring, parameter optimization and self-learning capabilities are realized. The photoelectric sensor is suitable for complex scenes such as optical element detection, industrial robot control and wind power generation monitoring, and the anti-interference capability and the measurement precision of the photoelectric sensor are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of photoelectric sensor precision control technology, and in particular to a photoelectric sensor precision control method, system and readable medium for the industrial Internet. Background Art

[0002] Photoelectric sensors have been widely used in industrial detection, automatic control, and intelligent manufacturing due to their high sensitivity, fast response, and non-contact measurement. However, there are still some technical difficulties and shortcomings in the actual application of photoelectric sensors in complex industrial environments, which are mainly reflected in the following aspects:

[0003] Serious environmental interference and poor signal stability: In industrial production, environmental factors such as temperature, humidity, and vibration can have a significant impact on the output signal of photoelectric sensors. For example, temperature changes can cause thermal expansion of sensor materials, leading to measurement deviations; humidity changes can cause condensation on the surface of photoelectric components, affecting optical performance; and mechanical vibrations can directly interfere with the output stability of the sensor. These external environmental interferences can cause random noise and drift in sensor signals, making it difficult for measurement accuracy to meet the high requirements of industrial applications.

[0004] Traditional signal processing technology is difficult to meet the needs of dynamic compensation: At present, the signal processing methods of many photoelectric sensors mainly rely on filtering algorithms with fixed parameters (such as low-pass filtering, Gaussian filtering, etc.). These methods are effective in processing specific types of noise, but they are powerless for the dynamic changes of multi-source interference in complex environments (such as rapid temperature fluctuations and random changes in vibration amplitude), and cannot dynamically compensate for the impact of external factors on sensor performance in real time.

[0005] The error compensation model is not accurate enough and has poor versatility: Some high-end photoelectric sensors use error compensation algorithms (such as polynomial fitting or interpolation methods) to correct environmental influences, but these compensation models are usually based on single environmental test data in the laboratory and lack adaptability to complex working conditions. For example, when there is a coupling effect between environmental parameters (such as temperature, humidity, and vibration), the existing model cannot accurately capture these interactive effects, resulting in low compensation accuracy.

[0006] Lack of deep integration with the Industrial Internet: Existing photoelectric sensors are mostly isolated systems in industrial environments, usually only implementing localized data processing and feedback control, and lack deep integration with the Industrial Internet. This limitation makes it impossible for sensors to achieve remote data monitoring, real-time analysis and optimization, and cannot meet the needs of the development of smart manufacturing and the Industrial Internet of Things.

[0007] Signal processing hardware resources are limited, making it difficult to balance high precision and real-time performance: Photoelectric sensors are usually small in size and have limited hardware resources. Traditional high-precision signal processing algorithms (such as Kalman filtering) require large computing resources and are difficult to run efficiently on sensor hardware platforms. This contradiction is particularly evident in real-time industrial applications that pursue high precision and low latency.

[0008] Therefore, we urgently need to design industrial Internet photoelectric sensor precision control methods, systems and readable media to solve the above problems. Summary of the invention

[0009] On the one hand, the present invention proposes a method for controlling the precision of a photoelectric sensor of an industrial Internet, the method comprising the following steps:

[0010] Optical signal acquisition: Use photoelectric sensors to collect the optical signal of the target object and generate the original signal S(t), where: S(t): represents the light intensity signal at time t;

[0011] Signal preprocessing: De-noise and filter the collected signal S(t) using an adaptive sliding window filtering algorithm:

[0012]

[0013] Where: S′(t): filtered signal; W(t): adaptive window size, calculated by the following formula:

[0014]

[0015] Among them, T c : filtering time constant; Δt: sampling time interval;

[0016] Error compensation: Combine the environmental parameters E(t) to perform error compensation on S′(t) and obtain the compensation signal S c (t), the calculation formula is:

[0017] S c (t)=S′(t)·(1+k1T+k2H+k3V)

[0018] Where: S c (t): compensated signal; T: ambient temperature; H: ambient humidity; V: vibration amplitude; k1, k2, k3: compensation coefficients for temperature, humidity and vibration respectively;

[0019] Dynamic optimization: According to the reference signal S ref Calculation error e(t):

[0020] e(t)=S ref -S c (t)

[0021] Where: e(t): dynamic error; S ref : Ideal signal reference value; dynamically adjust the gain G and exposure time T of the photoelectric sensor according to the error e(t) e .

[0022] As a preferred technical solution of the present invention, the expression of the environmental parameter E(t) is:

[0023] E(t)=w1T+w2H+w3V

[0024] Where: E(t): the comprehensive impact value of environmental parameters on the signal, indicating the impact of the environment on the measurement signal of the photoelectric sensor; w1, w2, w3: the weighted coefficients of environmental factors, indicating the weights of the impact of temperature, humidity and vibration on the signal, respectively, satisfying:

[0025] w1+w2+w3=1

[0026] Compensation coefficient k i (i=1,2,3) is calculated by the following formula:

[0027]

[0028] in: : Partial derivative symbol, indicating that when taking the derivative of a variable of a multivariable function, the other variables remain unchanged k i : Compensation coefficient, indicating the sensitivity of the sensor to environmental factors T, H, V; x i :Environment variables, where x1=T, x2=·, x3=V.

[0029] As a preferred technical solution of the present invention, the dynamic adjustment of the photoelectric sensor gain G and the exposure time T e The formula is:

[0030]

[0031] Where: G(t): gain after dynamic adjustment; T e (t): exposure time after dynamic adjustment; G0: initial gain; T e0 : Initial exposure time; S ref : Reference signal strength.

[0032] As a preferred technical solution of the present invention, the error compensation algorithm further includes a nonlinear compensation mechanism, and the compensation formula is:

[0033]

[0034] Where: α: error control factor, used to suppress sudden errors caused by environmental parameters; e(t): dynamic error.

[0035] The present invention also provides an industrial Internet photoelectric sensor precision control system, comprising the following modules:

[0036] Photoelectric sensor module: used to collect the optical signal S(t) of the target object;

[0037] Data processing module: denoise, filter and compensate S(t) to generate S c (t);

[0038] Feedback control module: By adjusting the photoelectric sensor gain G and exposure time T e Optimize signal quality;

[0039] Communication module: The compensated signal S c (t) and environmental parameters E(t) are transmitted to the remote platform via the Industrial Internet protocol.

[0040] As a preferred technical solution of the present invention, the data processing module adopts a multi-stage filtering mechanism, including: Gaussian filter:

[0041]

[0042] Where: σ: standard deviation of the filter; S′(t): filtered signal;

[0043] Kalman Filter:

[0044]

[0045] in: Signal estimation at the current moment; K t : Kalman gain, satisfying:

[0046]

[0047] Among them, P t|t-1 : prediction error covariance; R: measurement noise covariance.

[0048] As a preferred technical solution of the present invention, the feedback control module is based on the following closed-loop control model:

[0049]

[0050] Where: u(t): control signal; K p ,K i ,K d : are proportional, integral and differential coefficients respectively; e(t): dynamic error.

[0051] As a preferred technical solution of the present invention, the communication module adopts the MQTT protocol based on the industrial Internet, supports data transmission delay less than 10ms, and ensures real-time transmission of signal S c (t).

[0052] The present invention also provides a readable medium, on which instructions are stored. When the instructions are executed on an electronic device, the electronic device executes the method for controlling the accuracy of photoelectric sensors in the industrial Internet.

[0053] Beneficial effects:

[0054] The present invention effectively solves the problem of unstable signals and reduced measurement accuracy of photoelectric sensors in complex industrial environments due to external factors such as temperature, humidity, and vibration by introducing adaptive filtering, dynamic error compensation, and feedback control algorithms. Compared with the prior art, the signal processing method of the present invention has higher real-time performance and adaptability, and can dynamically adjust the filter window, error compensation parameters, and control strategies, significantly improving the anti-interference ability and measurement accuracy of the sensor. In addition, by establishing a sensitivity model of environmental variables and signal characteristics, the compensation algorithm can accurately correct the multi-dimensional environmental coupling effect and achieve accurate restoration of signals under complex interference conditions.

[0055] The present invention also deeply integrates photoelectric sensors with the industrial Internet, and realizes the functions of remote monitoring, real-time parameter adjustment and intelligent optimization through communication modules and industrial Internet platforms. Combined with the remote analysis capabilities of the industrial Internet of Things, the system can self-learn and optimize based on historical data and real-time operating status, improving the automation level and efficiency of industrial production. The present invention is suitable for a variety of scenarios such as optical component detection, robot motion control, wind power generation monitoring, etc., and provides a high-precision, high-reliability, and intelligent solution for industrial detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 Flow chart of the photoelectric sensor accuracy control method for the Industrial Internet. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] The following is combined with Figure 1 , the specific implementation methods of the present invention are described in detail.

[0060] The system of the present invention comprises the following modules: a photoelectric sensor module: used to collect the optical signal S(t) of the target object; a data processing module: denoising the collected signal, using an adaptive sliding window filter and an error compensation algorithm;

[0061] Feedback control module: Dynamically adjust the gain G and exposure time T of the photoelectric sensor based on the closed-loop control model e ;

[0062] Communication module: realize remote data transmission and control through industrial Internet protocols (such as MQTT);

[0063] Industrial Internet platform: realize data analysis, fault diagnosis and remote control.

[0064] The implementation process of the system is as follows: the photoelectric sensor module collects the signal S(t) in real time and transmits the data to the data processing module;

[0065] The data processing module performs denoising on S(t), filters out environmental interference noise, and generates a signal S′(t); calculates the environmental parameter E(t) and performs error compensation on S′(t) based on the compensation formula to obtain a compensation signal S c (t);

[0066] Dynamically calculate the error e(t) and adjust the photoelectric sensor gain G and exposure time T through the feedback control module e ;

[0067] The final signal and system operation status are uploaded to the industrial Internet platform through the communication module.

[0068] Signal acquisition and preprocessing: The photoelectric sensor module collects optical signals in real time and generates the original signal S(t).

[0069] The signal may contain noise caused by environmental interference (such as temperature, humidity, vibration). The following adaptive sliding window filtering algorithm is used to denoise S(t):

[0070]

[0071] Where: S′(t): filtered signal; Indicates the window size, which is determined by the filter time constant T c and the sampling interval Δt.

[0072] Error compensation: Calculate the environmental parameter E(t) according to the actual working environment of the sensor:

[0073] E(t)=w1T+w2H+w3V

[0074] Where: T, H, V: ambient temperature (℃), humidity (%), vibration amplitude (mm);

[0075] w1,w2,w3: corresponding weight coefficients, satisfying w1+w2+w3=1.

[0076] Based on the environmental parameter E(t), the signal S′(t) is compensated:

[0077] S c (t)=S′(t)·(1+k1T+k2H+k3V)

[0078] Among them: k1, k2, k3: represent the sensitivity of the sensor to temperature, humidity, and vibration respectively, and the calculation formula is:

[0079]

[0080] Dynamic optimization calculation error e(t):

[0081] e(t)=S ref -S c (t)

[0082] Dynamically adjust the photoelectric sensor gain G and exposure time T e The formula is:

[0083]

[0084] Where: G0,T e0 : Initial gain and initial exposure time;

[0085] S ref : Reference signal strength.

[0086] Feedback control: Using PID controller to optimize dynamic error:

[0087]

[0088] Where: u(t): control signal; K p ,K i ,K d: Proportional, integral, and differential coefficients.

[0089] Data transmission and industrial Internet integration system use MQTT protocol to transmit signal S c (t) and status data are uploaded to the industrial Internet platform for remote monitoring and parameter adjustment.

[0090] The following is a specific explanation with reference to several embodiments;

[0091] Example 1: Surface defect detection of high-precision optical components;

[0092] An optical component manufacturing company needs to detect surface defects of lenses and collect reflected light signals through photoelectric sensors. Due to the influence of temperature fluctuations (20℃-40℃), humidity (30%-90%) and vibration (0-2mm) in the workshop environment, the detection accuracy is low, and the method of the present invention is needed to perform signal processing and error compensation.

[0093] Calculation process: Signal acquisition: The original signal collected by the photoelectric sensor:

[0094] S(t)=S true (t)+n(t)

[0095] Where: S true (t) = 50·sin(2πft): actual reflected light signal; n(t): environmental noise, including interference caused by temperature, humidity and vibration; f = 10: signal frequency, in Hz.

[0096] Assuming that sampling is performed within t=0, 0.1, 0.2, …, 1s, the initial acquisition value of S(t) is:

[0097] S(t)=[50.0, 48.1, 42.7, 34.2, 23.0, 9.6, -5.1, -19.4, -31.9, -41.3, -46.6] (the signal contains environmental noise).

[0098] Signal preprocessing: Use sliding window filtering (window size W = 5) to denoise S(t):

[0099]

[0100] Apply filtering to the above collected values, the calculation process is as follows: For t = 0.1s:

[0101]

[0102] For t = 0.2s:

[0103]

[0104] After filtering, the obtained signal sequence is:

[0105] S′(t)=[50.0,48.5,45.7,41.4,35.2,27.0,17.2,6.6,-4.5,-15.0,-24.3].

[0106] Error compensation: The temperature measured by the environmental sensor is T = 30°C, the humidity is H = 50%, and the vibration amplitude is V = 1.0 mm.

[0107] Weight coefficient w1=0.4, w2=0.3, w3=0.3, environmental parameters: E(t)=w1T+w2H+w3V=0.4·30+0.3·50+0.3·1.0=27.3.

[0108] The compensation formula is: S c (t)=S′(t)·(1+k1T+k2H+k3V).

[0109] Assume: k1 = 0.001, k2 = 0.002, k3 = 0.01, calculate the compensation factor:

[0110] k1T+k2H+k3V=0.001·30+0.002·50+0.01·1=0.11

[0111] but:

[0112] S c (t) = S′(t)·(1+0.11)

[0113] Compute the compensation value for each filtered signal:

[0114] t=0.1s:S c (0.1) = 48.5 1.11 = 53.8

[0115] t=0.2s:S c (0.2) = 45.7 1.11 = 50.7,

[0116] The signal sequence after compensation is: S c (t)=[50.0,53.8,50.7,45.9,39.1,30.0,19.1,7.3,-5.0,-16.6,-27.0]

[0117] Dynamic optimization: reference signal strength S ref =50.0, calculate the dynamic error:

[0118] e(t)=S ref -S c (t))

[0119] t=0.1s:

[0120] e(0.1)=50.0-53.8=-3.8

[0121] t=0.2s:

[0122] e(0.2)=50.0-50.7=-0.7

[0123] Adjust the gain G(t) and exposure time T e (t):

[0124]

[0125] Assume G0 = 2.0, for t = 0.1s:

[0126]

[0127] Result analysis: Compensated signal S c (t) Reduced fluctuations caused by environmental interference, the final signal fluctuation range was reduced from ±10% to ±2%. Through dynamic optimization control, the accuracy of optical component surface defect detection was improved to ±0.2μm.

[0128] Example 2: Optimizing the positioning accuracy of industrial robot arms;

[0129] An industrial robot in a smart factory needs to operate precisely on the assembly line. The positioning accuracy of its arm is affected by humidity and vibration, causing the movement deviation to exceed the tolerance range of ±1mm.

[0130] Calculation process: Acquisition signal: The sampling sequence of the robot arm operation signal S(t) is:

[0131] S(t)=[500.0,498.0,495.0,490.0,485.0,480.0]

[0132] Environmental parameters: humidity H = 60%, vibration V = 1.5mm.

[0133] Calculate the environmental parameters E(t)=0.5H+0.5V=0.5·60+0.5·1.5=30.75.

[0134] Compensation process: Use the compensation formula to calculate the compensation signal S c (t):

[0135] S c (t)=S′(t)·(1+0.005H+0.01V)

[0136] Calculate S for each point c (t).

[0137] Feedback optimization and adjustment: Dynamic adjustment of G(t) and T e (t), according to e(t) = S ref -S c (t)Optimization.

[0138] Results: The positioning deviation was reduced from ±1.2mm to ±0.1mm, and the robot operation accuracy was improved to 99.8%.

[0139] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the precision of photoelectric sensors in industrial Internet, characterized in that: The method comprises the following steps: Optical signal acquisition: Use photoelectric sensors to collect the optical signal of the target object and generate the original signal S(t), where: S(t): represents the light intensity signal at time t; Signal preprocessing: De-noise and filter the collected signal S(t) using an adaptive sliding window filtering algorithm: Where: S′(t): filtered signal; W(t): adaptive window size, calculated by the following formula: Among them, T c : filtering time constant; Δt: sampling time interval; Error compensation: Combine the environmental parameters E(t) to perform error compensation on S′(t) and obtain the compensation signal S c (t), the calculation formula is: S c (t)=S′(t)·(1+k1T+k2H+k3V) Where: S c (t): compensated signal; T: ambient temperature; H: ambient humidity; V: vibration amplitude; k1, k2, k3: compensation coefficients for temperature, humidity and vibration respectively; Dynamic optimization: According to the reference signal S ref Calculation error e(t): e(t)=S ref -S c (t) Where: e(t): dynamic error; S ref : Ideal signal reference value; dynamically adjust the gain G and exposure time T of the photoelectric sensor according to the error e(t) e .

2. The method for controlling the precision of photoelectric sensors of the industrial Internet according to claim 1 is characterized in that: The expression of the environmental parameter E(t) is: E(t)=w1T+w2H+w3V Where: E(t): the comprehensive impact value of environmental parameters on the signal, indicating the impact of the environment on the measurement signal of the photoelectric sensor; w1, w2, w3: the weighted coefficients of environmental factors, indicating the weights of the impact of temperature, humidity and vibration on the signal, respectively, satisfying: w1+w2+w3=1 Compensation coefficient k i (i=1,2,3) is calculated by the following formula: x i ∈{T,H,V} in: The partial derivative symbol indicates that when taking the derivative of a variable of a multivariable function, the other variables remain unchanged. i : Compensation coefficient, indicating the sensitivity of the sensor to environmental factors T, H, V; x i :Environment variables, where x1=T, x2=H, x3=V.

3. The method for controlling the precision of photoelectric sensors of the industrial Internet according to claim 1 is characterized in that: The photoelectric sensor gain G and exposure time T are dynamically adjusted e The formula is: Where: G(t): gain after dynamic adjustment; T e (t): exposure time after dynamic adjustment; G0: initial gain; T e0 : Initial exposure time; S ref : Reference signal strength.

4. The method for controlling the precision of photoelectric sensors of the industrial Internet according to claim 1 is characterized in that: The error compensation algorithm further includes a nonlinear compensation mechanism, and the compensation formula is: Where: α: error control factor, used to suppress sudden errors caused by environmental parameters; e(t): dynamic error.

5. An industrial Internet photoelectric sensor precision control system, characterized in that: Includes the following modules: Photoelectric sensor module: used to collect the optical signal S(t) of the target object; Data processing module: denoise, filter and compensate S(t) to generate S c (t); Feedback control module: By adjusting the photoelectric sensor gain G and exposure time T e Optimize signal quality; Communication module: The compensated signal S c (t) and environmental parameters E(t) are transmitted to the remote platform via the Industrial Internet protocol.

6. The industrial Internet photoelectric sensor precision control system according to claim 5 is characterized in that: The data processing module adopts a multi-stage filtering mechanism, including: Gaussian filter: Where: σ: standard deviation of the filter; S′(t): filtered signal; Kalman Filter: in: Signal estimation at the current moment; K t : Kalman gain, satisfying: Among them, P t|t-1 : prediction error covariance; R: measurement noise covariance.

7. The industrial Internet photoelectric sensor precision control system according to claim 5 is characterized in that: The feedback control module is based on the following closed-loop control model: Where: u(t): control signal; K p ,K i ,K d : are proportional, integral and differential coefficients respectively; e(t): dynamic error.

8. The industrial Internet photoelectric sensor precision control system according to claim 5 is characterized in that: The communication module adopts the MQTT protocol based on the industrial Internet, supports data transmission delay less than 10ms, and ensures real-time transmission of signal S c (t).

9. A readable medium, characterized in that The readable medium stores instructions, which, when executed on an electronic device, enable the electronic device to execute the method for controlling the accuracy of photoelectric sensors in the industrial Internet as described in any one of claims 1 to 4.

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