Automatic cleaning device, control method and control system of photoelectric impurity removing machine

Abstract

The invention discloses an automatic cleaning device, a control method and a control system of a photoelectric impurity removing machine, and relates to the technical field of automation control of tobacco equipment. The method comprises the following steps: cleaning the surface of the photoelectric cleaner by using a cleaning brush and a dust collection system, and monitoring the bristle pressure and dust concentration of the cleaning brush in real time; the cleaning brush is combined with sequential injection of the air nozzle for deep cleaning, and the bristle pressure and the dust concentration of the cleaning brush are monitored in real time; cleaning parameters are dynamically adjusted based on a PID algorithm according to the brush hair pressure and the dust concentration of the cleaning brush, and closed-loop control is formed till the preset cleaning standard is met. According to the invention, self-adaptive control of the cleaning process of the tobacco photoelectric impurity removing machine can be automatically realized, and deep cleaning work can be carried out on a blind area.

Description

Technical Field

[0001] This invention relates to the field of automated control technology for tobacco equipment, and in particular to an automatic cleaning device, control method, and control system for a photoelectric cleaning machine. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Tobacco photoelectric dust collectors accumulate tobacco dust, fibrous impurities during continuous production, requiring cleaning after shutdown. Currently, manual cleaning is used, involving opening multiple cabinet doors, including the main cabinet door and internal cabinets. However, manual cleaning is inefficient and time-consuming. Furthermore, manual cleaning requires entering and penetrating deep into the equipment, posing safety hazards.

[0004] Current technologies include some simple cleaning devices added to mechanical structures, but these have low levels of intelligence in the control process and insufficient cleaning power, resulting in poor cleaning effects. Moreover, tobacco photoelectric cleaning machines have a relatively complex structure, and their cleaning methods have blind spots, such as gaps in the conveyor belt and gaps in the solenoid valves, which are difficult to clean thoroughly. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of this invention is to provide an automatic cleaning device, control method and control system for a photoelectric cleaning machine, which can automatically realize adaptive control of the cleaning process of the tobacco photoelectric cleaning machine and perform deep cleaning work for blind areas.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: The first aspect of this invention provides a control method for an automatic cleaning device of a photoelectric impurity remover, comprising the following steps: The surface of the photoelectric dust collector is cleaned using a cleaning brush and a dust collection system, and the brush bristle pressure and dust concentration are monitored in real time. Deep cleaning is achieved by using a cleaning brush combined with a jet nozzle to spray in sequence, and the pressure of the cleaning brush bristles and the dust concentration are monitored in real time. By using a PID algorithm to dynamically adjust cleaning parameters based on the brush bristle pressure and dust concentration, a closed-loop control is formed until the preset cleaning standard is reached.

[0007] Furthermore, before using the cleaning brush and vacuuming system to clean the surface of the photoelectric dust collector, the working status of the photoelectric dust collector and the status of the cleaning execution unit are detected. When the photoelectric dust collector is in a stopped state and the cleaning execution unit is in a normal state, a cleaning command is issued.

[0008] Furthermore, the normal state of the cleaning execution unit includes that the cleaning brush is installed, the vacuuming system is connected, and the air nozzle has been calibrated.

[0009] Furthermore, the specific steps for surface cleaning of the photoelectric dust collector using a cleaning brush and vacuum system are as follows: Clean by rotating the cleaning brush clockwise; The vacuum system is linked for cleaning, with the frequency converter controlling the vacuum fan to perform negative pressure vacuuming.

[0010] Furthermore, the specific steps for deep cleaning using a cleaning brush combined with the sequential spraying of the air nozzle are as follows: The jet nozzle performs sequential injection according to dynamic injection logic; Cleaning brushes clean by reciprocating motion.

[0011] Furthermore, the specific steps for the jet nozzle to perform sequential injection according to the dynamic injection logic are as follows: Group the components according to their nozzle positions and set state activation functions accordingly; Set the injection parameters and adaptively adjust the injection time; The jet nozzle is used for timing injection based on the current activation state and the state activation function.

[0012] Furthermore, the specific steps for dynamically adjusting cleaning parameters based on the PID algorithm according to the brush bristle pressure and dust concentration are as follows: Calculate the error between the current brush pressure value and the reference value, and then calculate the PID output. Torque adjustment is performed based on the PID output.

[0013] Furthermore, cleaning parameters include cleaning brush speed, jet cycle, and suction airflow.

[0014] A second aspect of the present invention provides a control system for an automatic cleaning device of a photoelectric impurity remover, comprising: The surface cleaning module is configured to use a cleaning brush and a vacuum fan to clean the surface of the photoelectric dust removal machine, and to monitor the brush bristle pressure and dust concentration in real time. The deep cleaning module is configured to perform deep cleaning by using a cleaning brush in conjunction with a jet nozzle in a sequential spray pattern, and to monitor the pressure of the cleaning brush bristles and the dust concentration in real time. The dynamic parameter adjustment module is configured to dynamically adjust the cleaning parameters based on the brush bristle pressure and dust concentration until the preset cleaning standard is reached. Specifically, it uses closed-loop control based on PID algorithm to perform multi-objective energy consumption optimization calculations based on the real-time parameters of the photoelectric dust collector, and dynamically adjusts the cleaning parameters based on the optimization results.

[0015] A third aspect of the present invention provides an automatic cleaning device for a photoelectric impurity remover, controlled by the control method described in the first aspect, comprising: The sensing unit is used to receive dust concentration signals and position signals in real time; The control unit is used to generate cleaning instructions based on dust concentration signals and location signals; The cleaning execution unit is used to perform cleaning tasks according to cleaning instructions. The drive unit is used to provide driving force for the cleaning execution unit.

[0016] The above one or more technical solutions have the following beneficial effects: This invention discloses an automatic cleaning device, control method, and control system for a photoelectric dust collector. The cleaning device is installed inside the photoelectric dust collector and its movement adapts to the dynamic structure of the machine. This invention designs cleaning strategies at different levels, from surface cleaning to deep cleaning. It also utilizes a PLC algorithm combined with dust sensors to form a closed-loop control, ensuring that cleaning meets standards and achieving cleaning of hard-to-reach areas and flexible blowing.

[0017] Key blind spots in photoelectric impurity removal machines include conveyor belt gaps, solenoid valve gaps, and corners of the lens area. The cleaning device of this invention uses a rotating cleaning brush combined with a position sensor to adjust its position in real time, preventing it from exceeding its limits. The telescopic nozzle's travel can extend into the blind spots, and combined with dynamic blowing logic, it prioritizes activating high-concentration dead zones. A negative pressure dust collection system, in conjunction with a centrifugal fan, recovers impurities in real time, preventing secondary deposition.

[0018] This invention dynamically adjusts the spraying logic based on dust sensor data: in the lens area (high dust accumulation zone), the sensor triggers priority spraying; combined with PID algorithm and position sensor, it achieves coordinated control, which not only dynamically sprays to improve cleaning efficiency, but also reduces energy consumption.

[0019] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of the automatic cleaning device control method for the photoelectric impurity remover in Embodiment 1 of the present invention; Figure 2This is a flowchart of the PID pressure control algorithm in Embodiment 1 of the present invention; Figure 3 This is a flowchart of the timing logic of the jet nozzle in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the photoelectric impurity removal machine in Embodiment 3 of the present invention; Figure 5 This is a schematic diagram of the operation of the photoelectric impurity removal machine cleaning device in Embodiment 3 of the present invention; Figure 6 This is a schematic diagram showing the position of the jet nozzle of the photoelectric impurity removal machine in Embodiment 3 of the present invention; Among them, 1. feeding device, 2. conveyor belt, 3. lens area, 4. conveyor belt end area, 5. cleaning device, 6. cleaning area, and 7. air nozzle. Detailed Implementation

[0022] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, 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.

[0023] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof. The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0024] Example 1: Embodiment 1 of the present invention provides a control method for an automatic cleaning device of a photoelectric impurity remover, such as... Figure 1 As shown, the system detects a stop signal, receives a PROFINET DI signal, and the speed sensor confirms the conveyor belt has stopped, entering the cleaning mode. The HMI displays an orange indicator light. The actuators are initialized (air jet nozzles and cleaning brushes are reset to zero). A cleaning command is received, triggered by the HMI button or an external button, and the PLC starts the cleaning program: Stage 1: Surface cleaning, cleaning brushes rotate clockwise at 40 rpm, and the vacuum fan operates at 800 m / s. 3 / h, real-time monitoring of brush bristle pressure and dust concentration. Stage 2: Deep cleaning, sequential jet spraying (0.5s cycle), cleaning brush reciprocating at 30rpm, continuous monitoring of dust concentration. Stage 3: Closed-loop feedback, dynamic adjustment of rotation speed, jet cycle, and airflow, achieving the target (concentration ≤5μg / m³). 3 Cleaning effect verification and final concentration detection: if the standard is met, reset; if the standard is not met, perform a second cleaning. System reset: shut down all actuators, perform reverse pulse cleaning of the filter, display the completion status on the HMI and record the log.

[0025] Specifically, the following steps are included: Step 1: System status detection and initialization.

[0026] In one specific implementation, before using a cleaning brush and a dust collection system to clean the surface of the photoelectric dust collector, the working status of the photoelectric dust collector and the status of the cleaning execution unit are detected. When the photoelectric dust collector is in a stopped state and the cleaning execution unit is in a normal state, a cleaning command is issued and an initialization operation is performed.

[0027] Step 1.1: Cleaning execution unit status detection.

[0028] A normal cleaning execution unit includes a cleaning brush installed, a vacuum system connected, and a jet nozzle calibrated.

[0029] Step 1.1.1: Install the cleaning brush.

[0030] Specifically, fix the brush roller bracket to the guide rails on both sides of the conveyor belt with a spacing of 150mm, and adjust the spring pressure to 10N. Set the servo motor parameters using Siemens TIA Portal software, with a maximum torque of 4.5Nm and an acceleration of 50rpm / s.

[0031] Step 1.1.2: Connect the vacuum system.

[0032] Specifically, the suction duct is connected to the EBMPapst fan inlet using clamps, and the tested negative pressure value is ≥2kPa. A differential pressure sensor (model: SMC PSE530R04) is installed in the dust collection chamber to monitor the filter clogging status.

[0033] Step 1.1.3: Nozzle calibration.

[0034] Specifically, the air pressure was adjusted to 0.6 MPa using an SMC digital pressure gauge (model: PF2A7100601) to test the spray coverage.

[0035] Step 1.2: Detection and triggering of the photoelectric cleaning machine's shutdown status.

[0036] Step 1.2.1: The PLC receives the shutdown signal (DI signal, 24VDC high level) from the main control system of the equipment via the PROFINET communication protocol. At the same time, the equipment speed sensor detects that the conveyor belt speed drops to 0 rpm and remains so for 10 minutes, confirming the shutdown status.

[0037] Step 1.2.2: Set the trigger conditions. When the stop signal and speed signal are both valid, the PLC switches to "cleaning mode" and the HMI interface displays an orange "cleaning" indicator light.

[0038] Step 1.3: Cleaning command input and initialization.

[0039] Step 1.3.1: Command input methods include: HMI touch screen: The operator clicks the "One-Click Cleaning" button, triggering a digital input signal (DI0 channel). External physical button: A spare button (model: Schneider XB2BA31C) is hardwired to the PLC's DI1 channel.

[0040] Step 1.3.2: The PLC sends initialization commands to each actuator: the cleaning brush motor returns to zero and resets to its initial position. The air nozzle retracts to a safe position, confirmed by feedback from the position sensor NBN818GM50E2V1. The vacuum cleaner fan pre-starts, running at low speed with an airflow of 200m³ / h. 3 / h.

[0041] Step 2: Use a cleaning brush and a vacuum system to clean the surface of the photoelectric dust removal machine, and monitor the brush bristle pressure and dust concentration in real time.

[0042] In one specific implementation, the termination condition for stage 1 surface cleaning is that the timer reaches 2 minutes, or the dust sensor (Honeywell HPMA115S0) detects a concentration of <20 μg / m3. Alternatively, if the dust sensor (Honeywell HPMA115S0) detects a concentration of <20 μg / m3, the deep cleaning stage is not performed.

[0043] Step 2.1: Clean by rotating the cleaning brush clockwise.

[0044] Specifically, in this embodiment, a Siemens SIMOTICS servo motor is used to rotate clockwise at 40 rpm, with the torque limited to 4.5 Nm (to prevent overload); a brush pressure sensor (TE Connectivity FX1901) monitors the contact force in real time (target value 10 N ± 1 N), and the motor output torque is dynamically adjusted through a PID algorithm.

[0045] Step 2.2: The vacuum system is linked for cleaning, in which the frequency converter controls the vacuum fan to perform negative pressure vacuuming.

[0046] Specifically, in this embodiment, the EBMPapst fan is controlled by a Danfoss VLT2800 frequency converter, and the air volume is gradually increased to 800m³ / h. 3 / h (frequency 35Hz); the negative pressure value of the suction port is monitored by a pressure sensor (SMC PSE530) and maintained at 2kPa±0.1kPa.

[0047] Step 3: Use a cleaning brush in conjunction with the air nozzle to perform a timed spray for deep cleaning, and monitor the pressure of the cleaning brush bristles and the dust concentration in real time.

[0048] In one specific implementation, such as Figure 3 As shown, initialization begins by closing all nozzles, followed by a state machine loop. The SMC nozzles operate according to a preset timing sequence. In this embodiment, the cycle is set to 0.5 seconds, the injection time to 100 milliseconds, and the air pressure stabilized at 0.6 MPa (adjusted via the Festo pressure reducing valve). The injection logic monitors the area in a cyclical manner, from the upper left of the inner wall to the lower right, then from the lower left of the conveyor belt to the right, covering all blind spots. If the concentration does not exceed the set threshold, the current area is skipped, and the nozzles are only triggered to spray in areas exceeding the set threshold. In some other implementations, the cyclical injection sequence can be customized. The specific steps for Phase 2 deep cleaning are as follows: Step 3.1: The jet nozzle performs sequential injection according to the dynamic injection logic.

[0049] Step 3.1.1: Group the components according to their nozzle positions and set the state activation function.

[0050] The dynamic jetting logic in this embodiment is based on the real-time dust concentration C(t) (measured by a Honeywell sensor), defining state variables and transition rules. Let the jet nozzle group be: 1 = upper left of the inner wall, 2 = lower right of the inner wall, 3 = lower left of the conveyor belt, 4 = lower right of the conveyor belt. State activation function: Nozzle activation is based on concentration-zoned thresholds. Let the threshold vector be... (unit ),in For the region The activation threshold (adjustable via HMI).

[0051] 。

[0052] in: For the jet nozzle The status of the solenoid valve (1=open, 0=closed). The dust concentration in region i (sensor zone monitoring). This is a priority function, set based on the concentration gradient. The one with the fastest concentration increase takes priority.

[0053] Step 3.1.2: Set the injection parameters and adaptively adjust the injection time.

[0054] In this embodiment, the injection parameters are set as follows: air pressure maintained at 0.6 MPa (adjusted via the Festo pressure reducing valve), and injection time adaptive. This embodiment adaptively sets the injection time and duration. Dynamic adjustment to avoid excessive gas consumption: 。

[0055] in, = 50 ms Base spray time; The proportional coefficient (adjusted via PLC) is a constraint. Limit to 50-200ms (to prevent overpressure).

[0056] Step 3.1.3: Perform timing injection of the jet nozzle based on the current activation state and the state activation function.

[0057] In this embodiment, the system uses a cyclic state machine, but activation is based on concentration rather than a fixed timing, and the state transition equation is set as follows: .

[0058] Where S(t) is the current activation state (integer 1-4). For PLC scan cycle, Returns the index of the region with the largest concentration deviation. If no region exceeds the limit ( ( ), maintain the current state or enter standby mode.

[0059] When average concentration The overall cleaning phase terminates when the (Phase 2 threshold) is reached. This represents the average dust concentration.

[0060] This embodiment dynamically activates the jet nozzles based on sensor data (e.g., prioritizing high-concentration areas), solving the problem of difficult deep cleaning of blind spots such as conveyor belt gaps. It also reduces compressed air usage (measured duty cycle decreased from 20% to 10-15%) by adaptively adjusting the spray time, thereby reducing energy consumption.

[0061] Step 3.2: The cleaning brush cleans by reciprocating motion.

[0062] In this embodiment, the servo motor switches to a forward rotation mode of 30 rpm (2 seconds) → reverse rotation mode of 30 rpm (2 seconds) to improve the cleaning effect in crevices. The position sensor provides real-time feedback on the brush roller position to prevent it from going out of bounds. The cleaning time is set after 2 minutes, or when the dust concentration is <15 μg / m³. 3termination.

[0063] Step 4: Utilize a PID algorithm to dynamically adjust cleaning parameters based on the brush bristle pressure and dust concentration to form a closed-loop control until the preset cleaning standard is achieved.

[0064] In one specific implementation, stage 3 is the dynamic adjustment stage. In this embodiment, the Honeywell sensor uploads data to the PLC every 10 seconds to monitor dust concentration. If the concentration is >10 μg / m³ 3 The cleaning brush speed is increased to 60 rpm (maximum torque limited to 5.0 Nm), the jet cycle is shortened to 0.3 s, the jet time is extended to 150 ms, and the suction air volume is increased to 1000 m³ / h (frequency 45 Hz). If the concentration is ≤10 μg / m³, the current parameters are maintained until the timing ends. After 5 minutes of timing, or after 3 consecutive tests, the concentration is ≤5 μg / m³. 3 termination.

[0065] Step 4.1: Calculate the error between the current brush pressure value and the reference value, and calculate the PID output.

[0066] like Figure 2 As shown, the PID algorithm is used to control the contact force of the cleaning brush bristles, ensuring it remains stable at the target value (10N±1N). This embodiment reads data from the pressure sensor (TE Connectivity FX1901) in real time, calculates the error, and uses a PID (Proportional-Integral-Derivative) controller to dynamically adjust the output torque of the servo motor (Siemens SIMOTICS S1FL6), forming a closed-loop control to prevent overload (torque limited to 4.5Nm) and improve cleaning efficiency. The algorithm is executed during the surface cleaning phase and updates once per cycle (response time ≤1s). The process can be summarized as follows: Start → Read sensor value → Calculate E → Calculate P, I, and D terms → Summate to obtain u(t) → Output to motor → Cycle monitoring until the error approaches 0, forming a closed-loop control to improve the stability and efficiency of the cleaning brush.

[0067] Specifically, PID output calculation involves proportional, integral, and derivative terms. Gain coefficients Kp, Ki, and Kd are determined through system debugging: the proportional coefficient Kp is initialized to 0.8 and dynamically adjusted based on the error: if |E|>2N, Kp increases to 1.2 to accelerate the response; if |E|<0.5N, Kp decreases to 0.5 to smooth control; the integral coefficient Ki = 0.1, with the integral limiter restricting the output range to prevent motor saturation; the derivative coefficient Kd = 0.05, used to dampen oscillations.

[0068] Step 4.1.1: Error calculation (E).

[0069] Ensure the brush pressure is stable at around 10N. An error E(t) > 0 indicates insufficient pressure (torque needs to be increased), while E(t) < 0 indicates excessive pressure (torque needs to be reduced).

[0070] .

[0071] Where E(t) is the error value at the current time t (unit: N). The pressure value is set to a fixed 10N. The actual pressure value is measured in real time by the TE Connectivity FX1901 sensor (pressure unit is N).

[0072] Step 4.1.2: PID output u(t).

[0073] The proportional term P (Kp×E) provides a fast response, the integral term I (Ki×integral) eliminates long-term deviations (such as sensor drift), and the derivative term D (Kd×derivative) reduces overshoot and oscillation. Overall, it achieves "dynamic adjustment" so that the pressure error approaches 0 (target: ±1N).

[0074] .

[0075] Where u(t) is the output of the PID controller (unit: Nm), which is directly used to adjust the torque of the servo motor; Kp is the proportional gain, which controls the response strength to the current error; and Ki is the integral gain (unit: s). -1 To eliminate steady-state error, Kd is the differential gain (unit: s), suppressing system oscillations. The sampling time interval is in seconds (s). The sensor response time is ≤1 second. , This is a discrete approximation of the integral term. It is a discrete approximation (backward difference) of the differential term.

[0076] Step 4.2: Adjust the torque based on the PID output.

[0077] The cleaning parameters in this embodiment include the cleaning brush rotation speed, jet cycle, and suction airflow. The cleaning brush rotation speed is determined by torque.

[0078] Specifically, the PID output limit must first be within a safe range to ensure that the system operates within a safe range and avoid mechanical damage (such as triggering an emergency stop when the brush pressure is >20N).

[0079] .

[0080] in, To minimize torque and prevent reverse movement, The adjusted output, representing the maximum torque, is sent to the Siemens SIMOTICS servo motor to drive the brush roller to rotate. In this embodiment, all parameter settings are illustrative; values ​​can be customized according to actual conditions.

[0081] In practical applications, during the surface cleaning stage (stage 1), the algorithm is executed once every Δt seconds (Δt = 0.1s to match the sensor response).

[0082] The PID control method described above in this embodiment can reduce energy consumption. Specifically: Energy consumption (unit: kWh) is defined as the integral of motor power P(t) over time. Instantaneous power P(t) is related to torque output u(t), and combined with motor efficiency η (based on typical values ​​for servo motors, taking η=0.9), the formula is as follows: .

[0083] in, For PID output torque, Motor angular velocity (unit: rad / s), speed conversion .

[0084] 2) Total Energy Equation: .

[0085] in, Start time; End time; The sampling interval is set to match the sensor response time, and is set to 0.1s. After optimization, the algorithm limits the torque output ( Within 0-4.5 Nm) and with adaptive Kp, power peak is reduced.

[0086] Based on PID dynamic gain adjustment, energy consumption optimization can reduce torque fluctuations: when the error is small (|E|<0.5N), Kp is reduced to 0.5 to avoid high-frequency torque adjustment, thereby reducing average power.

[0087] Formula for energy consumption reduction rate: .

[0088] in, For the energy consumption of a fixed-gain PID controller, To optimize energy consumption.

[0089] Experiments have shown that, before optimization (fixed gain PID): assuming a fixed gain... = 1.0, large torque fluctuations (high variance) result in high average power. For example, during the surface cleaning phase (2 minutes), the average power is... (Based on torque fluctuation estimation), energy consumption is: .

[0090] Optimized (Adaptive Gain PID): Dynamic Reduce torque fluctuations, average power reduced to Energy consumption is: .

[0091] Energy consumption reduction rate before and after: 。

[0092] In this embodiment, the sensor uploads concentration data (range 0-1000 μg / m³) every 10 seconds during this stage. 3 Resolution 1μg / m 3 The PLC compares the concentration with the threshold and adjusts the cleaning brush speed, jet cycle, and suction airflow. The concentration is set to ≤5 μg / m³ or the timing ends.

[0093] Step 5: Verify the cleaning effect and reset the system.

[0094] Step 5.1: Cleaning effect verification process. Step 5.1.1: PLC starts final dust concentration detection: lasts for 30 seconds, and average value is taken.

[0095] Step 5.1.2: If the concentration is ≤5μg / m³: the cleaning standard is met; otherwise, the secondary cleaning process is triggered, and the dynamic adjustment steps in stage 3 are repeated.

[0096] Step 5.2: System reset. Step 5.2.1: Shut down all actuators. The cleaning brush motor stops and locks; the vacuum fan speed is reduced to 0, and the nozzle retracts. Step 5.2.2: Filter self-cleaning. The dust collection chamber filter starts reverse pulse airflow (0.3MPa, pulse width 0.1s, interval 0.5s, for a total of 5 times); the HMI displays green "cleaning complete" and records the log (cleaning time, energy consumption, dust peak).

[0097] Step 5.2.3: Feedback Loop. In stage 3, dust concentration data is fed back to the PLC in real time, forming a closed-loop control. The algorithm forms a feedback loop based on real-time dust concentration (Honeywell HPMA115S0 sensor).

[0098] In one specific implementation, this embodiment also features safety protection and log recording functions. When the brush pressure exceeds the limit (>20N) or the motor is overloaded, an emergency stop and alarm are immediately triggered. Data such as cleaning time, energy consumption, and peak dust levels are recorded and stored on the PLC's SD card, with USB export supported. The concentration threshold in this embodiment is 10μg / m³. 3 and 5μg / m 3 Based on tobacco industry standards (safe limits for residual impurities), dynamic calibration is performed using a PLC algorithm.

[0099] In addition, this embodiment integrates historical data learning (log recording). If the concentration decreases slowly after multiple cleanings, the algorithm automatically reduces the initial airflow to save energy. Utilizing dust sensors and position sensors in conjunction, it ensures synchronized movement of the air nozzles and cleaning brushes (prioritizing activation of blind spots during high concentrations). This algorithm reduces energy consumption and displays progress in real-time via an HMI (Siemens KTP700 touchscreen).

[0100] Example 2: Embodiment 2 of the present invention provides a control system for an automatic cleaning device of a photoelectric impurity remover, comprising: The surface cleaning module is configured to use a cleaning brush and a vacuum fan to clean the surface of the photoelectric dust removal machine, and to monitor the brush bristle pressure and dust concentration in real time. The deep cleaning module is configured to perform deep cleaning by using a cleaning brush in conjunction with a jet nozzle in a sequential spray pattern, and to monitor the pressure of the cleaning brush bristles and the dust concentration in real time. The dynamic parameter adjustment module is configured to dynamically adjust the cleaning parameters based on the brush bristle pressure and dust concentration until the preset cleaning standard is reached. Specifically, it uses closed-loop control based on PID algorithm to perform multi-objective energy consumption optimization calculations based on the real-time parameters of the photoelectric dust collector, and dynamically adjusts the cleaning parameters based on the optimization results.

[0101] Example 3: Embodiment 3 of the present invention provides an automatic cleaning device for a photoelectric impurity removal machine, such as... Figure 4 , Figure 5 and Figure 6 As shown, the photoelectric cleaning machine is controlled using the control method described in Embodiment 1. It includes a feeding device 1, a conveyor belt 2, and a cleaning device 5, and is provided with a lens area 3, a conveyor belt end area 4, and a cleaning area 6.

[0102] A rotating shaft is mounted on a fixed bracket inside the photoelectric dust collector. The bracket extends from the rotating shaft and is connected to a cleaning device. The rotating shaft drives the cleaning device to perform the cleaning process. In this embodiment, the cleaning device is highly flexible and can be freely adjusted. The structure of the photoelectric dust collector is existing in the art and will not be described in detail here. Those skilled in the art can set the positions of the rotating shaft and the bracket according to actual conditions, as long as they can cover the cleaning area as much as possible.

[0103] The cleaning device includes: The sensing unit receives dust concentration and position signals in real time. It includes a dust sensor and a position sensor. The dust sensor is a Honeywell HPMA115S0XXX laser particulate sensor with a measurement range of 0~1000 μg / m³. 3 Resolution 1μg / m 3 The response time is ≤1s. The position sensor is a Pepperl+Fuchs NBN818GM50E2V1 Hall sensor with a detection distance of 8mm and outputs a PNP signal. In this embodiment, the position sensor is used to monitor the position traversed by the sensing unit, preventing duplicate monitoring or the occurrence of undetected positions.

[0104] The control unit generates cleaning commands based on dust concentration and position signals. It includes a PLC controller and an HMI (Human Machine Interface). The PLC controller is a Siemens SIMATIC S71200, model 6ES72141HG400XB0, with an integrated PROFINET interface. The HMI is a Siemens KTP700 Basic 7-inch touchscreen, model 6AV21232GB030AX0, supporting cleaning progress display and fault alarms.

[0105] The cleaning execution unit performs cleaning tasks according to cleaning instructions. It includes a cleaning brush, a negative pressure vacuum system, and air nozzles. The cleaning brush is a rotatable, dual-axis stainless steel brush roller (80mm diameter), covered with anti-static nylon bristles, 60mm in length, and with a Shore A hardness of 85. The negative pressure vacuum system includes a 50mm inner diameter suction duct with a 150mm spacing between suction ports and a centrifugal fan. The centrifugal fan is an EBMPapst RadiCal centrifugal fan with a power of 1.5kW and an airflow of 0~1200m³ / h. 3 / h, noise ≤65dB. Nozzle 7 is a telescopic nozzle, including a nozzle assembly and a solenoid valve. The nozzle assembly is a KRIYING STP-150 series, with a stroke of 50mm, a nozzle diameter of 5mm, and a pressure resistance of 1.0Mpa. The solenoid valve is a Festo MEH5 / 21 / 8PB one-way solenoid valve, with a response time ≤15ms and a working air pressure of 0.4~0.8Mpa.

[0106] The drive unit is used to provide driving force for the cleaning execution unit.

[0107] The cleaning brush is driven by a Siemens SINAMICS V90 servo drive, model: 6SL32105FE100UF0, which is matched with the SIMOTICS motor and supports EtherCAT communication.

[0108] The negative pressure vacuum system uses a Danfoss VLT HVAC Drive inverter, model: VLT2800, with a power of 1.5kW, to achieve stepless airflow adjustment.

[0109] The overall efficiency comparison is shown in Table 1.

[0110] Table 1. Comparison of Cleaning Equipment and Manual Cleaning

[0111] The steps and methods involved in Examples 2 and 3 above correspond to those in Example 1. For specific implementation details, please refer to the relevant description section of Example 1.

[0112] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application. In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data processing device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, an optical medium, or a semiconductor medium, etc. The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A control method of an automatic cleaning device of a photoelectric impurity removal machine, characterized by, The method comprises the following steps: The surface of the photoelectric impurity removal machine is cleaned by using a cleaning brush and a dust suction system, and the brush hair pressure of the cleaning brush and the dust concentration are monitored in real time; Deep cleaning is performed by using the timing injection of the cleaning brush combined with the air jet nozzle, and the brush hair pressure of the cleaning brush and the dust concentration are monitored in real time; The cleaning parameters are dynamically adjusted according to the brush hair pressure of the cleaning brush and the dust concentration based on a PID algorithm, forming a closed-loop control until the preset cleaning standard is reached.

2. The control method of the automatic cleaning device of the photoelectric impurity removal machine according to claim 1, characterized in that, Before the surface of the photoelectric impurity removal machine is cleaned by using the cleaning brush and the dust suction system, the working state of the photoelectric impurity removal machine and the state of the cleaning execution unit are detected, and a cleaning instruction is issued when the photoelectric impurity removal machine is in a stopped state and the cleaning execution unit is in a normal state.

3. The control method of the automatic cleaning device of the photoelectric impurity removing machine according to claim 2, characterized in that, The normal state of the cleaning execution unit includes that the cleaning brush has been installed, the dust suction system has been connected, and the air jet nozzle has been calibrated.

4. The control method of the automatic cleaning device of the photoelectric impurity removing machine according to claim 1, characterized in that, The specific steps of cleaning the surface of the photoelectric impurity removal machine by using the cleaning brush and the dust suction system are: The cleaning brush rotates clockwise to clean; The dust suction system is linked to clean, wherein the frequency converter controls the dust suction fan to perform negative pressure dust suction.

5. The control method of the automatic cleaning device of the photoelectric impurity removing machine according to claim 1, characterized in that, The specific steps of deep cleaning by using the timing injection of the cleaning brush combined with the air jet nozzle are: The air jet nozzle performs timing injection according to a dynamic blowing logic; The cleaning brush cleans through reciprocating motion.

6. The control method of the automatic cleaning device of the photoelectric impurity removing machine according to claim 5, characterized in that, The specific steps of the air jet nozzle performing timing injection according to a dynamic blowing logic are: Grouping is performed according to the position of the air jet nozzle and a state activation function is set; Injection parameters are set and injection time is adjusted adaptively; Timing injection of the air jet nozzle is performed based on the current activated state and the state activation function.

7. The control method of the automatic cleaning device of the photoelectric impurity removing machine according to claim 1, characterized in that, The specific steps of dynamically adjusting the cleaning parameters according to the brush hair pressure of the cleaning brush and the dust concentration based on a PID algorithm are: The error between the current brush hair pressure value and the reference value is calculated, and the PID output is calculated; Torque adjustment is performed according to the PID output.

8. The control method of the automatic cleaning device of the photoelectric impurity removing machine according to claim 1, characterized in that, The cleaning parameters include the cleaning brush speed, the air jet cycle, and the dust suction air volume.

9. A control system for an automatic cleaning device of a photoelectric particle cleaner, characterized in that It comprises: A surface cleaning module configured to clean the surface of the photoelectric impurity removal machine by using a cleaning brush and a dust suction fan, and to monitor the brush hair pressure of the cleaning brush and the dust concentration in real time; A deep cleaning module configured to perform deep cleaning by using the timing injection of the cleaning brush combined with the air jet nozzle, and to monitor the brush hair pressure of the cleaning brush and the dust concentration in real time; A dynamic parameter adjustment module configured to dynamically adjust the cleaning parameters according to the brush hair pressure of the cleaning brush and the dust concentration until the preset cleaning standard is reached, wherein a closed-loop control based on a PID algorithm is used to perform multi-objective energy consumption optimization calculation according to the real-time parameters of the photoelectric impurity removal machine, and the cleaning parameters are dynamically adjusted according to the optimization results.

10. An automatic cleaning device of a photoelectric impurity removal machine, controlled by the control method according to any one of claims 1-8, characterized in that, It comprises: A sensing unit for receiving dust concentration signals and position signals in real time; A control unit for generating a cleaning instruction according to the dust concentration signals and the position signals; A cleaning execution unit for performing cleaning work according to the cleaning instruction; A driving unit for providing driving force for the cleaning execution unit.

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