Automatic control system and method for spun yarn blowing and suction fan and medium

Abstract

The invention relates to the technical field of spinning frame auxiliary equipment, and discloses an automatic control system and method for a spun yarn blowing and suction fan and a medium, and the system comprises a multi-mode sensing unit, an execution and interaction unit and a central control unit. The central control unit is configured to continuously analyze air duct state data during the operation period of the air blowing and suction device, capture real-time position data when abnormality is detected, bind an abnormal event with the position time and space and store the abnormal event and the position time and space into a health distribution diagram; when a doffing preparation signal is responded, the health distribution diagram is inquired, and if a space fault record exists, a motion executing mechanism is instructed to drive the air blowing and sucking device to navigate to a fault physical position; and if the space fault record does not exist, the air blowing and sucking device is driven to move to a preset conventional doffing parking point. According to the method, the specific positions of space faults such as air duct blockage can be accurately positioned in the operation of the air blowing and suction device, and automatic navigation to fault points is carried out for active intervention and prompt in a doffing process gap.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spinning machine auxiliary equipment, in particular to a spinning blowing and suction fan automatic control system, method and medium. BACKGROUND

[0002] The spinning machine is a key equipment in spinning production, and a large amount of lint and dust will be generated during its operation. In order to protect the spinning quality and the workshop environment, the spinning machine is usually equipped with a blowing and suction device. The device reciprocates along the machine rail, and continuously cleans the key parts of the machine through blowing and suction units. In the existing control scheme, the start-stop, reciprocating walking and intermittent working mode of the blowing and suction device are usually composed of an electrical circuit composed of traditional time relays and contactors.

[0003] When the suction port or air duct of the blowing and suction device is blocked due to accumulation of lint, the cleaning efficiency of the system will be significantly reduced. The traditional electrical control circuit lacks real-time monitoring capability of the fluid state of the air duct, and therefore cannot perceive the occurrence of such space faults. Even if the system is tripped and stopped due to secondary effects such as fan overload, the control system cannot know the specific physical location of the blockage. The operator can only manually inspect the machine rail of tens of meters long after the equipment is stopped, and the fault location is difficult, the troubleshooting efficiency is low, and the cleaning blind area exists for a long time.

[0004] In addition, when the spinning machine performs a doffing process, the blowing and suction device must retreat and accurately stop at the preset regular doffing stop point to avoid interference with the doffing mechanism. The existing technology usually uses proximity switches in combination with time relays to achieve this function. This open-loop time delay control-based stopping method has positioning accuracy limited by factors such as inertia of the walking motor and changes in rail friction, and it is difficult to ensure accurate stopping at the target position every time, and there is a position error, which may affect the smooth performance of the doffing process. SUMMARY

[0005] The purpose of the present application is to provide a spinning blowing and suction fan automatic control system, method and medium, which solves the problems of lack of accurate positioning capability for air duct blockage and insufficient doffing stopping control accuracy in the prior art.

[0006] To achieve the above purpose, the present application is implemented by the following technical solutions: The first aspect provides a spinning blowing and suction fan automatic control system. The system includes a central control unit, a multi-modal sensing unit and an execution and interaction unit.

[0007] The central control unit is electrically connected with the multi-modal sensing unit and the execution and interaction unit respectively.

[0008] The multi-modal perception unit is configured to acquire real-time state information of the spinning frame. The information includes a preparation doffing signal acquired by a working condition perception module, air duct state data acquired by a system health perception module, and real-time position data of the blowing and suction device acquired by a precision positioning module.

[0009] The execution and interaction unit includes a motion execution mechanism for driving the blowing and suction device to move.

[0010] The central control unit is configured to execute the following control logic: During operation of the blowing and suction device, the air duct state data is continuously analyzed. When it is detected that the air duct state data indicates an abnormality, the current real-time position data is immediately captured, the abnormal event is spatiotemporally bound with the real-time position data, and the spatiotemporal bound abnormal event is stored as a spatial fault record in a health distribution map.

[0011] In response to the preparation doffing signal received by the working condition perception module, the central control unit queries the health distribution map to determine whether there is the spatial fault record.

[0012] If the spatial fault record exists in the health distribution map, the motion execution mechanism is instructed to drive the blowing and suction device to navigate and stop at the fault physical position corresponding to the spatial fault record.

[0013] If the spatial fault record does not exist in the health distribution map, the motion execution mechanism is instructed to drive the blowing and suction device to move to a preset regular doffing parking point.

[0014] In an embodiment, the system health perception module includes a differential pressure sensor or a thermal type air speed sensor installed in the air duct. The central control unit detects whether the air duct state data indicates an abnormality by comparing the air duct state data with a preset health threshold.

[0015] In an embodiment, the precision positioning module includes a high-resolution absolute value encoder or a magnetic grating ruler coupled with the motion execution mechanism to provide the real-time position data.

[0016] In an embodiment, the working condition perception module includes a process parameter interface connected with a main control PLC of the spinning frame, and the central control unit receives the preparation doffing signal via the process parameter interface.

[0017] In an embodiment, the execution and interaction unit further includes a human-computer interaction module. The central control unit, while instructing the motion execution mechanism to stop at the fault physical position, is further configured to instruct the human-computer interaction module to issue an audible and visual alarm or display position information of the fault physical position.

[0018] In one embodiment, the central control unit, when instructing the motion execution mechanism to move to the preset regular doffing parking point, is configured to perform closed-loop position control using the real-time position data fed back by the precision positioning module to achieve high-precision positioning stop.

[0019] In one embodiment, the multi-modal perception unit further comprises a cleaning demand perception module for providing fly / dust concentration data. The central control unit is further configured to diagnose process abnormalities based on comparison of the fly / dust concentration data with a dynamic threshold, and store the process abnormalities in the health distribution map after spatiotemporal binding with the real-time position data.

[0020] In one embodiment, the working condition perception module is further used to provide process parameters. The central control unit is further configured to perform dynamic intermittent operation control, which calculates blower operation time and blower stop time through a decision model based on the fly / dust concentration data and the process parameters, and instructs the blowing and suction blower in the motion execution mechanism to execute.

[0021] The second aspect of the present application provides an automatic control method for a blowing and suction blower for spinning, which is applied to the automatic control system for a blowing and suction blower for spinning as described above, and comprises the following steps: S100: Real-time acquisition of states: real-time acquisition of spinning machine working condition signals, air duct state data, and real-time position data of the blowing and suction device; S200: Diagnosis and spatial positioning: during operation of the blowing and suction device, the air duct state data is continuously analyzed, when an abnormality is detected, the current real-time position data is immediately captured, the abnormal event is spatiotemporally bound with the real-time position data, and stored in the health distribution map as a spatial fault record; S300: Receiving a doffing trigger signal: receiving a doffing preparation signal in the spinning machine working condition signals; S400: Starting intelligent response decision: in response to the doffing preparation signal, immediately querying the health distribution map to determine whether there is a spatial fault record that has not been processed; S500: Performing response actions: if there is a spatial fault record in the health distribution map, driving the blowing and suction device to navigate during the doffing gap and stop at the fault physical position corresponding to the spatial fault record; if there is no spatial fault record in the health distribution map, driving the blowing and suction device to move to a preset regular doffing parking point.

[0022] The third aspect of the present application provides a storage medium, which stores a computer program, and the computer program is executed by a processor to realize the functions of the automatic control system of the blowing and suction fan of the fine yarn.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: 1. The present application realizes the spatiotemporal binding of faults and physical locations by continuously analyzing air duct state data during the operation of the blowing and suction fan device and capturing real-time location data immediately when an anomaly is detected. This mechanism enables the system to construct a health distribution map containing spatial dimensions, thereby accurately locating the specific occurrence location of spatial faults such as air duct blockage, providing a basis for subsequent accurate maintenance, and overcoming the problem of the inability of traditional systems to locate fault points.

[0024] 2. The present application uses the preparation doffing signal issued by the main control system of the spinning frame as the trigger condition for intelligent decision-making. When the system queries the health distribution map and confirms the existence of spatial fault records, it can utilize the gap time of the doffing process to instruct the blowing and suction fan device to automatically navigate to the fault physical location and prompt the operator. This design realizes active intervention and immediate correction of faults, avoids the decline in cleaning effect or unplanned downtime caused by fault accumulation, and ensures the stable operation of the system.

[0025] 3. When there are no fault records in the conventional process, i.e., the health distribution map, the present application uses real-time location data provided by the precise positioning module to perform doffing stop of the blowing and suction fan device. This method replaces the traditional time delay relay control with closed-loop position control, realizes high-precision positioning stop at the conventional doffing stop point, and ensures the stable connection of the blowing and suction fan device and the doffing process. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 is a system framework diagram of the present application; Figure 2 is a method flowchart of the present application; Figure 3 is a computer equipment structure schematic diagram of the present application.

[0027] Among them, 100, central control unit; 200, multi-modal perception unit; 210, working condition perception module; 220, cleaning demand perception module; 230, system health perception module; 240, precise positioning module; 300, execution and interaction unit; 310, motion execution mechanism; 320, human-computer interaction module; 40, computer equipment; 41, processor; 42, memory; 43, storage medium. DETAILED DESCRIPTION

[0028] Referring to the accompanying Figure 1 , Figure 1is a schematic diagram of the architecture of the fine spinning blowing and suction air intelligent control system according to the embodiment of the present application. The present application provides a fine spinning blowing and suction air fan automatic control system, comprising: a central control unit 100 for aggregating data, running algorithms and issuing control instructions; a multi-modal perception unit 200 electrically connected with the central control unit 100 for collecting various real-time state information of the spinning frame; an execution and interaction unit 300 electrically connected with the central control unit 100 for receiving and executing control instructions and providing state feedback.

[0029] In the embodiment, the multi-modal perception unit 200 comprises: a working condition perception module 210 for acquiring the running working condition signals of the spinning frame, including an upper proximity switch and a lower proximity switch for triggering the doffing process, and a process parameter interface for acquiring the process parameters of the main control PLC of the spinning frame; a cleaning demand perception module 220, such as an optical fly / dust concentration sensor installed in the key area of the spinning frame, for real-time monitoring of the local particulate matter concentration; a system health perception module 230, such as a differential pressure sensor or a thermal type air speed sensor installed in the air duct, for monitoring the air volume or air pressure state of the blowing and suction air system; a precision positioning module 240, such as an encoder or a magnetic scale ruler following the blowing and suction air device, for acquiring the real-time physical position of the blowing and suction air device.

[0030] In the embodiment, the execution and interaction unit 300 comprises: a motion execution mechanism 310 including the blowing and suction air fan (and its associated frequency converter or contactor) and a walking motor for driving the blowing and suction air device to reciprocate; a human-computer interaction module 320 including indicator lights, buzzers or display screens for state display or abnormal alarm.

[0031] The specific implementation modes and cooperative work processes of each module in the embodiment of the present application will be described in detail below.

[0032] The central control unit 100 is the core of the control system and can be implemented by an industrial programmable logic controller (PLC) or an embedded microcontroller (MCU). The control algorithm described in the present application is run inside the unit to replace the hardware combination of traditional relays and time relays with software logic.

[0033] In its work process, the central control unit 100 specifically performs the following steps: S10: After receiving the start signal from the working condition perception module 210, the central control unit 100 executes the delay start logic. The central control unit 100 starts the internal programmable timer and waits for a preset delay time Tdelay_start After completion, the instruction motion actuator 310 starts the blowing and suction fan. This delay logic replaces the hardware implementation of a traditional time relay (such as KT1).

[0034] S20: The central control unit 100 continuously receives real-time data from the multimodal sensing unit 200 and executes dynamic intermittent operation control. The central control unit 100 internally runs a fuzzy adaptive decision model f. adapt This model replaces the fixed-cycle mode of traditional dual-time relays. It uses the average fly ash / dust concentration data provided by the cleaning demand sensing module 220 during the k-th acquisition cycle. The current process parameters S provided by the operating condition sensing module 210 proc_k As input, the model dynamically calculates and outputs the wind turbine operating time T for the (k+1)th cycle based on these inputs. on and stopping time T off And instruct the motion actuator 310 to execute. Its adaptation principle is that when a high concentration of fly ash / dust is detected, or when the spinning machine is operating at high speed or under high dust generation conditions, the model will correspondingly increase the fan running time T. on Or shorten the stopping time T off To enhance cleaning effectiveness; conversely, under low dust generation conditions, the Tday time is extended. off Or shorten T on In order to optimize energy consumption.

[0035] The output of this decision model can be expressed as: in: T on This refers to the operating time of the wind turbine; T off This refers to the fan stop time; k is the sequence number of the current running cycle; f adapt The specific implementation of the fuzzy adaptive decision model, including the formulation of fuzzy rules and the defuzzification method, is well known to those skilled in the art and will not be elaborated here. The average fly ash / dust concentration in the k-th period; S proc_k For the process parameters of the k-th cycle, such as machine speed or yarn count.

[0036] S300: The central control unit 100 performs real-time anomaly diagnosis in parallel. This unit comprehensively analyzes data from the multimodal sensing unit 200 to perform process anomaly diagnosis and spatial fault diagnosis, and constructs a health distribution map M. anomaly .

[0037] S310: During process anomaly diagnosis, the central control unit 100 will transmit real-time concentration data D from the cleaning demand sensing module 220. dust (t) and based on the current process parameters S proc The dynamic threshold is compared. When the instantaneous value of the concentration or its rate of change exceeds the threshold, a process abnormality is determined. This diagnostic logic uses a process abnormality trigger (Flag). proc Implementation. Among them, the dynamic threshold Th level (S proc ) and Th rate (S proc It will be based on the current process parameters S of the spinning machine. proc Adjustments should be made. For example, when the spinning machine is operating at high speed or spinning high-count yarn, where dust generation is normally high, Th level (S proc ) and Th rate (S proc The threshold will be increased accordingly to avoid false alarms; while in low-dust-generating conditions such as low-speed spinning or spinning low-count yarn, the threshold will be decreased to improve the sensitivity of anomaly detection.

[0038] in: Flag proc (t) represents the state of the process exception trigger, where 1 indicates triggering; D dust (t) represents the real-time concentration of fly ash / dust at time t; Th level (S proc () is based on the current process parameter S proc Concentration level threshold; The rate of change of concentration over time; Th rate (S proc () is based on the current process parameter S proc The concentration change rate threshold.

[0039] S320: During space fault diagnosis, this unit will receive air duct status data P from the system health sensing module 230. flow (t) and the preset health threshold Th flow_min Comparison. When P flow (t) is lower than Th flow_min At that time, it was determined to be a spatial fault. Simultaneously, the unit compared the time of the fault occurrence with the real-time position data L from the precision positioning module 240. pos (t) is bound to achieve spatial location of the fault.

[0040] S330: The central control unit 100 stores the abnormal events diagnosed in steps S310 and S320 into the health profile M in real time in a data structure containing the type of abnormality, location, severity level, and time stamp anomaly .

[0041] S400: When the doffing process is triggered, the central control unit 100 executes a dynamic doffing intelligent response decision. The unit first queries the health profile M anomaly for its status. If M anomaly is empty, a high-precision pinpoint shutdown process is executed, which no longer relies on the time delay mode of traditional time relays (such as KT2), but uses the position feedback of the precision positioning module 240 to accurately stop the blowing and suction device at the preset position through a closed-loop control algorithm (such as proportional-integral-derivative PID control). If M anomaly contains abnormal records, the central control unit 100 instructs the motion execution mechanism 310 to navigate to the fault point to execute the preset correction action according to the highest priority abnormal event in the record, and provides an abnormal prompt through the human-computer interaction module 320. The determination of the highest priority abnormal event can be based on a comprehensive evaluation of factors such as the severity of the abnormality (Severity), the type of abnormality (Type, for example, process abnormalities are usually higher than spatial faults), or the duration of the abnormality. The preset correction action includes but is not limited to performing a stationary strong cleaning or a local reciprocating cleaning at the fault point, etc. This decision mechanism realizes intelligent intervention and proactive maintenance during the doffing process.

[0042] The multi-modal perception unit 200 is responsible for collecting various real-time data required for system operation, and its modules are electrically connected to the central control unit 100. The multi-modal perception unit 200 includes an operating condition perception module 210, a cleaning demand perception module 220, a system health perception module 230, and a precision positioning module 240.

[0043] The operating condition perception module 210 includes various sensors and interfaces for obtaining fine spinning machine operating condition signals.

[0044] The operating condition perception module 210 includes an upper proximity switch and a lower proximity switch, which are inductive or photoelectric sensors installed at specific positions of the reciprocating movement path of the blowing and suction device on the fine spinning machine track. The upper proximity switch is mainly used to indicate that the blowing and suction device has reached the preset pre-doffing stop point, and its output signal Sig pre_stop is transmitted to the central control unit 100 as a trigger condition for the high-precision shutdown process in the doffing process. The lower proximity switch is used to indicate that the blowing and suction device has reached the doffing start position, and its output signal Sig doff_startThe transmission to the central control unit 100 as a trigger signal for the start of the doffing process, and start the intelligent response decision process. The setting of the two proximity switches can accurately feedback the state of the blowing and suction device at the key position point, guarantee the timing control and positioning accuracy of the system in the doffing process.

[0045] In addition, the working condition perception module 210 also contains the process parameter interface with the main control PLC of the spinning frame. The interface exchanges data with the main control system of the spinning frame through a standard industrial communication protocol (such as Modbus, Profinet or EtherCAT, etc., the specific implementation belongs to the prior art, and will not be repeated here). Through the interface, the central control unit 100 can obtain the current process parameters S proc (t) of the spinning frame in real time. These parameters include but are not limited to spinning varieties, spindle speeds, draft ratios, spindle numbers, and current spinning frame operating states (such as normal operation, parking, fault, etc.). The central control unit 100 uses these process parameters S proc (t) as the input of the dynamic intermittent operation control model f adapt , and the adjustment basis of the dynamic threshold Th level (S proc ) and Th rate (S proc ) in process abnormality diagnosis, so that the cleaning strategy and fault diagnosis mechanism of the blowing and suction system can accurately match the actual working condition of the spinning frame, avoiding the limitations of fixed parameter control.

[0046] The cleaning demand perception module 220 adopts a flying fluff / dust concentration sensor based on the principle of optical scattering. The sensor usually contains a light source (such as a laser diode or an LED) and a light receiver (such as a photodiode). When flying fluff or dust particles in the air pass through the detection area of the sensor, they will scatter the light emitted by the light source. The light receiver captures these scattered lights and converts their intensity into an electrical signal. The intensity of the scattered light is positively correlated with the number and size (i.e. concentration) of particulate matter in the air, and through calibration, the concentration of flying fluff / dust in the air can be quantitatively measured.

[0047] The sensor is installed near the air inlet of the blowing and suction device or in the key spinning area of the spinning frame where flying fluff and dust are easily accumulated. The purpose of selecting these positions is to ensure that the sensor can accurately reflect the actual dust production and cleaning demand of the spinning frame in a specific area in real time. The sensor outputs an analog voltage signal proportional to the particulate matter concentration or a processed digital signal D dust (t), which is periodically transmitted to the central control unit 100.

[0048] The central control unit 100 will D dust(t) Data as the core input to perform dynamic intermittent operation control. Specifically, when D dust (t) is high, it indicates that the area has a faster accumulation of lint or dust, and the demand for cleaning increases. The central control unit 100 will adjust the operation cycle of the blowing and suction fan, and increase the strength or frequency of blowing or suction. Conversely, when D dust (t) is low, the demand for cleaning decreases accordingly, and the system optimizes the fan operation mode to save energy. In addition, D dust (t) data is also used for real-time anomaly diagnosis. For example, an abnormal increase or rapid change in D dust (t) may be due to process anomalies such as broken yarn or winding, resulting in a sharp increase in local dust production, providing important evidence for the central control unit 100 to judge process failure.

[0049] The system health perception module 230 is mainly used to monitor the fluid mechanics state of the blowing and suction system in real time to provide quantitative data of the air duct health condition. This module uses a differential pressure sensor or a thermal type air speed sensor as the core sensing element. The sensor is fixedly installed at the key nodes of the main air duct inside the blowing and suction device, the fan outlet or the suction port. These locations are sensitive areas of air flow changes and can directly reflect the operating resistance and flow characteristics of the entire pneumatic system.

[0050] When a thermal type air speed sensor is used, it works on the principle of heat dissipation. The sensor probe contains a heated element inside, when the airflow flows through the probe, it carries away heat, the faster the airflow speed, the faster the heat dissipation. The sensor converts the change in current required to maintain the element temperature into a corresponding wind speed electrical signal. If a differential pressure sensor is used, it measures the pressure difference (static pressure or dynamic pressure) between the inside of the air duct and the outside atmosphere, and calculates the current ventilation or wind resistance state according to the Bernoulli equation principle.

[0051] The sensor converts the physical quantity collected into a standardized electrical signal and undergoes analog-to-digital conversion processing to generate air duct state data P flow (t). This data is sent in real time to the central control unit 100 through signal transmission lines. P flow (t) is a continuous variable that changes over time, directly reflecting the work efficiency of the blowing and suction device at the current time.

[0052] The data output of the system health perception module 230 provides a physical basis for the central control unit 100 to perform spatial fault diagnosis. During normal operation, P flow (t) should be kept within the preset rated operating condition range. When the blowing and suction device runs to a certain position, if the suction port is blocked by lint or the filter screen is too thick with dust, it will cause the air duct resistance to increase sharply, which is manifested as P flow(t) (wind speed) significantly decreased or (negative pressure) abnormally increased. Conversely, if the fan drive belt is broken or the motor fails, P flow (t) will drop to near zero value instantaneously.

[0053] In order to achieve accurate positioning of the fault, the system health perception module 230 collects data P flow (t) inside the central control unit 100 and the real-time position data L pos (t) output by the precise positioning module 240 are spatiotemporally aligned. This data fusion mechanism enables the system not only to perceive that "a fault has occurred", but also to determine "where the fault occurred", thereby supporting subsequent corrective actions. For example, the system can identify whether the wind channel blockage occurred at the front, rear, or middle of the spinning device, thereby constructing a spatially dimensioned device health status distribution map.

[0054] The precise positioning module 240 is the key to achieving high-precision motion control of the blowing and suction device and spatial fault binding, mainly using high-precision absolute value encoders or magnetic grating rulers.

[0055] The positioning device is directly coupled with the walking motor shaft or walking track that drives the blowing and suction device to move reciprocally. When using an absolute value encoder, it calculates the absolute physical position of the blowing and suction device relative to the track zero point by measuring its own mechanical angle or the number of gear rotations installed on the walking mechanism, combined with the known mechanical transmission ratio. When using a magnetic grating ruler, it directly senses the precise scale of the blowing and suction device on the magnetic scale attached to the track using non-contact magnetic encoding technology, thereby obtaining position information. Both of these methods can provide high-resolution position feedback, with a position accuracy of millimeter level.

[0056] The precise positioning module 240 continuously outputs real-time physical position data L pos (t) of the blowing and suction device and transmits it to the central control unit 100 through a high-speed communication interface. The central control unit 100 uses L pos (t) data to perform the following functions: S241: High-precision pinpoint stopping during the doffing process. The stopping of the blowing and suction device of the traditional spinning machine relies on simple proximity switches and time relays, with low positioning accuracy. The present invention uses L pos (t) to achieve closed-loop position control, and the central control unit 100 compares it with the preset parking target position L target , and according to the position error E pos = L pos (t) - L target , issues precise speed regulation and braking instructions to the motion execution mechanism 310; Wherein: E pos is the real-time position error; L target The preset parking target position. This enables the blowing and sucking air device to stop at a specific spindle position at the front or rear of the spinning frame, for example, to accurately stay above the yarn feeding or doffing operation point of the doffing mechanism, ensuring smooth doffing.

[0057] S242: Spatial positioning of real-time anomalies. When the central control unit 100 performs real-time anomaly diagnosis (S300), L pos (t) is used to accurately spatiotemporally bind the detected process anomalies (data from the cleaning demand perception module 220) or system health anomalies (data from the system health perception module 230) to specific spindle positions or machine areas. For example, the central control unit 100 records the data structure of the anomaly event E as; {E type ,L pos (t),T stamp}; Wherein: E is the anomaly event record; E type is the anomaly type (e.g., process anomaly or spatial failure); T stamp is the timestamp of the anomaly occurrence. This precise spatial information is the basis for constructing the health distribution map M anomaly and is a prerequisite for intelligent navigation of the doffing gap to the failure point for corrective action (S400).

[0058] L pos The high resolution and high refresh rate of (t) are necessary technical guarantees for the high precision control and accurate fault location described above.

[0059] The execution and interaction unit 300 is responsible for receiving instructions from the central control unit 100, performing corresponding physical actions, and providing feedback to the operator. This unit is mainly composed of a motion execution mechanism 310 and a human-machine interaction module 320.

[0060] The motion execution mechanism 310 is a unit that realizes the physical action of the blowing and sucking air system. It receives control instructions from the central control unit 100 and converts them into start-stop or speed regulation of the fan, as well as reciprocating motion of the blowing and sucking air device on the track. This mechanism is mainly composed of a fan control assembly and a walking control assembly.

[0061] The blower control assembly includes the blower and its driving circuit. The driving circuit can employ contactors to achieve fixed speed start-stop control of the blower. In a preferred embodiment, the driving circuit employs a variable frequency drive (VFD) whose control terminals are connected to the analog output ports or communication interface of the central control unit 100. When performing dynamic intermittent operation control (S200), the central control unit 100 sends start-stop signals and frequency setting signals to the VFD to accurately execute the calculated blower operation time T on and stop time T off , and to adjust the blower speed to dynamically change the air volume.

[0062] The travel control assembly includes the travel motor and its motor driver for power supply and control. The travel motor is responsible for driving the blower to reciprocate along the track of the spinning frame. To achieve high-precision position control, the travel motor is preferably a servo motor whose servo driver is connected to the pulse output ports or high-speed field bus interface of the central control unit 100. The central control unit 100 forms a position closed-loop control in combination with the real-time position L pos (t) from the precision positioning module 240. The central control unit 100 issues speed adjustment and precise positioning instructions to the servo driver to execute high-precision positioning stop at a specific point during the doffing process (S241), and to navigate to the fault point position recorded in the health distribution map M anomaly (S400) when an abnormality is detected. In other embodiments, the travel motor can also employ a stepper motor whose driver receives pulse and direction signals from the central control unit 100 to achieve corresponding position control.

[0063] The human-machine interaction module 320 is responsible for providing state feedback to the operator during system operation, especially when an abnormality is detected. This module is connected to the output ports or data bus of the central control unit 100.

[0064] In one embodiment, the human-machine interaction module 320 contains basic audible and visual alarm elements, such as multi-color indicator lights and buzzers installed on the housing or control cabinet of the blower. When the central control unit 100 executes dynamic doffing intelligent response decision (S400) and finds an abnormality record in the health distribution map M anomaly , the central control unit 100 sends an alarm instruction to this module. After receiving the instruction, the module executes the corresponding prompt action, such as the indicator light of a specific color starts to flash, or the buzzer emits a sound of a specific frequency, to remind the operator that the device has an abnormality that needs to be intervened.

[0065] In another preferred embodiment, the human-machine interaction module 320 employs a human-machine interface (HMI) touch screen or liquid crystal display. This way provides more abundant information interaction capability. When the central control unit 100 detects an anomaly, it not only triggers an audible and visual alarm, but also extracts detailed information of the abnormal event from the health distribution map M anomaly and sends the information to the display screen for visualization. The displayed content specifically includes the type of anomaly (e.g., “process anomaly” or “air duct blockage”), the precise location of the anomaly (the location information is derived from the data bound by the precise positioning module 240), and the severity level and timestamp of the anomaly.

[0066] In this way, the operator can intuitively know the specific location and type of the fault, and quickly navigate to the fault point for inspection and maintenance during the doffing interval. In addition, if a touch screen is used, the module can also be used to receive the operator’s setting instructions, such as adjusting the operating parameters of the system or manually resetting the processed alarm information.

[0067] In a specific embodiment, the central control unit 100 employs a high-performance industrial programmable logic controller (PLC). The working condition perception module 210 is connected to the main control system of the spinning frame through an industrial Ethernet interface, and reads the current spindle speed, spinning variety, and other process parameters in real time. This module also includes two inductive proximity switches installed at both ends of the track, which are used for position calibration during the doffing period.

[0068] The precise positioning module 240 employs a high-resolution absolute encoder, which is coaxially connected to the walking servo motor (belonging to the motion execution mechanism 310) that drives the blowing and suction air device, ensuring that the central control unit 100 always obtains the high-precision absolute position of the blowing and suction air device on the spinning frame track.

[0069] The cleaning demand perception module 220 employs an optical scattering type dust concentration sensor, which is installed in the suction main pipe. The system health perception module 230 employs a differential pressure sensor, which is used to monitor the real-time negative pressure change of the suction air duct. The signals of these two sensors are both connected to the analog input end of the central control unit 100.

[0070] During normal spinning periods, the central control unit 100 performs dynamic gap operation control. Based on the process parameters (such as high-speed spinning) provided by the working condition module 210 and the real-time dust concentration provided by the cleaning demand module 220, the controller dynamically adjusts the running time and speed of the blower (belonging to the motion execution mechanism 310) through internal algorithms, achieving energy-saving operation.

[0071] During real-time anomaly diagnosis, the central control unit 100 continuously analyzes the air duct negative pressure data from the system health perception module 230 and correlates it with the position data from the precise positioning module 240.

[0072] S301: Assuming that when the blowing and sucking device is running to the middle of the machine body (for example, corresponding to the 500th spindle), a cotton flock is sucked in, causing the suction port to be temporarily blocked.

[0073] S302: The system health perception module 230 immediately detects that the air duct negative pressure value abnormally soars.

[0074] S303: The central control unit 100 captures this abnormal signal and immediately reads the data of the precision positioning module 240, recording the accurate physical position (for example, at 15.8 meters) when the blockage occurs.

[0075] S304: The controller stores this "space failure" event (type: air duct blockage, location: 15.8 meters) in the internal health distribution map.

[0076] Subsequently, when the spinning frame completes a spinning cycle and prepares to doff, the dynamic doffing intelligent response decision is executed: S401: The working condition perception module 210 receives the "preparing to doff" signal sent by the spinning frame main control system.

[0077] S402: The central control unit 100 responds to this signal and first queries the health distribution map, finding an unprocessed record of "air duct blockage at 15.8 meters".

[0078] S403: The central control unit 100 overrides the conventional "return to headstock parking" instruction and instead sends an instruction to the walking servo motor driver in the motion execution mechanism 310, causing the blowing and sucking device to move and stop accurately and quickly at the recorded 15.8 meters.

[0079] S404: At the same time, the central control unit 100 sends an instruction to the human-computer interaction module 320 (for example, a touch screen installed on the equipment), and a prompt message "Warning: suction port blockage at the 500th spindle position, please handle" pops up on the screen, and the red indicator light on the equipment starts to flash.

[0080] S405: The operator uses the doffing gap to directly go to 15.8 meters for inspection according to the clear instructions of the human-computer interaction module 320, and removes the blockage.

[0081] S406: The operator clicks the "fault cleared" button on the touch screen, and the central control unit 100 removes the abnormal record from the health distribution map and directs the blowing and sucking device to move to the standard parking point required for the doffing process, waiting for the doffing to be completed.

[0082] Through this embodiment, the system realizes automatic perception, accurate positioning and active prompting of physical faults without affecting the production rhythm (utilizing the doffing gap), thereby guaranteeing the continuous stability of the cleaning effect.

[0083] Referring to the drawings Figure 2 , Figure 2 is a method flowchart according to an embodiment of the present application, and the present application further provides an automatic control method for a spinning blower, comprising the following steps: S1: Real-time acquisition of states. The central control unit 100 acquires, in real time, spinning machine working condition signals from the working condition perception module 210, air duct state data from the system health perception module 230, and real-time position data of the blowing and sucking air device from the precise positioning module 240.

[0084] S2: Diagnosis and spatial positioning. The central control unit 100 continuously analyzes the air duct state data during the reciprocating operation of the blowing and sucking air device. When it is detected that the air duct state data indicates an abnormality (for example, air duct blockage), the current real-time position data reported by the precise positioning module 240 is immediately captured, the abnormal event is spatiotemporally bound with the physical position, and the spatial fault record is stored in the health distribution graph as a spatial fault record.

[0085] S3: Receiving a doffing trigger signal. The central control unit 100 receives the “ready to doff” signal sent by the spinning machine main control system through the working condition perception module 210.

[0086] S4: Starting intelligent response decision. The central control unit 100 responds to the “ready to doff” signal and immediately queries the health distribution graph to determine whether there is a spatial fault record that has not been processed.

[0087] S5: Performing a response action.

[0088] If there is a spatial fault record in the health distribution graph, the central control unit 100 executes an intelligent error correction process: sending an instruction to the motion execution mechanism 310 to drive the blowing and sucking air device to navigate in the doffing gap and stop at the fault physical position corresponding to the record; at the same time, instructing the man-machine interaction module 320 to issue a sound and light alarm or display fault position information to prompt the operator.

[0089] If there is no spatial fault record in the health distribution graph, the central control unit 100 executes a regular process: sending an instruction to the motion execution mechanism 310 to drive the blowing and sucking air device to move to a pre-set regular doffing parking point.

[0090] Referring to the drawings Figure 3 The present application further provides a computer device 40, comprising a processor 41 and a memory 42, wherein the memory 42 stores a computer program executable by the processor, and the computer program performs the above method when executed by the processor.

[0091] The application also provides a storage medium 43, which stores a computer program, and the computer program is executed by the processor 41 to perform the method as above.

[0092] The storage medium 43 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

Claims

1. A spinning blow and suction fan automatic control system, characterized by, The system comprises: a multi-modal perception unit configured to acquire real-time state information of the spinning frame, the real-time state information comprising: a preparation doffing signal acquired by a working condition perception module, air duct state data acquired by a system health perception module, and real-time position data of a blowing and suction device acquired by a precision positioning module; an execution and interaction unit comprising a motion execution mechanism for driving movement of the blowing and suction device; a central control unit electrically connected to the multi-modal perception unit and the execution and interaction unit; the central control unit is configured to: continuously analyze the air duct state data during operation of the blowing and suction device, and when an abnormality is detected in the air duct state data, immediately capture the current real-time position data, time-space bind the abnormal event with the real-time position data, and store the same as a spatial fault record in a health distribution map; in response to the preparation doffing signal received by the working condition perception module, query the health distribution map to determine whether there is a spatial fault record; if there is a spatial fault record in the health distribution map, instruct the motion execution mechanism to drive the blowing and suction device to navigate and stop at the fault physical position corresponding to the spatial fault record; if there is no spatial fault record in the health distribution map, instruct the motion execution mechanism to drive the blowing and suction device to move to a pre-set regular doffing parking point.

2. The auto control system of the blowing and suction fan for spinning according to claim 1, characterized in that, The system health perception module comprises a differential pressure sensor or a thermal type air speed sensor installed in the air duct; the central control unit detects whether the air duct state data indicates an abnormality by comparing the air duct state data with a pre-set health threshold.

3. The auto control system of the blowing and suction fan for spinning according to claim 1, characterized in that, The precision positioning module comprises a high-resolution absolute value encoder or a magnetic grating ruler coupled to the motion execution mechanism, to provide the real-time position data.

4. The auto control system of the blowing and suction fan for spinning according to claim 1, characterized in that, The working condition perception module comprises a process parameter interface connected to a main control PLC of the spinning frame, and the central control unit receives the preparation doffing signal via the process parameter interface.

5. The auto control system of the blowing and suction fan for spinning according to claim 1, characterized in that, The execution and interaction unit further comprises a human-computer interaction module; the central control unit, while instructing the motion execution mechanism to stop at the fault physical position, is further configured to: instruct the human-computer interaction module to issue an audible and visual alarm or display position information of the fault physical position.

6. The auto control system for a blowing and suction fan of a spinning frame according to claim 1, wherein The central control unit, while instructing the motion execution mechanism to move to the pre-set regular doffing parking point, is configured to: perform closed-loop position control using the real-time position data fed back by the precision positioning module, to achieve high-precision positioning.

7. The auto control system of the blowing and suction fan for spinning according to claim 1, characterized in that, The multi-modal perception unit further comprises a cleaning demand perception module for providing fly / fluff concentration data; the central control unit is further configured to: diagnose a process abnormality based on comparison of the fly / fluff concentration data with a dynamic threshold; and time-space bind the process abnormality with the real-time position data and store the same in the health distribution map.

8. The auto control system for a blowing and suction fan of a spinning frame according to claim 1, wherein The working condition perception module is further configured to provide process parameters; the central control unit is further configured to: Performing dynamic intermittent operation control, the dynamic intermittent operation control calculates the fan running time and fan stopping time through a decision model based on the flying / fluff concentration data and the process parameters, and instructs the blowing and suction fan in the motion execution mechanism to execute.

9. Spinning blower fan automatic control method according to any one of claims 1 to 8, characterized in that, The method comprises the following steps: S1: Real-time acquisition of state: Real-time acquisition of spinning frame working condition signals, air duct state data, and real-time position data of the blowing and suction device; S2: Diagnosis and spatial positioning: During operation of the blowing and suction device, the air duct state data is continuously analyzed, when it is detected that the air duct state data indicates an abnormality, the current real-time position data is immediately captured, the abnormal event is spatiotemporally bound with the real-time position data, and is stored as a spatial fault record in a health distribution map; S3: Receiving a doffing trigger signal: Receiving a doffing preparation signal in the spinning frame working condition signals; S4: Starting intelligent response decision: In response to the doffing preparation signal, immediately querying the health distribution map to determine whether there is an unprocessed spatial fault record; S5: Performing a response action: If there is the spatial fault record in the health distribution map, driving the blowing and suction device to navigate during a doffing gap and stop at the fault physical position corresponding to the spatial fault record; If there is no spatial fault record in the health distribution map, driving the blowing and suction device to move to a pre-set regular doffing parking point.

10. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by a processor to implement the system of any one of claims 1-8.

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