A self-adaptive charging system and method for a rehabilitation sky rail

Abstract

This invention discloses an adaptive charging system and method for a rehabilitation ceiling track, relating to the field of mobile power supply technology for nursing equipment. It includes: a data acquisition module for real-time acquisition of contact status datasets, charging electrical parameter datasets, ceiling track operating status datasets, and equipment status datasets throughout the entire ceiling track's journey, and preprocessing these to obtain standardized time-series fusion data; and a risk prediction module for classifying risk levels according to ceiling track sections and establishing a full-track contact failure feature library. Based on the standardized time-series fusion data and historical contact anomaly data pre-stored in the feature library, it identifies the development trend of contact failures and comprehensively analyzes the real-time contact risk level of the corresponding track section. This invention solves the problem of asynchronous contact adjustment and power compensation during ceiling track movement by setting up a dual closed-loop control module that links contact posture control and power compensation, achieving uninterrupted and stable charging throughout the entire ceiling track's journey.

Description

Technical Field

[0001] This invention relates to the field of mobile power supply technology for nursing equipment, specifically to an adaptive charging system and charging method for a rehabilitation ceiling track. Background Technology

[0002] The rehabilitation overhead rail system is a core piece of equipment used in hospital rehabilitation departments, ICUs, and elderly care facilities for patient transfer and weight-loss rehabilitation training. It effectively reduces the workload of nursing staff while ensuring the safety of patients during rehabilitation training and daily transfers. In recent years, it has been widely used and promoted in the field of medical rehabilitation. To meet the requirement of continuous operation of the overhead rail trolley throughout its entire journey, existing overhead rail systems mostly adopt a power supply method using an embedded sliding contact busbar within the track. Through the sliding contact between the onboard contact head and the busbar, real-time power supply and energy storage battery charging are achieved during the movement of the overhead rail trolley.

[0003] However, existing rehabilitation ceiling rail charging systems still have many shortcomings in actual use. When the ceiling rail trolley turns, passes through doors, changes tracks, and passes through track joints, it is prone to poor contact, loose connection, or even momentary disconnection of the contact head due to track misalignment, running vibration, and installation deviation. Existing control methods can only remedy the situation after the fault occurs, and cannot predict and avoid the risk of poor contact in advance, which can easily cause charging interruption and ceiling rail operation jamming. Therefore, an adaptive charging system and charging method for rehabilitation ceiling rails are proposed to solve these problems. Summary of the Invention

[0004] Technical problems to be solved To address the shortcomings of existing technologies, this invention provides an adaptive charging system and charging method for a rehabilitation skyrail, solving the problems mentioned in the background section.

[0005] Technical solution To achieve the above objectives, the present invention provides the following technical solution: an adaptive charging system for a rehabilitation skyrail, comprising: The data acquisition module is used to acquire in real time the contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset for the entire overhead rail journey, and to preprocess them to obtain standardized time-series fused data. The risk prediction module is used to classify risk levels according to the track sections of the skyrail and establish a feature library of poor contact in the entire track. Based on standardized time-series fusion data and historical contact anomaly data pre-stored in the feature library, it identifies the development trend of poor contact, comprehensively analyzes the real-time contact risk level of the corresponding track section, and outputs the prediction results of high-risk points and the anomaly trigger threshold. The feedforward control module is used to determine the timing and parameters of pre-control based on the prediction results of high-risk locations, the real-time operating speed and direction of the overhead track, and to send pre-aiming intervention control commands to the execution end. The closed-loop adjustment module is used to perform closed-loop correction control of contact posture and adaptive compensation control of charging power based on standardized time-series fusion data, poor contact development trend and target charging parameters, respectively. The safety control module is used to execute a graded fault handling strategy based on the real-time contact risk level and abnormal charging electrical parameters, and to perform a main / backup power supply switching operation under abnormal contact conditions.

[0006] Preferably, the contact status dataset includes real-time contact pressure at each contact point, contact resistance of the charging circuit, and triaxial position offset of the contact head relative to the power supply bus. The charging electrical parameter dataset includes bus-side input voltage, bus-side input current, load-side output voltage, load-side output current, real-time charging power, and on-board energy storage battery operating status data. The data set of the overhead track operation status includes the real-time position, speed, acceleration, direction of travel, real-time track position information, track segment attributes, and track change trigger signals of the overhead track trolley. The equipment status dataset includes the operating parameters of the contact attitude actuator, the operating status of the power regulation unit, the voltage of the buffer power supply module, and the linkage status data of the overhead rail main control system.

[0007] Preferably, the specific steps for obtaining standardized time-series fusion data are as follows: The contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset are timestamped to unify the time measurement dimension and sampling frequency of all data. All formatted data is filtered and noise-reduced to remove abnormal values ​​and abrupt data that exceed the normal fluctuation range; All processed data are integrated and aligned according to the three-dimensional association dimensions of timestamp, track segment identifier, and equipment number to form standardized time-series fused data.

[0008] Preferably, the specific steps for classifying risk levels according to the track sections of the skyrail and establishing a database of poor track contact features are as follows: Based on the physical properties and historical anomaly probability of the skyrail track, the entire track is divided into five types of sections: straight section, turning section, gate section, track changing section, and track joint section. Each section is assigned a unique location identifier and initial risk level. Collect basic parameters for the corresponding track section, including section length, track curvature, door misalignment, frequency of historical contact anomalies, and historical optimal contact control parameters; Based on the section location identifier, the above basic parameters are associated with historical contact status data and historical contact anomaly data pre-stored in the feature library to establish a full track contact failure feature library containing section attributes, basic parameters, risk level, anomaly characteristics, and optimal control parameters.

[0009] Preferably, the specific steps for comprehensively analyzing the real-time contact risk level of the corresponding track section are as follows: From the full track contact failure feature database, retrieve the historical contact data and abnormal feature thresholds corresponding to the current track section as the benchmark for judgment; Obtain real-time contact status data from standardized time-series fusion data, comprehensively analyze the deviation values ​​between the current contact parameters and the benchmark threshold, and obtain the basic risk value; The real-time operating speed and acceleration data of the overhead track are obtained, and the influence coefficient of the operating status on the contact stability is comprehensively analyzed to obtain the operating correction value. Obtain the historical anomaly frequency of the current track segment, comprehensively analyze the inherent risk coefficient of the segment, and obtain the segment correction value; By comprehensively analyzing the basic risk value, the operational correction value, and the section correction value, the real-time contact risk level of the current track section is obtained. At the same time, the development trend of poor contact, such as continuous increase in contact resistance and uneven contact pressure, is identified, and the prediction results of high-risk points are output.

[0010] Preferably, the specific steps for determining the pre-control timing and pre-control parameters in advance and issuing the pre-targeting intervention control command to the execution end are as follows: Based on the prediction results of high-risk locations and the real-time operating speed of the overhead rail, the remaining time for the overhead rail trolley to reach the high-risk location is comprehensively analyzed to determine the timing of the pre-control trigger. Based on the section type and risk level of high-risk locations, the corresponding optimal pre-control parameters are retrieved from the poor contact feature library, including the contact head reference contact pressure, floating margin adjustment value, smooth adjustment value of the overhead rail trolley running speed, and hot standby command of the buffer power supply module. When the pre-control triggering time arrives, corresponding pre-aiming intervention control commands are simultaneously sent to the contact attitude actuator, the main control system of the overhead rail, and the buffer power supply module.

[0011] Preferably, the specific steps for performing the closed-loop correction control of the contact posture are as follows: Real-time acquisition of contact status data from standardized time-series fusion data, comparison with the optimal contact parameter threshold in the poor contact feature library to determine whether there are contact parameters out of tolerance or abnormal trends; When any abnormality is detected, such as uneven contact pressure, contact resistance exceeding the threshold, or position offset exceeding the tolerance, the deviation between the current contact parameters and the optimal threshold is comprehensively analyzed to generate a contact posture correction command. The system issues correction commands to the contact attitude actuator to adjust the centering position, contact pressure, and pitch angle of the contact head in real time, bringing the contact parameters back to the optimal threshold range. After the correction is completed, the corrected contact parameters will be updated to the poor contact feature library to complete the self-learning optimization of the feature library.

[0012] Preferably, the specific steps for performing adaptive charging power compensation control are as follows: The charging electrical parameters, contact resistance data, and load status data are collected in real time from standardized time-series fusion data. The power loss is obtained by comprehensively analyzing the above data. Obtain the target charging parameters, and perform a comprehensive analysis based on the power loss to obtain the target output power; The deviation between the real-time output power on the load side and the target output power is collected, and the above deviation is analyzed comprehensively. The output duty cycle of the power regulation unit is adjusted to correct the output power so that the actual charging power on the load side is consistent with the target charging power. It can simultaneously identify load fluctuations caused by the start-stop, acceleration, and deceleration of the overhead rail and adjust the output power in advance.

[0013] Preferably, the specific steps for implementing the graded fault handling strategy are as follows: based on the real-time contact risk level and the abnormal state of charging electrical parameters, the fault is divided into three levels: minor abnormality, moderate abnormality, and severe abnormality. If it is a minor abnormality, the parameter correction is completed only by contact attitude closed-loop correction control, and the power compensation amount is adjusted synchronously. If the anomaly is moderate, while performing contact posture correction, the buffer power supply module is activated for hot standby, and the speed of the overhead track is limited simultaneously. If a severe anomaly is detected, i.e. a contact disconnection or electrical fault is detected, the main power supply is switched to the buffer power supply module through a contactless solid-state switch, and the maximum range of contact posture correction is performed simultaneously. After the contact is reliably restored, the main power supply is switched back. If the correction is ineffective, control the overhead track trolley to brake smoothly and trigger a visual and audible alarm.

[0014] An adaptive charging method for a rehabilitation sky track includes the following steps: Step 1: Real-time acquisition of contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset for the entire overhead rail journey, and preprocessing them to obtain standardized time-series fusion data; Step 2: Divide the risk level according to the track section of the skyrail and establish a feature library of poor contact of the entire track. Based on standardized time series fusion data and historical contact anomaly data pre-stored in the feature library, identify the development trend of poor contact, comprehensively analyze the real-time contact risk level of the corresponding track section, and output the prediction results of high-risk points and the anomaly trigger threshold. Step 3: Based on the prediction results of high-risk locations, the real-time operating speed and direction of the overhead track, determine the timing and parameters for pre-control in advance, and issue pre-aiming intervention control commands to the execution end; Step 4: Based on standardized time-series fusion data, the development trend of poor contact, and target charging parameters, execute closed-loop correction control of contact posture and adaptive compensation control of charging power respectively, and synchronously link the adjustment parameters of the two closed loops. Step 5: Based on the real-time contact risk level and abnormal charging electrical parameters, implement a graded fault handling strategy and perform a main / backup power supply switching operation under abnormal contact conditions.

[0015] Beneficial effects The present invention has the following beneficial effects: (1) The adaptive charging system and charging method for the rehabilitation ceiling track solves the problem of asynchronous contact adjustment and power compensation during the movement of the ceiling track by setting up a dual closed-loop control module that links contact posture control and power compensation, and realizes uninterrupted and stable charging during the entire movement of the ceiling track.

[0016] (2) The adaptive charging system and charging method for the rehabilitation ceiling track solves the problem of easy contact and disconnection when the ceiling track passes through the door, track change and joint areas by setting a risk prediction module with a full track contact failure feature library and a feedforward control module, and realizes early adaptation and adjustment of high-risk sections to avoid charging interruption.

[0017] (3) The adaptive charging system and charging method for the rehabilitation ceiling track solves the problem of unstable charging power caused by contact resistance fluctuation and load change by setting a power adaptive compensation module that is linked to the contact state in real time, thereby achieving accurate charging power compensation and continuous stable output.

[0018] (4) The adaptive charging system and charging method for the rehabilitation ceiling rail solves the problem of the ceiling rail easily stopping when charging is abnormal by setting up a safety control module for graded fault handling and seamless power supply switching, realizes seamless power supply switching under abnormal working conditions, and ensures the safe operation of the equipment.

[0019] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0020] Figure 1 This is a structural diagram of an adaptive charging system for a rehabilitation sky track according to the present invention; Figure 2 This is a flowchart of an adaptive charging method for a rehabilitation sky track according to the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] This invention provides a technical solution: an adaptive charging system for a rehabilitation ceiling track, such as... Figure 1 As shown, it includes: The data acquisition module is used to acquire in real time the contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset for the entire overhead rail journey, and to preprocess them to obtain standardized time-series fused data. The contact status dataset includes the real-time contact pressure of each contact point, the contact resistance of the charging circuit, and the triaxial position offset of the contact head relative to the power supply bus. The charging electrical parameter dataset includes bus-side input voltage, bus-side input current, load-side output voltage, load-side output current, real-time charging power, and on-board energy storage battery operating status data. The data set of the overhead track operation status includes the real-time position, speed, acceleration, direction of travel, real-time track position information, track segment attributes, and track change trigger signals of the overhead track trolley. The equipment status dataset includes the operating parameters of the contact attitude actuator, the operating status of the power regulation unit, the voltage of the buffer power supply module, and the linkage status data of the overhead rail main control system.

[0023] Thin-film pressure sensors with a range of 0-50N, an accuracy of ±0.05N, and a sampling frequency of 200Hz are installed on the contact surfaces of the four sets of symmetrical elastic contact heads on the overhead track trolley to collect the real-time contact pressure at each contact point; a four-wire high-precision resistance acquisition circuit with a measurement range of 0-100mΩ, an accuracy of ±0.1mΩ, and a sampling frequency of 200Hz is connected in series with the charging circuit to collect the real-time contact resistance of the charging circuit; A three-axis laser displacement sensor with a range of ±10mm, an accuracy of ±0.1mm, and a sampling frequency of 200Hz is installed on the contact head bracket to collect the three-axis position offset of the contact head relative to the power supply bus.

[0024] Hall voltage sensors with an accuracy of ±0.2% and a sampling frequency of 100Hz are installed on the input side of the overhead rail power supply bus and the output side of the vehicle load, respectively, to collect real-time voltage and current data on the bus side and the load side, and to calculate the real-time charging power through the power calculation circuit. An RS485 communication interface is set in the vehicle-mounted battery management system (BMS) with a sampling frequency of 50Hz to collect real-time operating status data such as battery charging and discharging status, voltage, and current.

[0025] An incremental encoder with a resolution of 1000 lines and a sampling frequency of 100Hz is installed on the shaft of the overhead track trolley's motor to collect motor speed and angle data in real time, and calculate the real-time position, running speed, acceleration and direction of travel of the overhead track trolley. An RFID location tag is deployed every 0.5m along the skyrail track. The tag pre-stores the unique identifier of the corresponding track section, the section attribute, and the initial risk level information. The skyrail trolley is equipped with an RFID reader with a sampling frequency of 50Hz to read the tag information in real time and obtain the real-time track location information and track section attributes. The track-changing actuator of the skyrail main control system is equipped with a dry contact signal interface to transmit the track-changing trigger signal to the data acquisition module in real time.

[0026] A CANopen communication interface is set on the servo driver of the contact attitude actuator, with a sampling frequency of 100Hz, to collect operating parameters such as motor operating frequency, output torque, and position feedback in real time. A data interface is set on the PWM rectifier control board of the power regulation unit, with a sampling frequency of 100Hz, to collect data such as rectifier operating status, output duty cycle, and fault alarms in real time. Voltage sensors with an accuracy of ±0.2% and a sampling frequency of 100Hz are installed at both ends of the supercapacitor group of the buffer power supply module to collect the voltage of the buffer power supply module in real time; it communicates with the main control system of the overhead rail via CAN bus with a sampling frequency of 50Hz to obtain data such as the operating status and linkage command execution status of the main control system of the overhead rail in real time.

[0027] The specific steps for obtaining standardized time-series fusion data are as follows: The contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset are formatted with timestamps. The time records of all collected data are uniformly converted into millisecond-level timestamps to unify the time measurement dimension of all data. At the same time, the sampling frequency of all data is uniformly aligned to 100Hz. For data with low sampling frequency, linear interpolation is used to fill in the time series to ensure that each dataset is accurately aligned on the time axis. All formatted data are filtered and noise reduced. Based on the historical operating data of the equipment, the normal fluctuation range of each parameter is determined using the 3σ principle. Abnormal values ​​and jump data that exceed the range are removed. The missing data after removal is filled in by the arithmetic mean of the effective values ​​of adjacent time periods. When there is no historical operating data during the first power-on operation, the feature library pre-stores the industry-standard track section anomaly feature benchmark data, initial risk level and optimal control parameters. After the equipment generates operating data, the feature library is updated synchronously. The contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset, which have undergone the above processing, are associated with each other according to time sequence, track section identifier, and equipment number. The data format and units of measurement are unified to form structured and standardized time-series fusion data.

[0028] The risk prediction module is used to classify risk levels according to the track sections of the skyrail and establish a feature library of poor contact in the entire track. Based on standardized time-series fusion data and historical contact anomaly data pre-stored in the feature library, it identifies the development trend of poor contact, comprehensively analyzes the real-time contact risk level of the corresponding track section, and outputs the prediction results of high-risk points and the anomaly trigger threshold. The specific steps for comprehensively analyzing the real-time contact risk level of the corresponding track section are as follows: From the full track contact failure feature database, retrieve the historical best operating speed and historical acceleration fluctuation benchmark value corresponding to the current track section as the benchmark judgment basis; among them, the historical best operating speed is the average speed of the section during historical safe and stable operation, and the rated operating speed of the sky track is used when there is no historical data. Obtain real-time contact status data from standardized time-series fusion data, comprehensively analyze the deviation values ​​between the current contact parameters and the benchmark threshold, and obtain the basic risk value; Among them, the greater the deviation of the contact pressure from the benchmark value, the more the contact resistance exceeds the threshold, and the greater the positional offset, the higher the basic risk value. The basic risk value ranges from 0 to 1. The real-time operating speed and acceleration data of the overhead track are obtained, and the influence coefficient of the operating status on the contact stability is comprehensively analyzed to obtain the operating correction value. Among them, the faster the operating speed and the greater the acceleration fluctuation, the higher the operating correction value, and the value range of the operating correction value is 0-0.5; the historical anomaly frequency of the current track section is obtained, and the inherent risk coefficient of the section is comprehensively analyzed to obtain the section correction value; When the total number of runs for the first time is 0, the section correction value is taken as the default value according to the initial risk level of the section: 0.1 for low-risk sections, 0.2 for medium-risk sections, and 0.4 for high-risk sections. Among them, the higher the frequency of historical anomalies, the higher the segment correction value, and the range of the segment correction value is 0-0.5; The base risk value, operation correction value, and section correction value are combined to calculate the real-time contact risk value of the current track section. Based on the numerical range of the real-time contact risk value, the real-time contact risk level is divided into three levels: low risk, medium risk, and high risk. Simultaneously, the development trend of poor contact, such as continuous increase in contact resistance and uneven contact pressure, is identified, and the prediction result of high-risk points is output.

[0029] The specific method for obtaining the runtime correction value is as follows: From the full track contact failure feature database, retrieve the historical best operating speed and historical acceleration fluctuation benchmark value corresponding to the current track section as the benchmark judgment basis; Obtain the real-time running speed of the skyrail, and calculate the deviation between the real-time running speed and the historical best running speed. That is, the speed deviation is obtained by subtracting the historical best running speed from the real-time running speed. A positive speed deviation indicates that the running speed is higher than the optimal value, and a negative speed deviation indicates that the running speed is lower than the optimal value. Obtain real-time acceleration data of the sky track, calculate the fluctuation range of acceleration in the current period, that is, the difference between the maximum acceleration and the minimum acceleration in the current period, and obtain the real-time acceleration fluctuation range; Based on the weights of the impact of velocity deviation and real-time acceleration fluctuation amplitude on contact stability, with velocity deviation having a higher weight than acceleration fluctuation amplitude (e.g., velocity deviation weight 0.7 and acceleration fluctuation amplitude weight 0.3), the velocity deviation and real-time acceleration fluctuation amplitude are multiplied by their respective weights, summed, and then divided by the historical best operating speed to obtain the operating correction value. When the deviation is positive, the correction term is positive, indicating that the exposure risk needs to be increased; when the deviation is negative, the correction term is negative, indicating that the exposure risk can be reduced.

[0030] The specific method for obtaining the segment correction value is as follows: Retrieve the historical anomaly frequency and total number of operations in the past 12 months for the current track section from the full track contact failure feature database; Calculate the historical anomaly probability of the current track segment, which is the frequency of historical anomalies divided by the total number of runs; Based on the proportion of the impact of the probability of anomaly occurrence on the inherent risk of the section, the probability of anomaly occurrence is converted into a section correction value; The higher the probability of an anomaly, the higher the segment correction value. For example, the segment correction value is 0.1 when the probability of an anomaly is 5%, 0.2 when the probability of an anomaly is 10%, and 0.4 when the probability of an anomaly is 20%, with a maximum of 0.5.

[0031] The method for obtaining the real-time contact risk value is as follows: In the formula, Indicates the first Real-time contact risk values ​​for each track segment Indicates the first The basic risk value for each track segment is a dimensionless coefficient. Indicates the first The operational correction values ​​corresponding to each track segment are dimensionless coefficients. Indicates the first The segment correction value for each orbital segment is a dimensionless coefficient. when A value less than 0.5 indicates low risk, while a value ≤ 0.5 indicates low risk. A value less than 1.2 indicates a medium risk level. A value ≥1.2 indicates high risk.

[0032] The feedforward control module is used to determine the timing and parameters of pre-control based on the prediction results of high-risk locations, the real-time operating speed and direction of the overhead track, and to send pre-aiming intervention control commands to the execution end. The specific steps for determining the pre-control timing and pre-control parameters in advance, and issuing pre-targeting intervention control commands to the execution end are as follows: Based on the prediction results of high-risk locations and the real-time operating speed of the overhead rail, the remaining time for the overhead rail trolley to reach the high-risk location is comprehensively analyzed to determine the timing of the pre-control trigger. The pre-control triggering time is before the overhead rail trolley reaches the high-risk point, reserving a time window to complete the pre-adjustment actions. The time window is calculated by multiplying the real-time running speed of the overhead rail by the preset safety lead time. The preset safety lead time is not less than the minimum time required for the pre-adjustment actions, ensuring that all pre-adjustment actions are completed before the trolley reaches the high-risk point. Based on the section type and risk level of high-risk locations, the corresponding optimal pre-control parameters are retrieved from the poor contact feature library, including the contact head reference contact pressure, floating margin adjustment value, smooth adjustment value of the overhead rail trolley running speed, and hot standby command of the buffer power supply module. Among them, the high-risk section corresponds to a higher reference contact pressure, a larger floating margin, and a lower operating speed limit; the medium-risk section corresponds to a medium reference contact pressure, a medium floating margin, and a medium operating speed limit; and the low-risk section maintains the default operating parameters. When the pre-control triggering time arrives, corresponding pre-aiming intervention control commands are simultaneously sent to the contact attitude actuator, the main control system of the overhead rail, and the buffer power supply module to complete the adaptation and adjustment of high-risk points in advance. Among them, the contact attitude actuator adjusts the contact pressure and floating margin of the contact head according to the pre-controlled parameters, the main control system of the overhead rail controls the running speed of the trolley according to the smooth adjustment value, and the buffer power supply module completes hot standby start-up to ensure stable contact and continuous power supply during the passage of high-risk sections.

[0033] The closed-loop adjustment module is used to execute contact posture closed-loop correction control and charging power adaptive compensation control based on standardized time-series fusion data, poor contact development trend and target charging parameters, and synchronously link the adjustment parameters of the two closed loops. The specific steps for performing closed-loop correction control of contact posture are as follows: Real-time acquisition of contact status data from standardized time-series fusion data, comparison with the optimal contact parameter threshold in the poor contact feature library to determine whether there are contact parameters out of tolerance or abnormal trends; When any abnormality is detected, such as uneven contact pressure, contact resistance exceeding the threshold, or position offset exceeding the tolerance, the deviation between the current contact parameters and the optimal threshold is comprehensively analyzed to generate a contact posture correction command. Among them, the deviation is positively correlated with the correction adjustment range, ensuring that the correction action is accurately matched to the degree of abnormality and avoiding secondary contact fluctuations caused by over-adjustment; The system sends a correction command to the contact posture actuator, and adjusts the centering position, contact pressure, and pitch angle of the contact head in real time through the servo drive mechanism to pull the contact parameters back to the optimal threshold range. After correction, the corrected contact parameters are updated to the poor contact feature library to complete the self-learning optimization of the feature library and continuously improve the accuracy of subsequent prediction and correction.

[0034] The specific steps for implementing adaptive charging power compensation control are as follows: The charging electrical parameters, contact resistance data, and load status data are collected in real time from standardized time-series fusion data. By comprehensively analyzing the above data, the circuit power loss is obtained. The method for obtaining the circuit power loss is as follows: In the formula, Indicates the power loss of the circuit. This represents the real-time current of the charging circuit, expressed in amperes (A). This indicates the real-time contact resistance of the charging circuit, in Ω. This represents the inherent impedance of the charging circuit, measured in Ω. Obtain the target charging parameters, and perform a comprehensive analysis based on the power loss to obtain the target output power; The target output power is obtained in the following way: In the formula, This indicates the target output power of the power regulation unit, in watts (W). This indicates the preset target charging power, in watts (W). This represents the circuit power loss, measured in watts (W), and is calculated from the contact resistance, line impedance, and circuit current. The deviation between the real-time output power on the load side and the target output power is collected, and the above deviation is analyzed comprehensively. The output duty cycle of the power regulation unit is adjusted to correct the output power so that the actual charging power on the load side is consistent with the target charging power. By synchronously using the overhead rail operation status dataset, the start / stop and acceleration / deceleration commands issued by the overhead rail main control system can be obtained in advance, the upcoming load fluctuations can be identified, the output power can be adjusted in advance, and the power fluctuations caused by sudden load changes can be eliminated.

[0035] The contact posture closed-loop correction control and the charging power adaptive compensation control are linked in real time. When the contact posture closed-loop performs the correction action and the contact resistance changes, the contact resistance data is transmitted to the power compensation control unit in real time. The power compensation control unit updates the power loss calculation results in real time and adjusts the output power in real time to ensure that the charging power remains stable without fluctuation or drop during the contact posture adjustment process.

[0036] The safety control module is used to execute graded fault handling strategies based on real-time contact risk level and abnormal charging electrical parameters, and to perform main and backup power supply switching operations under abnormal contact conditions. The specific steps for implementing the graded fault handling strategy are as follows: Based on the real-time contact risk level and abnormal state of charging electrical parameters, the fault is divided into three levels: minor abnormality, moderate abnormality, and severe abnormality. Among them, minor anomalies correspond to contact parameters exceeding the tolerance but not exceeding the safety threshold and the circuit is conducting normally; moderate anomalies correspond to contact parameters exceeding the safety threshold but the circuit remains conducting and there are no electrical faults; severe anomalies correspond to contact disconnection, circuit short circuit / leakage and other electrical faults. If it is a minor anomaly, the parameter correction is completed only through contact attitude closed-loop correction control, and the power compensation amount is adjusted synchronously. There is no need to switch the power supply and it does not affect the normal operation of the overhead rail. If the anomaly is moderate, while performing contact posture correction, the buffer power supply module is activated for hot standby, and the overhead rail running speed is simultaneously limited to 50% of the rated speed to prevent the anomaly from escalating. Once the contact parameters return to the normal range, the speed limit and hot standby status are lifted. If a severe anomaly is detected, i.e. a contact disconnection or electrical fault is detected, the main power supply is switched to the buffer power supply module through a contactless solid-state switch, and the maximum range of contact posture correction is performed simultaneously. After the contact is reliably restored, the main power supply is smoothly switched back. If the correction is ineffective, the overhead track trolley will brake smoothly, triggering a visual and audible alarm. At the same time, the fault information will be uploaded to the medical staff operation terminal and the hospital's equipment management system to ensure the safety of equipment and personnel.

[0037] An adaptive charging control method for a rehabilitation skyrail, such as Figure 2 As shown, it includes the following steps: Step 1: Real-time acquisition of contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset for the entire overhead rail journey, and preprocessing them to obtain standardized time-series fusion data; Step 2: Divide the risk level according to the track section of the skyrail and establish a feature library of poor contact of the entire track. Based on standardized time series fusion data and historical contact anomaly data pre-stored in the feature library, identify the development trend of poor contact, comprehensively analyze the real-time contact risk level of the corresponding track section, and output the prediction results of high-risk points and the anomaly trigger threshold. Step 3: Based on the prediction results of high-risk locations, the real-time operating speed and direction of the overhead track, determine the timing and parameters for pre-control in advance, and issue pre-aiming intervention control commands to the execution end; Step 4: Based on standardized time-series fusion data, the development trend of poor contact, and target charging parameters, execute closed-loop correction control of contact posture and adaptive compensation control of charging power respectively, and synchronously link the adjustment parameters of the two closed loops. Step 5: Based on the real-time contact risk level and abnormal charging electrical parameters, implement a graded fault handling strategy and perform a main / backup power supply switching operation under abnormal contact conditions.

[0038] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0039] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An adaptive charging system for a rehabilitation ceiling track, characterized in that, include: The data acquisition module is used to acquire in real time the contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset for the entire overhead rail journey, and to preprocess them to obtain standardized time-series fused data. The risk prediction module is used to classify risk levels according to the track sections of the skyrail and establish a feature library of poor contact in the entire track. Based on standardized time-series fusion data and historical contact anomaly data pre-stored in the feature library, it identifies the development trend of poor contact, comprehensively analyzes the real-time contact risk level of the corresponding track section, and outputs the prediction results of high-risk points and the anomaly trigger threshold. The feedforward control module is used to determine the timing and parameters of pre-control based on the prediction results of high-risk locations, the real-time operating speed and direction of the overhead track, and to send pre-aiming intervention control commands to the execution end. The closed-loop adjustment module is used to execute contact posture closed-loop correction control and charging power adaptive compensation control based on standardized time-series fusion data, poor contact development trend and target charging parameters, and synchronously link the adjustment parameters of the two closed loops. The safety control module is used to execute a graded fault handling strategy based on the real-time contact risk level and abnormal charging electrical parameters, and to perform a main / backup power supply switching operation under abnormal contact conditions.

2. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The contact status dataset includes the real-time contact pressure of each contact point, the contact resistance of the charging circuit, and the triaxial position offset of the contact head relative to the power supply bus. The charging electrical parameter dataset includes bus-side input voltage, bus-side input current, load-side output voltage, load-side output current, real-time charging power, and on-board energy storage battery operating status data. The data set of the overhead track operation status includes the real-time position, speed, acceleration, direction of travel, real-time track position information, track segment attributes, and track change trigger signals of the overhead track trolley. The equipment status dataset includes the operating parameters of the contact attitude actuator, the operating status of the power regulation unit, the voltage of the buffer power supply module, and the linkage status data of the overhead rail main control system.

3. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for obtaining standardized time-series fusion data are as follows: The contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset are timestamped to unify the time measurement dimension and sampling frequency of all data. All formatted data is filtered and noise-reduced to remove abnormal values ​​and abrupt data that exceed the normal fluctuation range; All processed data are integrated and aligned according to the three-dimensional association dimensions of timestamp, track segment identifier, and equipment number to form standardized time-series fused data.

4. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for classifying risk levels according to the track sections of the overhead rail system and establishing a database of poor track contact characteristics are as follows: Based on the physical properties and historical anomaly probability of the skyrail track, the entire track is divided into five types of sections: straight section, turning section, gate section, track changing section, and track joint section. Each section is assigned a unique location identifier and initial risk level. Collect basic parameters for the corresponding track section, including section length, track curvature, door misalignment, frequency of historical contact anomalies, and historical optimal contact control parameters; Based on the section location identifier, the above basic parameters are associated with historical contact status data and historical contact anomaly data pre-stored in the feature library to establish a full track contact failure feature library containing section attributes, basic parameters, risk level, anomaly characteristics, and optimal control parameters.

5. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for comprehensively analyzing the real-time contact risk level of the corresponding track section are as follows: From the full track contact failure feature database, retrieve the historical contact data and abnormal feature thresholds corresponding to the current track section as the benchmark for judgment; Obtain real-time contact status data from standardized time-series fusion data, comprehensively analyze the deviation values ​​between the current contact parameters and the benchmark threshold, and obtain the basic risk value; The real-time operating speed and acceleration data of the overhead track are obtained, and the influence coefficient of the operating status on the contact stability is comprehensively analyzed to obtain the operating correction value. Obtain the historical anomaly frequency of the current track segment, comprehensively analyze the inherent risk coefficient of the segment, and obtain the segment correction value; By comprehensively analyzing the basic risk value, the operational correction value, and the section correction value, the real-time contact risk level of the current track section is obtained. At the same time, the development trend of poor contact, such as continuous increase in contact resistance and uneven contact pressure, is identified, and the prediction results of high-risk points are output.

6. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for determining the pre-control timing and pre-control parameters in advance, and issuing pre-targeting intervention control commands to the execution end are as follows: Based on the prediction results of high-risk locations and the real-time operating speed of the overhead rail, the remaining time for the overhead rail trolley to reach the high-risk location is comprehensively analyzed to determine the timing of the pre-control trigger. Based on the section type and risk level of high-risk locations, the corresponding optimal pre-control parameters are retrieved from the poor contact feature library, including the contact head reference contact pressure, floating margin adjustment value, smooth adjustment value of the overhead rail trolley running speed, and hot standby command of the buffer power supply module. When the pre-control triggering time arrives, corresponding pre-aiming intervention control commands are simultaneously sent to the contact attitude actuator, the main control system of the overhead rail, and the buffer power supply module.

7. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for performing closed-loop correction control of contact posture are as follows: Real-time acquisition of contact status data from standardized time-series fusion data, comparison with the optimal contact parameter threshold in the poor contact feature library to determine whether there are contact parameters out of tolerance or abnormal trends; When any abnormality is detected, such as uneven contact pressure, contact resistance exceeding the threshold, or position offset exceeding the tolerance, the deviation between the current contact parameters and the optimal threshold is comprehensively analyzed to generate a contact posture correction command. The system issues correction commands to the contact attitude actuator to adjust the centering position, contact pressure, and pitch angle of the contact head in real time, bringing the contact parameters back to the optimal threshold range. After the correction is completed, the corrected contact parameters will be updated to the poor contact feature library to complete the self-learning optimization of the feature library.

8. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for implementing adaptive charging power compensation control are as follows: The charging electrical parameters, contact resistance data, and load status data are collected in real time from standardized time-series fusion data. The power loss is obtained by comprehensively analyzing the above data. Obtain the target charging parameters, and perform a comprehensive analysis based on the power loss to obtain the target output power; The deviation between the real-time output power on the load side and the target output power is collected, and the above deviation is analyzed comprehensively. The output duty cycle of the power regulation unit is adjusted to correct the output power so that the actual charging power on the load side is consistent with the target charging power. It can simultaneously identify load fluctuations caused by the start-stop, acceleration, and deceleration of the overhead rail and adjust the output power in advance.

9. The adaptive charging system for a rehabilitation ceiling track according to claim 1, characterized in that: The specific steps for implementing the graded fault handling strategy are as follows: Based on the real-time contact risk level and the abnormal state of charging electrical parameters, the fault is divided into three levels: minor abnormality, moderate abnormality, and severe abnormality. If it is a minor abnormality, the parameter correction is completed only by contact attitude closed-loop correction control, and the power compensation amount is adjusted synchronously. If the anomaly is moderate, while performing contact posture correction, the buffer power supply module is activated for hot standby, and the speed of the overhead track is limited simultaneously. If a severe anomaly is detected, i.e. a contact disconnection or electrical fault is detected, the main power supply is switched to the buffer power supply module through a contactless solid-state switch, and the maximum range of contact posture correction is performed simultaneously. After the contact is reliably restored, the main power supply is switched back. If the correction is ineffective, control the overhead track trolley to brake smoothly and trigger a visual and audible alarm.

10. An adaptive charging method for a rehabilitation sky track, applied to the adaptive charging system for a rehabilitation sky track as described in claim 1, characterized in that, Includes the following steps: Step 1: Real-time acquisition of contact status dataset, charging electrical parameter dataset, overhead rail operation status dataset, and equipment status dataset for the entire overhead rail journey, and preprocessing them to obtain standardized time-series fusion data; Step 2: Divide the risk level according to the track section of the skyrail and establish a feature library of poor contact of the entire track. Based on standardized time series fusion data and historical contact anomaly data pre-stored in the feature library, identify the development trend of poor contact, comprehensively analyze the real-time contact risk level of the corresponding track section, and output the prediction results of high-risk points and the anomaly trigger threshold. Step 3: Based on the prediction results of high-risk locations, the real-time operating speed and direction of the overhead track, determine the timing and parameters for pre-control in advance, and issue pre-aiming intervention control commands to the execution end; Step 4: Based on standardized time-series fusion data, the development trend of poor contact, and target charging parameters, execute closed-loop correction control of contact posture and adaptive compensation control of charging power respectively, and synchronously link the adjustment parameters of the two closed loops. Step 5: Based on the real-time contact risk level and abnormal charging electrical parameters, implement a graded fault handling strategy and perform a main / backup power supply switching operation under abnormal contact conditions.

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