Base Station Companion Remote Access Management and Control System

Abstract

This application relates to the technical field of remote control of base station equipment and discloses a remote access control management and control system for a base station companion, including a data acquisition module, a feature extraction module, a state recognition module, and an access control module. Specifically, the data acquisition module is used to collect the operating current and photoelectric switch signals of an electronic lock; the feature extraction module is used to extract access control feature data of the base station companion; the state recognition module is used to construct a state transition chain for the access control and detect abnormal access control states based on the state transition chain; when an abnormal access control state occurs, the state recognition module identifies the abnormality type of the abnormal state; and the access control module performs access control on the base station companion based on the abnormality type and predicts the access control results. This application significantly improves the state recognition accuracy and remote control reliability of the base station access control system, realizing intelligent operation and maintenance of base station equipment.

Description

Technical Field

[0001] The present application relates to the technical field of remote control of base station equipment, and in particular to a base station companion remote access management and control system. Background Art

[0002] Base station companions, such as intelligent power cabinets, are crucial supporting equipment for base stations, responsible for power supply, equipment protection, and environmental monitoring. Access control systems are key components of base station companions, ensuring the security of internal equipment. In recent years, remote access control management and control systems have become mainstream in the industry. Through automated monitoring and control, they reduce the frequency of manual inspections and improve base station operation and maintenance efficiency. While existing technologies have achieved a certain degree of automated monitoring of access control status, they still face numerous deficiencies in actual operation.

[0003] Existing solutions often rely on a single sensor to determine the access control status, which is prone to misjudgment due to environmental interference such as dust, strong light, or aging equipment. They also use fixed thresholds. For example, if the current value exceeds a certain value, it is judged as an abnormality, and they cannot dynamically adapt to different working conditions. Existing systems usually treat all abnormalities in a unified manner and cannot distinguish between abnormalities that can be automatically recovered and abnormalities that cannot be recovered, resulting in unnecessary remote intervention, such as repeated attempts to close the door, or delays in repairing critical faults. Existing access control systems lack the ability to predict control results in real time. It is impossible to predict rebound, jamming, and other phenomena that may occur during the door closing process, and failure can only be passively judged through post-facto feedback, delaying fault handling. The door may be unable to close due to external force, but the system continues to send closing commands, causing motor overload or mechanical structure damage.

[0004] For example, Chinese patent application CN205212219U discloses a power distribution cabinet with a door-closing reminder function. The cabinet comprises a cabinet body and a door, with a switch mounted within the cabinet body. The door is equipped with a reminder device comprising: a light detection unit for detecting light intensity within the cabinet body and outputting a corresponding detection signal; a human body sensing unit for outputting a corresponding sensing signal in response to a human body approaching or moving away; a control unit for outputting a corresponding control signal in response to the sensing signal and the detection signal value; a reminder unit for activating or deactivating the reminder function in response to the control signal; and a power supply unit for providing an operating voltage to the reminder device. This utility model has the function of reminding staff that a cabinet door is not properly closed.

[0005] For example, Chinese patent application publication number CN112054394A discloses a protective device for an electric control cabinet and an air conditioning unit, comprising: a self-locking device that automatically locks the cabinet door when it is closed, a door-closing device that can close the cabinet door, a low-light sensor installed inside the electric control cabinet to detect light intensity, and a controller that controls the door-closing device or disconnects the power supply to the electric control cabinet based on the state of the self-locking device when the electric control cabinet is powered on and the light intensity signal exceeds a preset threshold. This invention controls the closing of the cabinet door based on light intensity and the cabinet door's closed state, eliminating the need for users to manually close the cabinet door. This prevents staff from accidentally forgetting to close or lock the cabinet door, improving the safety of the frequency converter cabinet and preventing damage to the cabinet body caused by dust, moisture, corrosion, and the like. Furthermore, the power supply can be disconnected based on a strong light signal. When a power device explodes or other components are damaged, generating a light arc, the power supply can be automatically disconnected to avoid continued impact, thus promptly and accurately protecting the equipment inside the frequency converter cabinet and minimizing losses.

[0006] The above technical solutions all have the problem raised by this background technology: they cannot distinguish between automatically recoverable exceptions and unrecoverable exceptions, resulting in unnecessary remote intervention.

[0007] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the application and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to ordinary technicians in this field. Summary of the Invention

[0008] The technical problem to be solved by this application is to overcome the defects of the existing technology and provide a base station companion remote access control management and control system, which improves the status recognition accuracy and remote control reliability of the base station access control system and realizes the intelligent operation and maintenance of base station equipment.

[0009] To solve the above technical problems, this application provides the following technical solutions:

[0010] A base station companion remote access control management and control system, including a data acquisition module, a feature extraction module, a state recognition module, and an access control module; wherein:

[0011] The data acquisition module is used to collect the working current and photoelectric switch signal of the electronic lock;

[0012] The feature extraction module extracts access control feature data of the base station companion based on the working current and the photoelectric switch signal;

[0013] The state recognition module constructs a state transition chain of the access control based on the access control feature data, and detects abnormal states of the access control based on the state transition chain; when an abnormal state occurs in the access control, the state recognition module identifies the abnormal type of the abnormal state;

[0014] The access control module performs access control on the base station companion based on the abnormality type and predicts the access control result; the access control module triggers an access abnormality alarm based on the abnormality type and the access control result.

[0015] As a preferred solution of the base station companion remote access control and management system described in this application, wherein: the feature extraction module includes a feature extraction unit and a data sorting unit;

[0016] The feature extraction unit is used to extract access control feature data of the base station companion; the access control feature data includes statistical features of the working current, frequency features and trend features of the photoelectric switch signal;

[0017] The feature extraction unit extracts the trend feature of the photoelectric switch signal by curve fitting, specifically comprising: reading the photoelectric switch signal at each moment, and performing curve fitting on the photoelectric switch signal to obtain a curve equation of the photoelectric switch signal; setting a time window, and calculating the trend feature of the photoelectric switch signal in each time window based on the curve equation, wherein the trend feature includes a slope and an intercept;

[0018] The data sorting unit is used to sort the access control feature data and construct an access control feature sequence, specifically including: standardizing each access control feature data separately; time aligning each access control feature data; encoding each access control feature data at the same time and splicing it into an access control feature sequence at the corresponding time.

[0019] As a preferred solution of the base station companion remote access control management and control system described in this application, wherein: the state identification module includes a state detection unit; the state detection unit is used to build a state transfer chain for access control;

[0020] The state detection unit is configured with a state classification model; the state detection unit identifies the access control state based on the state classification model; the input of the state classification model is the access control feature sequence at any time, and the output is the identification result of the access control state at the corresponding time; the access control state includes normal working state and abnormal working state; the normal working state includes stable door closing, door opening response, door opening execution, door opening intervention, maintenance stop, door closing response, door closing execution, and door closing intervention;

[0021] The state detection unit is also equipped with a state transition model to predict the next access control state;

[0022] The state detection unit composes the access control state at each moment in the last N minutes and the predicted access control state at the next moment into the state transfer chain in chronological order, and records the duration of each access control state in the state transfer chain.

[0023] As a preferred solution of the base station companion remote access control and management system described in this application, the state detection unit predicts the access control state at the next moment in the following manner:

[0024] Discretize and encode the access control feature sequence at each moment in the last N minutes to obtain the observation value at each moment; N is a positive integer;

[0025] The observation value at each moment is input into the state transition model; the state transition model calculates and outputs the transition probability of each access control state at the next moment; and the access control state with the highest transition probability is extracted as the alternative access control state;

[0026] The state detection unit is further configured with a transition probability threshold; if the transition probability of the candidate access control state is greater than the transition probability threshold, the access control state at the next moment is the candidate access control state; otherwise, the access control state at the next moment is the current access control state.

[0027] As a preferred solution of the base station companion remote access control management and control system described in this application, the state detection unit is further used to detect abnormal state of the access control according to the state transition chain, specifically including:

[0028] If the access control status in the state transfer chain includes an abnormal working state, then the access control is in an abnormal state;

[0029] The state detection unit is also configured with a reference state chain; any reference state chain includes a sequence of different access control states in the order of transition when the access control does not have an abnormal state, and marks the duration threshold interval of each access control state; the abnormal state detection of the access control also includes:

[0030] Extracting a state transition sequence from the state transition chain; the state transition sequence is a sequence of different access control states in the state transition chain in a transition order, and marking the duration of each access control state;

[0031] If any reference state chain includes a segment that corresponds one-to-one to the access control state in the state transition sequence, the segment is marked as a reference state sequence;

[0032] If there is at least one reference state sequence such that the duration of each access control state in the state transition sequence is within the duration threshold interval of the corresponding access control state in the reference state sequence, then the access control is not in an abnormal state; otherwise, the access control is in an abnormal state.

[0033] As a preferred solution of the base station companion remote access control management and control system described in this application, the state recognition module further includes an abnormality recognition unit; the abnormality recognition unit is used to identify the abnormal type of the abnormal state of the access control, specifically including:

[0034] Based on the statistical characteristics of the working current, the state of the electronic lock is identified; the state of the electronic lock includes a standby state, a lock response state, a lock execution state, and an abnormal state;

[0035] Dividing the slope of the photoelectric switch signal into different slope intervals; the slope intervals include a slow change interval, a fast change interval, and an abnormal fluctuation interval;

[0036] The abnormality type includes a permanent abnormality; the abnormality identification unit identifies the permanent abnormality of the access control based on the state and slope interval of the electronic lock, specifically including:

[0037] If the electronic lock is in the locked execution state and the slope of the photoelectric switch signal is always in the slow change range for at least n seconds, the abnormality type is permanent abnormality;

[0038] If the electronic lock passes through the lock response state, lock execution state, and standby state in sequence within m seconds, and the intensity value of the photoelectric switch signal is lower than the preset intensity threshold, the abnormality type is permanent abnormality;

[0039] If the electronic lock is in an abnormal state, or the slope of the photoelectric signal is in an abnormal fluctuation range, the abnormality type is permanent abnormality.

[0040] As a preferred solution of the base station companion remote access control management and control system described in this application, the abnormality type also includes permanent abnormality and recoverable abnormality; the abnormality identification unit further identifies the recoverable abnormality of the access control based on the state and slope interval of the electronic lock, specifically including:

[0041] If the electronic lock is in the locked execution state, and the photoelectric signal slope is always in the fast change range, or transitions from the slow change range to the fast change range for at least n seconds, the abnormality type is recoverable abnormality;

[0042] If the electronic lock is in standby state and has not experienced the lock response state or lock execution state within m seconds, and the slope of the photoelectric switch signal is not in the abnormal fluctuation range or the rapid change range, the abnormality type is a recoverable abnormality.

[0043] As a preferred solution of the base station companion remote access control and control system described in this application, wherein: the access control module includes a control unit and a prediction unit;

[0044] The control unit is used to perform access control on the base station companion according to the access control exception type, specifically including: if the access control exception type is a recoverable exception, sending an access control instruction to the base station companion to control the base station companion to automatically close and lock the door;

[0045] The prediction unit is used to predict the access control result; the access control result includes automatic door closing failure and automatic door closing success;

[0046] The prediction unit is also used to trigger an abnormality alarm based on the access control abnormality type and access control result, specifically including: if the access control abnormality type is a permanent abnormality or the access control result is an automatic door closing failure, an abnormality alarm is sent to the management end.

[0047] As a preferred solution of the base station companion remote access control and management system described in this application, the prediction unit is configured with a state prediction model; the prediction unit predicts the door closing state at each time step after the base station companion responds to the access control command based on the state prediction model, specifically including:

[0048] Each statistical feature of the electronic lock's operating current and the intensity and slope of the photoelectric switch signal are organized into corresponding time series. Each time series is input into a state prediction model, which predicts the door closing state in the next M time steps. The door closing state includes fully open, half open, and closed.

[0049] The prediction unit determines the access control result based on the predicted door closing state, specifically including:

[0050] During the process of the base station companion automatically closing the door, each time series is updated in real time, and the predicted value of the door closing state is updated in real time; if the predicted values ​​of the door closing state for R consecutive times are all fully open or half open, the access control result is that the automatic door closing fails;

[0051] If the predicted value of the door closing state jumps to closed and does not change, the access control result is that the automatic door closing is successful; if the predicted value of the door closing state jumps to closed and then jumps to fully open or half open again, the access control result is that the automatic door closing fails.

[0052] As a preferred solution of the base station companion remote access control and control system described in this application, wherein: the data acquisition module includes a current detection unit and a photoelectric detection unit;

[0053] The current detection unit is used to collect the working current of the electronic lock of the base station companion; the working current is the working current of the driving circuit of the electronic lock;

[0054] The photoelectric detection unit is used to collect the photoelectric switch signal of the base station partner; the photoelectric switch signal is an analog signal output by the photoelectric switch.

[0055] Compared with the prior art, the beneficial effects achieved by this application are as follows:

[0056] This application combines the electronic lock's operating current and the photoelectric switch signal to construct a state transfer chain, distinguishing between normal operation and abnormal states. This overcomes the defect of a single sensor being susceptible to interference, significantly reduces the misjudgment rate, and saves troubleshooting time and labor costs. By cross-validating the electronic lock's current state and the photoelectric signal slope, it distinguishes between recoverable and permanent anomalies, avoiding excessive intervention while achieving timely early warning of critical anomalies. This application predicts changes in the door closing state during the closing process, predicting whether it will be successfully closed or possibly stuck, optimizing the reliability of remote operation, reducing ineffective operations and equipment loss, and reducing the frequency of manual inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be derived from these drawings without inventive effort. Among them:

[0058] Figure 1 A schematic diagram of the structure of the base station companion remote access management and control system provided for this application;

[0059] Figure 2 This is a flow chart of the method for predicting the access control status at the next moment provided in this application. DETAILED DESCRIPTION

[0060] The technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. Unless there is a conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0061] A base station companion is a related device or system that is used in conjunction with communication base station equipment to provide support and guarantee for the operation of the base station. Taking the intelligent power cabinet as an example, it plays a key role in the operation and maintenance of 5G base stations. It can serve as a backup power supply to provide continuous power support for base station equipment, ensure the normal operation of the base station, and ensure the continuity and reliability of the communication network. It is a typical base station companion. This embodiment uses the intelligent power cabinet supporting the 5G base station as the preferred base station companion and provides it with management and control means. The intelligent power cabinet has intelligent monitoring and management functions, can realize remote network management, and supports working parameter collection and intelligent alarms. The intelligent power cabinet is equipped with an electronic lock and a photoelectric switch. The electronic lock can be remotely controlled to achieve automatic locking, and the photoelectric switch is used to detect the access switch status of the intelligent power cabinet.

[0062] This embodiment introduces a base station companion remote access control and management system. Figure 1 The system includes a data acquisition module, a feature extraction module, a state recognition module, and an access control module; wherein:

[0063] The data acquisition module is used to collect the working current and photoelectric switch signal of the electronic lock;

[0064] The data acquisition module includes a current detection unit and a photoelectric detection unit;

[0065] The current detection unit is used to collect the working current of the electronic lock of the base station companion; the working current is the working current of the driving circuit of the electronic lock; in this embodiment, the current detection unit preferably includes a high-precision current sensor connected in series in the driving circuit of the electronic lock, which collects the working current of the electronic lock in real time at a sampling frequency of 100Hz, including working current data in different working states such as locked and standby.

[0066] The photoelectric detection unit is used to collect the photoelectric switch signal of the base station companion; the photoelectric switch signal is an analog signal output by the photoelectric switch. The base station companion in this embodiment, that is, the intelligent power supply cabinet, is equipped with a beam-type photoelectric switch, including a transmitter and a receiver; the transmitter is installed on one side of the door frame and continuously emits an infrared beam; the receiver is installed on the edge of the door leaf or the other side of the door frame, aligned with the transmitter, to ensure that the beam can directly illuminate the receiver when the door is closed. The receiver continuously receives the light beam emitted by the transmitter and converts the intensity of the received light beam into an analog signal. The preferred photoelectric detection unit of this embodiment includes a 16-bit ADC chip, which samples the analog signal output by the photoelectric switch to obtain the intensity value of the photoelectric switch signal.

[0067] The feature extraction module extracts access control feature data of the base station companion based on the working current and the photoelectric switch signal;

[0068] The feature extraction module includes a feature extraction unit and a data sorting unit;

[0069] The feature extraction unit is used to extract access control feature data of the base station companion; the access control feature data includes statistical features of the working current, frequency features and trend features of the photoelectric switch signal;

[0070] In this embodiment, the statistical characteristics of the operating current preferably include the mean, variance, maximum, minimum, kurtosis, and skewness of the operating current. Time windows are set, and each statistical characteristic is extracted for the operating current in each time window. The statistical characteristics of the operating current can be used to distinguish between different operating states of the electronic lock, such as standby, unlocked, and locked. They can also be used to assess the degree of current fluctuation; abnormal current fluctuations indicate an operational anomaly in the electronic lock.

[0071] In this embodiment, the frequency characteristics of the photoelectric switch signal preferably include the dominant frequency and frequency band energy distribution of the photoelectric switch signal. During normal door opening and closing, the dominant frequency of the photoelectric switch signal is correlated with the door's movement speed. For example, a uniform door opening speed corresponds to a single low-frequency component. Abnormal door vibration generates a high-frequency component. High low-frequency energy indicates normal door movement or slight vibration.

[0072] The feature extraction unit extracts the trend characteristics of the photoelectric switch signal through curve fitting, specifically including: reading the photoelectric switch signal at each moment, performing curve fitting on the photoelectric switch signal, and obtaining the curve equation of the photoelectric switch signal; setting a time window, and calculating the trend characteristics of the photoelectric switch signal in each time window based on the curve equation, wherein the trend characteristics include slope and intercept. In this embodiment, the least squares method is preferably used to perform segmented curve fitting on the photoelectric switch signal. The trend characteristics of the photoelectric switch signal are related to the door speed. Combined with the timing of the electronic lock action reflected by the statistical characteristics of the electronic lock, the rationality of the access control state conversion can be verified, such as the corresponding slope change after the unlocking instruction.

[0073] The data sorting unit is used to sort the access control feature data and construct an access control feature sequence, specifically including: standardizing each access control feature data separately; time aligning each access control feature data; encoding each access control feature data at the same time and splicing it into an access control feature sequence at the corresponding time.

[0074] The state recognition module constructs a state transition chain of the access control based on the access control feature data, and detects abnormal states of the access control based on the state transition chain; when an abnormal state occurs in the access control, the state recognition module identifies the abnormal type of the abnormal state;

[0075] The state recognition module includes a state detection unit and an abnormality recognition unit;

[0076] The state detection unit is used to build a state transfer chain for access control;

[0077] The state detection unit is configured with a state classification model; the state detection unit identifies the access control state based on the state classification model; the input of the state classification model is the access control feature sequence at any time, and the output is the identification result of the access control state at the corresponding time; in this embodiment, a trained support vector machine classifier is preferably used as the state classification model; the access control state includes a normal working state and an abnormal working state; the normal working state includes stable door closing, door opening response, door opening execution, door opening intervention, maintenance stop, door closing response, door closing execution, and door closing intervention;

[0078] Stable door closing means that the door is completely closed and locked; door opening response means that the electronic lock has received the door opening command and is ready to unlock. At this time, the working current is a short current pulse; door opening execution means that the door is automatically opened after the electronic lock is unlocked. At this time, the slope of the photoelectric switch signal changes with the door speed, and the working current is maintained at the unlocked state current; door opening intervention means manual assistance is used to open the door. At this time, the photoelectric switch signal has low-frequency vibration, such as the main frequency of 2-5Hz, which corresponds to the influence of manual operation; maintenance stay means that the door remains fully open and the electronic lock is on standby; door closing response means that the electronic lock has received the door closing command and is ready to close automatically; door closing execution means that the electronic lock drives the automatic door closing; door closing intervention means manual assistance is used to close the door;

[0079] In this embodiment, the preferred abnormal working states include half-closed jamming, external force obstruction, and access control damage; half-closed jamming means that the door is not completely closed but the electronic lock is locked, and at this time the photoelectric switch signal strength is between the strength during stable door closing and maintenance stop; external force obstruction means that the photoelectric switch is blocked or the door closing is obstructed due to non-door movement, such as foreign object coverage; access control damage indicates electronic lock or photoelectric switch hardware failure, such as motor jamming, sensor failure, etc.

[0080] The state detection unit is also equipped with a state transition model to predict the access control state at the next moment; Figure 2 ,The state detection unit predicts the access control state at the next moment as follows:

[0081] Discretize and encode the access control feature sequence at each moment in the last N minutes to obtain the observation value at each moment; N is a positive integer;

[0082] The discretization encoding method is as follows: for any access control feature sequence, the continuous value of each access control feature data is mapped to different intervals, and a discrete symbol is assigned to each interval; the discrete symbols corresponding to each access control feature data are combined into the observation value of the corresponding access control feature sequence;

[0083] The observation value at each moment is input into the state transition model; the state transition model calculates and outputs the transition probability of each access control state at the next moment; and the access control state with the highest transition probability is extracted as the alternative access control state;

[0084] The state detection unit is also configured with a transition probability threshold. If the transition probability of the candidate access state is greater than the transition probability threshold, the access state at the next moment is the candidate access state; otherwise, the access state at the next moment is the current access state. The transition probability threshold is set by those skilled in the art based on actual needs, for example, 0.7.

[0085] In this embodiment, the state transition model is preferably a trained hidden Markov model; the hidden Markov model is configured with a trained state transition matrix, an observation probability matrix, and an initial state distribution; wherein the state transition matrix is ​​used to describe the transition pattern between access control states, wherein any element represents the transition probability of the access control state corresponding to the row to the access control state corresponding to the column; the observation probability matrix is ​​used to describe the correlation between access control states and observation values, wherein any element in the row corresponds to an access control state, and in the column corresponds to an observation value, and the element value represents the probability of the observation value occurring under the access control state; the initial state distribution represents the probability distribution of each access control state at the initial moment. Based on the trained state transition matrix, observation probability matrix, initial state distribution, and the observation value at each input moment, the hidden Markov model iteratively calculates the probability distribution of each access control state at the next moment through a built-in forward algorithm.

[0086] The state detection unit composes the access control state at each moment in the last N minutes and the predicted access control state at the next moment into the state transfer chain in chronological order, and records the duration of each access control state in the state transfer chain.

[0087] The state detection unit is further configured to detect abnormal states of the access control system according to the state transition chain, specifically including:

[0088] If the access control status in the state transfer chain includes an abnormal working state, then the access control is in an abnormal state;

[0089] The state detection unit is also configured with a reference state chain; any reference state chain includes a sequence of different access control states in the order of transition when the access control does not have an abnormal state, and marks the duration threshold interval of each access control state; the abnormal state detection of the access control also includes:

[0090] A state transition sequence is extracted from the state transition chain; the state transition sequence is a sequence of different access control states in the state transition chain in a transfer order, and the duration of each access control state is marked; in this embodiment, since the state transition chain is the access control state corresponding to each moment, adjacent moments may correspond to the same access control state, adjacent and similar access control states are merged, and the duration of each access control state is calculated (the duration is the duration corresponding to the merged moment), which can facilitate matching with the reference state chain.

[0091] If any reference state chain includes a segment that corresponds one-to-one to the access control state in the state transition sequence, the segment is marked as a reference state sequence;

[0092] If there is at least one reference state sequence such that the duration of each access control state in the state transition sequence is within the duration threshold interval of the corresponding access control state in the reference state sequence, then the access control is not in an abnormal state; otherwise, the access control is in an abnormal state.

[0093] A preferred reference state chain of this embodiment corresponds to a maintenance inspection of a base station companion, specifically as follows: the access control state and the marked time threshold intervals are door opening response, 0.5 seconds to 2 seconds; door opening execution, 3 seconds to 8 seconds; maintenance stay, 0 to 60 minutes; door closing response, 0.5 seconds to 2 seconds; door closing execution, 3 seconds to 8 seconds; stable door closing, 0 to infinity.

[0094] The abnormality identification unit is used to identify the abnormality type of the abnormal state of the access control; the abnormality type includes permanent abnormality and recoverable abnormality;

[0095] The abnormality identification unit identifies the abnormality type of the access control based on the access control feature data, specifically including:

[0096] Based on the statistical characteristics of the working current, the state of the electronic lock is identified; the state of the electronic lock includes a standby state, a locked response state, a locked execution state, and an abnormal state; the preferred method of identifying the state of the electronic lock in this embodiment is as follows: the abnormal identification unit is configured with an identification strategy for the electronic lock state, which is used to identify its state based on the statistical characteristics of the working current. For example, the standby state is when the electronic lock has not received a locking instruction, and the working current is stable in a low power consumption range, such as less than 50mA; the locked response state is when the electronic lock receives a locking instruction, and the current has a short rising pulse, such as from 50mA to 200mA, which lasts for 0.5 seconds; the locked execution state is when the electronic lock executes the locking instruction, and the current is maintained at a high level, such as 150mA, until the door is completely closed; the abnormal state is when the working current continues to fluctuate abnormally or exceeds the normal working range, for example, it is continuously greater than 300mA.

[0097] The slope of the photoelectric switch signal is divided into different slope intervals; the slope intervals include a slowly changing interval, a rapidly changing interval, and an abnormal fluctuation interval; in this embodiment, the slope of the photoelectric switch signal is preferably divided into different slope intervals in the following manner: the curve equation of the photoelectric switch signal is sampled to obtain the slope value at each moment; the abnormality identification unit is configured with a mutation number threshold and a slope threshold; the slope value is intercepted by a sliding window, and the number of slope polarity reversals (i.e., the number of positive and negative changes) in each sliding window is calculated as the number of mutations; the average slope in each sliding window is calculated; if the number of mutations in any sliding window is greater than the mutation number threshold, the slope interval corresponding to the sliding window is an abnormal fluctuation interval; otherwise, it is determined whether the average slope is greater than the slope threshold; if so, the slope interval corresponding to the sliding window is a rapidly changing interval; otherwise, the slope interval corresponding to the sliding window is a slowly changing interval. In the slow-changing range, the photoelectric signal intensity changes slowly over time, there is obvious obstruction resistance, and automatic door closing is significantly hindered; in the rapid-changing range, the photoelectric switch signal intensity changes significantly, corresponding to the door closing situation without obstruction or with weak obstruction resistance; in the abnormal fluctuation range, the photoelectric switch signal intensity changes suddenly multiple times, which is caused by abnormal conditions such as foreign objects covering the photoelectric switch or blocking the door body.

[0098] Identifying permanent access control anomalies based on the state and slope interval of the electronic lock specifically includes:

[0099] If the electronic lock is in the locked execution state and the slope of the photoelectric switch signal is always in the slow change range for at least n seconds, the abnormality type is permanent abnormality;

[0100] If the electronic lock state passes through the lock response state, lock execution state, and standby state in sequence within m seconds, and the intensity value of the photoelectric switch signal is lower than the preset intensity threshold, the abnormality type is permanent abnormality;

[0101] If the electronic lock is in an abnormal state, or the slope of the photoelectric signal is in an abnormal fluctuation range, the abnormality type is permanent abnormality.

[0102] Identifying recoverable access control anomalies based on the state and slope interval of the electronic lock specifically includes:

[0103] If the electronic lock is in the locked execution state, and the photoelectric signal slope is always in the fast change range, or transitions from the slow change range to the fast change range for at least n seconds, the abnormality type is recoverable abnormality;

[0104] If the electronic lock is in standby state and has not experienced the lock response state or lock execution state within m seconds, and the slope of the photoelectric switch signal is not in the abnormal fluctuation range or the rapid change range, the abnormality type is a recoverable abnormality.

[0105] The access control module performs access control on the base station companion based on the abnormality type and predicts the access control result; the access control module triggers an access abnormality alarm based on the abnormality type and the access control result.

[0106] The access control module includes a control unit and a prediction unit;

[0107] The control unit is used to perform access control on the base station companion according to the access control exception type, specifically including: if the access control exception type is a recoverable exception, sending an access control instruction to the base station companion to control the base station companion to automatically close and lock the door;

[0108] The prediction unit is used to predict the access control result; the prediction unit is configured with a state prediction model; the prediction unit predicts the door closing state at each time step after the base station partner responds to the access control instruction based on the state prediction model, specifically including:

[0109] Each statistical feature of the electronic lock's operating current, as well as the intensity and slope of the photoelectric switch signal, are organized into corresponding time series. Each time series is input into a state prediction model, which predicts the door closing state for the next M time steps. The door closing states include fully open, half open, and closed, where M is a positive integer.

[0110] The state prediction model is an LSTM model. It calculates the probability distribution of the door closing state at each future time step based on the time series of input access control feature data and maps this probability distribution to a specific state label. The LSTM model can predict nonlinear changes in door movement, such as door jamming and rebound, and learn the statistical characteristics of the operating current and the long-term dependency of the photoelectric switch signal, improving the recognition accuracy of complex door movement patterns (such as intermittent door jamming after occlusion).

[0111] The prediction unit further determines the access control result based on the predicted door closing state, specifically including:

[0112] During the process of the base station companion automatically closing the door, each time series is updated in real time, and the predicted value of the door closing state is updated in real time; if the predicted values ​​of the door closing state for R consecutive times are all fully open or half open, the access control result is that the automatic door closing fails;

[0113] If the predicted value of the door closing state jumps to closed and does not change, the access control result is that the automatic door closing is successful; if the predicted value of the door closing state jumps to closed and then jumps to fully open or half open again, the access control result is that the automatic door closing fails.

[0114] The prediction unit is also used to trigger an abnormality alarm based on the access control abnormality type and access control result, specifically including: if the access control abnormality type is a permanent abnormality or the access control result is an automatic door closing failure, an abnormality alarm is sent to the management end.

[0115] This embodiment cross-verifies the slope change of the photoelectric switch output signal with the electronic lock status to distinguish between recoverable anomalies (such as temporary obstructions such as dust and snow) and permanent anomalies (such as permanent obstructions by foreign objects that cannot be automatically recovered). Remote control is only performed for recoverable anomalies, automatically closing and locking the door, and the access control result of remote door closing is predicted in real time to prevent damage to the equipment caused by forced door closing in an obstructed state.

[0116] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] The above describes the embodiments of the present application in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose and scope of protection of this application, all of which are protected by this application.

Claims

1. Base station companion remote access management and control system, characterized by: It includes data acquisition module, feature extraction module, state recognition module and access control module; among which: The data acquisition module is used to collect the working current and photoelectric switch signal of the electronic lock; The feature extraction module extracts access control feature data of the base station companion based on the working current and the photoelectric switch signal; The state recognition module constructs a state transition chain of the access control based on the access control feature data, and detects abnormal states of the access control based on the state transition chain; when an abnormal state occurs in the access control, the state recognition module identifies the abnormal type of the abnormal state; The state recognition module includes a state detection unit; the state detection unit is used to build a state transfer chain for access control, specifically including: Based on the access control feature sequence at each moment, the access control status at each moment is identified, and the access control status at the next moment is predicted; the access control status includes normal working status and abnormal working status; the access control status at each moment in the last N minutes and the predicted access control status at the next moment are combined into the state transition chain in chronological order, and the duration of each access control status in the state transition chain is recorded; The state detection unit is further configured to detect abnormal states of the access control system according to the state transition chain, specifically including: If the access control status in the state transfer chain includes an abnormal working state, then the access control is in an abnormal state; The state detection unit is also configured with a reference state chain; any reference state chain includes a sequence of different access control states in the order of transition when the access control does not have an abnormal state, and marks the duration threshold interval of each access control state; the abnormal state detection of the access control also includes: Extracting a state transition sequence from the state transition chain; the state transition sequence is a sequence of different access control states in the state transition chain in a transition order, and marking the duration of each access control state; If any reference state chain includes a segment that corresponds one-to-one to the access control state in the state transition sequence, the segment is marked as a reference state sequence; If there is at least one reference state sequence such that the duration of each access control state in the state transition sequence is within the duration threshold interval of the corresponding access control state in the reference state sequence, then the access control is not in an abnormal state; otherwise, the access control is in an abnormal state; The access control module performs access control on the base station companion based on the abnormality type and predicts the access control result; the access control module triggers an access abnormality alarm based on the abnormality type and the access control result.

2. The base station companion remote access management and control system according to claim 1, characterized in that: The feature extraction module includes a feature extraction unit and a data sorting unit; The feature extraction unit is used to extract access control feature data of the base station companion; the access control feature data includes statistical features of the working current, frequency features and trend features of the photoelectric switch signal; The feature extraction unit extracts the trend feature of the photoelectric switch signal by curve fitting, specifically comprising: reading the photoelectric switch signal at each moment, and performing curve fitting on the photoelectric switch signal to obtain a curve equation of the photoelectric switch signal; setting a time window, and calculating the trend feature of the photoelectric switch signal in each time window based on the curve equation, wherein the trend feature includes a slope and an intercept; The data sorting unit is used to sort the access control feature data and construct an access control feature sequence, specifically including: standardizing each access control feature data separately; time aligning each access control feature data; encoding each access control feature data at the same time and splicing it into an access control feature sequence at the corresponding time.

3. The base station companion remote access management and control system according to claim 2, characterized in that: The state detection unit is configured with a state classification model; the state detection unit identifies the access control state based on the state classification model; the input of the state classification model is the access control feature sequence at any time, and the output is the identification result of the access control state at the corresponding time; the state detection unit is also configured with a state transition model for predicting the next access control state.

4. The base station companion remote access management and control system according to claim 3, characterized in that: The state detection unit predicts the access control state at the next moment as follows: Discretize and encode the access control feature sequence at each moment in the last N minutes to obtain the observation value at each moment; N is a positive integer; The observation value at each moment is input into the state transition model; the state transition model calculates and outputs the transition probability of each access control state at the next moment; and the access control state with the highest transition probability is extracted as the alternative access control state; The state detection unit is further configured with a transition probability threshold; if the transition probability of the candidate access control state is greater than the transition probability threshold, the access control state at the next moment is the candidate access control state; otherwise, the access control state at the next moment is the current access control state.

5. The base station companion remote access management and control system according to claim 4, characterized in that: The state recognition module further includes an abnormality recognition unit; the abnormality recognition unit is used to identify the abnormal type of the abnormal state of the access control, specifically including: Based on the statistical characteristics of the working current, the state of the electronic lock is identified; the state of the electronic lock includes a standby state, a lock response state, a lock execution state, and an abnormal state; Dividing the slope of the photoelectric switch signal into different slope intervals; the slope intervals include a slow change interval, a fast change interval, and an abnormal fluctuation interval; The abnormality type includes a permanent abnormality; the abnormality identification unit identifies the permanent abnormality of the access control based on the state and slope interval of the electronic lock, specifically including: If the electronic lock is in the locked execution state and the slope of the photoelectric switch signal is always in the slow change range for at least n seconds, the abnormality type is permanent abnormality; If the electronic lock passes through the lock response state, lock execution state, and standby state in sequence within m seconds, and the intensity value of the photoelectric switch signal is lower than the preset intensity threshold, the abnormality type is permanent abnormality; If the electronic lock is in an abnormal state, or the slope of the photoelectric signal is in an abnormal fluctuation range, the abnormality type is permanent abnormality.

6. The base station companion remote access management and control system according to claim 5, characterized in that: The abnormality type also includes permanent abnormality and recoverable abnormality; the abnormality identification unit further identifies the recoverable abnormality of the access control based on the state and slope interval of the electronic lock, specifically including: If the electronic lock is in the locked execution state, and the photoelectric signal slope is always in the fast change range, or transitions from the slow change range to the fast change range for at least n seconds, the abnormality type is recoverable abnormality; If the electronic lock is in standby state and has not experienced the lock response state or lock execution state within m seconds, and the slope of the photoelectric switch signal is not in the abnormal fluctuation range or the rapid change range, the abnormality type is a recoverable abnormality.

7. The base station companion remote access management and control system according to claim 6, characterized in that: The access control module includes a control unit and a prediction unit; The control unit is used to perform access control on the base station companion according to the access control exception type, specifically including: if the access control exception type is a recoverable exception, sending an access control instruction to the base station companion to control the base station companion to automatically close and lock the door; The prediction unit is used to predict the access control result; the access control result includes automatic door closing failure and automatic door closing success; The prediction unit is also used to trigger an abnormality alarm based on the access control abnormality type and access control result, specifically including: if the access control abnormality type is a permanent abnormality or the access control result is an automatic door closing failure, an abnormality alarm is sent to the management end.

8. The base station companion remote access management and control system according to claim 7, characterized in that: The prediction unit is configured with a state prediction model; the prediction unit predicts the door closing state at each time step after the base station companion responds to the access control instruction based on the state prediction model, specifically including: Each statistical feature of the electronic lock's operating current and the intensity and slope of the photoelectric switch signal are organized into corresponding time series. Each time series is input into a state prediction model, which predicts the door closing state in the next M time steps. The door closing state includes fully open, half open, and closed. The prediction unit determines the access control result based on the predicted door closing state, specifically including: During the process of the base station companion automatically closing the door, each time series is updated in real time, and the predicted value of the door closing state is updated in real time; if the predicted values ​​of the door closing state for R consecutive times are all fully open or half open, the access control result is that the automatic door closing fails; If the predicted value of the door closing state jumps to closed and does not change, the access control result is that the automatic door closing is successful; if the predicted value of the door closing state jumps to closed and then jumps to fully open or half open again, the access control result is that the automatic door closing fails.

9. The base station companion remote access management and control system according to claim 8, characterized in that: The data acquisition module includes a current detection unit and a photoelectric detection unit; The current detection unit is used to collect the working current of the electronic lock of the base station companion; the working current is the working current of the driving circuit of the electronic lock; The photoelectric detection unit is used to collect the photoelectric switch signal of the base station partner; the photoelectric switch signal is an analog signal output by the photoelectric switch.

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