CN121049718B - Remote monitoring-based full life cycle detection method for operating state of circuit breaker - Google Patents
Remote monitoring-based full life cycle detection method for operating state of circuit breakerInfo
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Abstract
本发明公开了一种基于远程监控的断路器运行状态全生命周期检测方法，涉及电力设备监测技术领域，包括：获取断路器控制装置记录的控制指令数据与多通道状态监测数据，所述多通道状态监测数据包括电流通道数据、电压通道数据与振动通道数据；基于控制指令数据中的时间戳构建滑动对齐窗口，并通过所述滑动对齐窗口截取多通道状态监测数据，生成通道响应片段；基于通道响应片段中各通道的响应起始时间点构建跨通道响应时差数据；本发明通过融合控制指令数据与多通道状态监测数据构建操作响应映射链，实现对断路器控制动作与多通道响应的因果耦合解析及异常演化追踪，从而完成断路器运行状态全生命周期的精确检测。
This invention discloses a method for detecting the entire lifecycle of circuit breaker operating status based on remote monitoring, relating to the field of power equipment monitoring technology. The method includes: acquiring control command data and multi-channel status monitoring data recorded by the circuit breaker control device, wherein the multi-channel status monitoring data includes current channel data, voltage channel data, and vibration channel data; constructing a sliding alignment window based on the timestamps in the control command data, and extracting multi-channel status monitoring data through the sliding alignment window to generate channel response segments; constructing cross-channel response time difference data based on the response start time points of each channel in the channel response segments; this invention constructs an operation response mapping chain by fusing control command data and multi-channel status monitoring data, realizing causal coupling analysis and anomaly evolution tracking of circuit breaker control actions and multi-channel responses, thereby achieving accurate detection of the entire lifecycle of circuit breaker operating status.
Description
Technical Field
The invention relates to the technical field of power equipment monitoring, in particular to a breaker running state full life cycle detection method based on remote monitoring.
Background
In a power distribution network operation scene, a breaker is used as key switch equipment, the change of the operation state of the breaker directly influences the safety and stability of a power grid, in order to ensure the long-term stable operation of the breaker, the conventional method generally carries out periodic sampling monitoring on the operation state of the breaker by installing a single type of sensor and carries out empirical evaluation on the operation state by combining with periodic maintenance records, and the method can assist in judging fault risks after the breaker has larger performance degradation, but cannot cover multichannel dynamic response behaviors under the triggering of control actions in the operation process, so that synchronous perception and joint analysis on the multisource state of the breaker cannot be realized in the early stage of operation;
Meanwhile, the existing method generally takes single-channel monitoring data as an independent sample to carry out thresholding judgment or trend fitting analysis, can give an alarm prompt when the degree of abnormality is higher, but lacks a causal coupling verification mechanism between control actions and physical responses, cannot evaluate the matching relationship between the instructions and the responses based on the combined result of control instruction data and multi-channel state monitoring data, is difficult to accurately judge the correspondence between the operation actions and state changes of the circuit breaker in the early stage of abnormality, and limits the causal judgment capability of the running state;
In addition, the existing method presumes the life stage of the breaker by relying on a history maintenance record, and can provide staged risk assessment after the equipment runs for a long time, but can not continuously track the abnormal interruption condition in the response process of operation in the actual running process, and lacks the capability of dynamically recording the closed state of a control action and channel response causal link, so that the trend change of the state evolution of the breaker is difficult to judge, therefore, a detection method capable of fusing control instruction data and multichannel state monitoring data and realizing causal verification and abnormal evolution identification is needed to realize the dynamic detection and state stage judgment of the whole life cycle of the running state of the breaker.
Disclosure of Invention
In order to solve the technical problems, the invention provides a breaker running state full life cycle detection method based on remote monitoring.
A circuit breaker operating state full life cycle detection method based on remote monitoring, the method comprising:
S11, acquiring control instruction data and multichannel state monitoring data recorded by a circuit breaker control device, wherein the multichannel state monitoring data comprise current channel data, voltage channel data and vibration channel data;
S12, constructing a sliding alignment window based on a time stamp in the control instruction data, intercepting multi-channel state monitoring data through the sliding alignment window, and generating a channel response segment;
S13, constructing cross-channel response time difference data based on response starting time points of all channels in the channel response fragments, and inputting the response time difference data into a delay correction model to generate a delay alignment label;
s14, screening channel response fragments meeting response synchronism through the delay alignment labels, and calculating a matching value based on the control instruction data and the channel response fragments to generate a cause and effect verification label;
s15, constructing an operation response mapping chain based on the causal verification tags arranged in time sequence, and generating state evolution mark data according to continuous non-closed loop events in the mapping chain.
Further, the step of acquiring the multichannel state monitoring data comprises the following steps:
s111, acquiring current channel data according to a preset sampling time interval through a current sensor on a main circuit of the circuit breaker;
s112, acquiring voltage channel data according to a preset sampling time interval through voltage sensors on an incoming line side and an outgoing line side of the circuit breaker;
S113, acquiring vibration channel data according to a preset sampling time interval through a triaxial vibration acceleration sensor arranged on a circuit breaker shell;
And S114, executing time sequence integration processing according to the sampling time stamps of the current channel data, the voltage channel data and the vibration channel data to generate multi-channel state monitoring data.
Further, the step of integrating the current channel data, the voltage channel data and the vibration channel data is as follows:
S114.1, extracting sampling time stamp fields of current channel data, voltage channel data and vibration channel data;
S114.2, constructing a time index list according to all the sampling time stamp fields;
s114.3, synchronous resampling is carried out on the current channel data, the voltage channel data and the vibration channel data based on the time index list;
And S114.4, outputting the synchronous resampling result as multi-channel state monitoring data.
Further, the step of S12 is:
s121, calculating adjacent time stamp intervals according to time stamp fields in control instruction data;
S122, generating a sliding alignment window boundary based on the adjacent time stamp interval and the set sliding step length;
S123, intercepting multi-channel state monitoring data through sliding the alignment window boundary to obtain a channel response segment.
Further, the step of generating the channel response segment is:
s123.1, extracting the starting time and the ending time of each sliding alignment window;
s123.2, intercepting multichannel state monitoring data in a window range according to the starting time and the ending time;
s123.3, arranging the intercepted multi-channel state monitoring data in ascending order according to the time stamp;
And S123.4, outputting the multi-channel state monitoring data with the time stamps arranged in an ascending order as channel response fragments.
Further, the step of constructing the cross-channel response time difference data comprises the following steps:
S131, extracting response starting time points of current channel data, voltage channel data and vibration channel data in the channel response segment;
s132, calculating a response starting time difference value between each pair of channels;
s133, combining response initial time differences among all channel pairs into cross-channel response time difference data;
s134, inputting the cross-channel response time difference data into the delay correction model to generate a delay alignment label.
Further, the step of generating cross-channel response time difference data comprises the following steps:
s133.1, performing difference calculation on response starting time points of the current channel data and the voltage channel data to obtain a current voltage starting time difference value;
S133.2, performing difference calculation on response starting time points of the current channel data and the vibration channel data to obtain a current vibration starting time difference value;
s133.3, performing difference calculation on response starting time points of the voltage channel data and the vibration channel data to obtain a voltage vibration starting time difference;
and S133.4, summarizing the current voltage starting time difference value, the current vibration starting time difference value and the voltage vibration starting time difference value into cross-channel response time difference data.
Further, the step of generating a cause and effect verification tag is:
s141, screening out channel response fragments with response starting time difference values lower than a set synchronization threshold value based on the delay alignment labels;
S142, extracting control instruction data corresponding to the synchronous channel response segment;
s143, performing matching value calculation based on the time interval and the amplitude variation of the control instruction data and the channel response segment;
s144, marking the channel response fragments with the matching values exceeding the set threshold as causal verification tags.
Further, the step of calculating the matching value is:
S143.1, extracting an action type field and a time stamp field in control instruction data;
s143.2, extracting response amplitude values and response starting time points in the channel response fragments;
S143.3, performing difference calculation on the timestamp field of the control instruction data and the response starting time point of the channel response segment to obtain a time interval value;
And S143.4, taking the time interval value and the response amplitude value as joint input, and calculating to obtain a matching value.
Further, the step of generating state evolution marking data according to continuous non-closed loop events in the mapping chain comprises the following steps:
s151, carrying out adjacent pairing connection on the causal verification tags arranged in time sequence to generate a mapping chain unit;
S152, performing time sequence splicing processing based on all the mapping chain units, and constructing an operation response mapping chain;
s153, detecting whether a mapping chain unit with an unclosed end node exists in the operation response mapping chain;
s154, marking continuous non-closed-loop mapping chain units as state evolution marking data;
The logic of the marker state evolution marker data is:
S154.1, extracting the starting nodes and the ending nodes of all mapping chain units in the operation response mapping chain;
S154.2, screening out mapping chain units which are not present in any starting node of the ending node;
s154.3, performing aggregation index processing on adjacent non-closed-loop mapping chain units which are continuous in time;
And S154.4, outputting the non-closed-loop mapping chain unit after the aggregation index processing as state evolution marking data.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, the channel response fragments are constructed based on the control instruction data and the multi-channel state monitoring data, so that the synchronization and response characteristics of each physical channel after the circuit breaker executes the action can be subjected to joint analysis under a remote monitoring environment, so that the real response process caused by the control action in different channels is obtained, the multi-source state sensing capability of the circuit breaker in the operation process is further improved, and the acquisition coverage range of the operation state is expanded;
In addition, the invention screens out the channel response fragments with higher response synchronism according to the cross-channel response time difference data and the delay alignment labels obtained by calculating the channel response fragments, and then combines the corresponding control instruction data to calculate the matching value and marks the matching value as a causal verification label, so that the causal coupling degree between the control action and the channel response can be identified in two dimensions of time and amplitude, the resolution precision of the corresponding relation between the operation action and the state change of the circuit breaker is further improved, and the causal judgment capability of the running state is further enhanced;
Further, the invention constructs the operation response mapping chain based on the causal verification tag and extracts the continuous unclosed mapping chain unit mark as the state evolution marking data, so that the concentration degree and the evolution trend of the abnormal event can be identified according to the distribution characteristics of the state evolution marking data in time, and the state evolution stage from operation, stable operation to degradation failure of the circuit breaker can be further judged, thereby improving the evolution detection capability of the whole life cycle of the running state of the circuit breaker;
In summary, the invention constructs the operation response mapping chain by fusing the control instruction data and the multichannel state monitoring data, and realizes causal coupling analysis and abnormal evolution tracking of the control actions and multichannel responses of the circuit breaker, thereby completing the accurate detection of the full life cycle of the running state of the circuit breaker.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for those skilled in the art.
Fig. 1 is a flowchart of a method for detecting a full life cycle of a circuit breaker operating state based on remote monitoring according to embodiment 1 of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Referring to fig. 1, the disclosure of the present embodiment provides a method for detecting a full life cycle of a circuit breaker operating state based on remote monitoring, where the method includes:
S11, acquiring control instruction data and multichannel state monitoring data recorded by a circuit breaker control device, wherein the multichannel state monitoring data comprise current channel data, voltage channel data and vibration channel data;
specifically, the step of acquiring the multichannel state monitoring data includes:
s111, acquiring current channel data according to a preset sampling time interval through a current sensor on a main circuit of the circuit breaker;
in a specific embodiment, a Hall current sensor is installed on a main circuit of the circuit breaker, and a sampling time interval is set;
the current sensor collects instantaneous current amplitude values at each sampling time interval, synchronously records sampling time stamps, and takes records formed by all the sampling time stamps and the corresponding current amplitude values as current channel data;
s112, acquiring voltage channel data according to a preset sampling time interval through voltage sensors on an incoming line side and an outgoing line side of the circuit breaker;
In a specific embodiment, a voltage sensor is respectively arranged on the incoming line side and the outgoing line side of the circuit breaker, and a sampling time interval is set;
The voltage sensor synchronously collects an incoming line voltage value and an outgoing line voltage value at each sampling time interval, records corresponding sampling time stamps, and takes records formed by the incoming line voltage value, the outgoing line voltage value and the sampling time stamps as voltage channel data;
S113, acquiring vibration channel data according to a preset sampling time interval through a triaxial vibration acceleration sensor arranged on a circuit breaker shell;
In a specific embodiment, a triaxial vibration acceleration sensor is fixedly arranged on the outer surface of a circuit breaker shell, and sampling time intervals are set;
The vibration acceleration sensor collects the instantaneous acceleration vector of the triaxial direction at each sampling time interval, records the corresponding sampling time stamp, and takes the record formed by the triaxial acceleration vector and the sampling time stamp as vibration channel data;
And S114, executing time sequence integration processing according to the sampling time stamps of the current channel data, the voltage channel data and the vibration channel data to generate multi-channel state monitoring data.
In one particular embodiment, three types of channel data are integrated to ensure time synchronicity;
The integration process builds a unified time index by extracting sampling time stamps of three types of channel data, resamples various channel data according to the time index, and combines current, voltage and vibration data at the same time point into a synchronous record so as to form multi-channel state monitoring data;
Specifically, the step of integrating the current channel data, the voltage channel data and the vibration channel data is as follows:
S114.1, extracting sampling time stamp fields of current channel data, voltage channel data and vibration channel data;
in a specific embodiment, the time stamps recorded in the three types of channel data are read one by one;
it should be noted that the extraction result is a set of timestamp fields containing all timestamps.
S114.2, constructing a time index list according to all the sampling time stamp fields;
In a particular embodiment, all timestamps within a set of timestamp fields are arranged in ascending order of time;
It should be noted that the ascending order arrangement result is used for subsequent data alignment, and the time points in the time index list are divided at equal intervals;
s114.3, synchronous resampling is carried out on the current channel data, the voltage channel data and the vibration channel data based on the time index list;
Searching the record with the closest time in the three types of channel data according to each index time point in the time index list;
when the index time point does not appear in the original record, the numerical values of the corresponding channels are complemented by adopting a linear interpolation mode so as to avoid missing;
And S114.4, outputting the synchronous resampling result as multi-channel state monitoring data.
The current channel data, the voltage channel data and the vibration channel data matched with each index time point are jointly packaged into a unified structure record;
It should be noted that all the output structure record sets are multichannel state monitoring data;
S12, constructing a sliding alignment window based on a time stamp in the control instruction data, intercepting multi-channel state monitoring data through the sliding alignment window, and generating a channel response segment;
Specifically, the step of S12 is:
s121, calculating adjacent time stamp intervals according to time stamp fields in control instruction data;
In a particular embodiment, all time stamp fields in the control instruction data are extracted in chronological order;
It should be noted that, the calculation mode is to subtract the time stamp of the previous control instruction data from the time stamp of the next control instruction data to obtain the adjacent time stamp interval for the subsequent window boundary setting.
S122, generating a sliding alignment window boundary based on the adjacent time stamp interval and the set sliding step length;
In a specific embodiment, the timestamp of the earliest piece of control instruction data is set as an initial window starting point, and window starting and stopping time is generated by sequentially and backwardly translating according to a set sliding step length;
it should be noted that the sliding step length is a preset parameter, and the source of the sliding step length is a moving step length which is statistically set according to the historical instruction interval and is used for controlling the start and stop time of the window, and each window boundary comprises a window start time and a window stop time as a sliding alignment window boundary.
S123, intercepting multi-channel state monitoring data through sliding an alignment window boundary to obtain a channel response segment;
In a specific embodiment, all records within the corresponding time period are extracted from the multi-channel state monitoring data based on the start time and the end time range defined by each sliding alignment window boundary;
it should be noted that the extracted records are reorganized into channel response fragments;
Specifically, the step of generating the channel response fragment is:
s123.1, extracting the starting time and the ending time of each sliding alignment window;
In a specific embodiment, a time range field defined in a sliding alignment window boundary is read;
it should be noted that each sliding alignment window includes a set of start time and end time for defining a interception range;
s123.2, intercepting multichannel state monitoring data in a window range according to the starting time and the ending time;
In a specific embodiment, records with time stamps between start and stop times of a window in the multi-channel state monitoring data are screened out;
it should be noted that the obtained record is intercepted as a channel monitoring record set in the window.
S123.3, arranging the intercepted multi-channel state monitoring data in ascending order according to the time stamp;
in a specific embodiment, all records in the channel monitoring record set intercepted in the previous step are rearranged in ascending order according to the time stamp field;
It should be noted that the ascending order arrangement is used to ensure the consistency of the time sequence of the channel monitoring records.
And S123.4, outputting the multi-channel state monitoring data with the time stamps arranged in an ascending order as channel response fragments.
S13, constructing cross-channel response time difference data based on response starting time points of all channels in the channel response fragments, and inputting the response time difference data into a delay correction model to generate a delay alignment label;
Specifically, the steps of constructing cross-channel response time difference data are as follows:
S131, extracting response starting time points of current channel data, voltage channel data and vibration channel data in the channel response segment;
in a specific embodiment, response start time points of the current channel data, the voltage channel data and the vibration channel data are respectively positioned from the channel response fragments;
it should be noted that, the response starting time point is not the first time stamp of the channel sampling record, but is based on the time point that the instantaneous change rates of the current channel data, the voltage channel data and the vibration channel data corresponding to the channel exceed the corresponding preset noise threshold value for the first time;
The noise threshold is obtained by carrying out statistical calculation on natural fluctuation ranges of current channel data, voltage channel data and vibration channel data at fixed sampling time intervals when the circuit breaker is in a steady-state operation stage, and is used for distinguishing natural noise fluctuation and real response change of monitoring data;
specifically, for each type of channel data, extracting continuous monitoring records under the state of no control instruction input, calculating the mean value and standard deviation of the instantaneous change rate of the continuous monitoring records, setting the change rate value corresponding to the mean value plus three times of the standard deviation as the noise threshold value of the channel data, and judging that the moment is the response starting time point of the channel when the instantaneous change rate of any type of channel data exceeds the corresponding preset noise threshold value for the first time, namely judging that the moment is the response starting time point of the channel and judging whether the moment is the response starting time point of the channel;
In a specific embodiment, the decision equation for the response start time point is expressed as:
in the formula, Is a channelIs set to be equal to the response starting time point of (1),E { current channel, voltage channel, vibration channel },Is a channelAt the time ofIs used for the sampling value of (a),Is a given response threshold; To meet the condition The time point that was first acquired is selected from all the time points of the map.
S132, calculating a response starting time difference value between each pair of channels;
in a specific embodiment, the response starting time points of the three types of channels are paired in pairs, and time difference calculation is performed;
It should be noted that the time difference calculating method is to subtract the response starting time point of the previous channel from the response starting time point of the next channel to obtain the response starting time difference of the channel pair;
s133, combining response initial time differences among all channel pairs into cross-channel response time difference data;
in a specific embodiment, the computation results of pairing the three types of channels in pairs are subjected to aggregation packaging;
It should be noted that the result after the aggregation and encapsulation is cross-channel response time difference data, which contains all initial response difference information among the three types of channels.
Specifically, the step of generating cross-channel response time difference data includes:
s133.1, performing difference calculation on response starting time points of the current channel data and the voltage channel data to obtain a current voltage starting time difference value;
In a specific embodiment, the voltage channel data response start time point is subtracted from the current channel data response start time point;
It should be noted that the result is recorded as the current-voltage start time difference.
S133.2, performing difference calculation on response starting time points of the current channel data and the vibration channel data to obtain a current vibration starting time difference value;
in a specific embodiment, the current channel data response start time point is subtracted from the vibration channel data response start time point;
It should be noted that the result is recorded as the current vibration start time difference.
S133.3, performing difference calculation on response starting time points of the voltage channel data and the vibration channel data to obtain a voltage vibration starting time difference;
In a specific embodiment, the voltage channel data response start time point is subtracted from the vibration channel data response start time point;
it should be noted that the result is recorded as the voltage vibration start time difference.
And S133.4, summarizing the current voltage starting time difference value, the current vibration starting time difference value and the voltage vibration starting time difference value into cross-channel response time difference data.
In a specific embodiment, the three time difference values are uniformly packaged into a structured record;
It should be noted that the output record is the cross-channel response time difference data.
S134, inputting the cross-channel response time difference data into the delay correction model to generate a delay alignment label.
In a specific embodiment, the cross-channel response time difference data are used as input one by one, and are sent into a preset delay correction model to be calculated to obtain a delay alignment label;
the training steps of the delay correction model are as follows:
Acquiring historical operation record data, and dividing the historical operation record data into a delay correction training set and a delay correction test set, wherein the historical operation record data comprises cross-channel response time difference data and corresponding delay alignment labels thereof;
The historical operation record data is derived from control instruction data and multichannel state monitoring data collected by the circuit breaker in different operation states, and comprises three typical working conditions of normal closing, action lag and fault response;
The cross-channel response time difference data consists of three types of data, namely a current voltage starting time difference value, a current vibration starting time difference value and a voltage vibration starting time difference value, and is obtained by pairwise pairing calculation based on the response starting time points of the current channel data, the voltage channel data and the vibration channel data.
The delay alignment labels include a synchronous alignment label, a lag alignment label and an abnormal alignment label;
Configuring an initial classifier, taking cross-channel response time difference data in a delay correction training set and input data serving as the initial classifier, taking delay alignment labels corresponding to the delay correction training set as output data of the initial classifier, and training the initial classifier to obtain an initial delay correction network;
It should be noted that the initial classifier includes, but is not limited to, a Support Vector Machine (SVM), K-nearest neighbor (KNN), decision tree or random forest;
Verifying the initial delay correction network through the delay correction test set, outputting the initial delay correction network with the accuracy larger than or equal to the preset test accuracy, and taking the initial delay correction network as a pre-constructed delay correction model;
preferably, the preset test accuracy is set to 90% or more.
S141, screening out channel response fragments with response starting time difference values lower than a set synchronization threshold value based on the delay alignment labels;
In a specific embodiment, the response start time differences of all delay alignment label records are extracted;
Comparing each response starting time difference value with a preset synchronous threshold value, and marking a channel response segment below the threshold value as a synchronous channel response segment;
The synchronous threshold value is a time difference threshold value for judging the synchronism of the channel response fragments, is determined based on the statistical result of the cross-channel response time difference data acquired by the circuit breaker in a normal operation state, specifically, in the operation stage without abnormal events, the historical records of the current voltage starting time difference value, the current vibration starting time difference value and the voltage vibration starting time difference value are extracted, the mean value and the standard deviation of each type of cross-channel response time difference data are respectively counted, the value corresponding to the mean value plus twice the standard deviation is set as the synchronous threshold value of the cross-channel response time difference data, the synchronous threshold value is a single-side judging threshold value, and when the response starting time difference value of any channel pair is smaller than the corresponding synchronous threshold value, the channel response fragments are judged to meet the synchronous requirement;
the delay alignment label is used for marking the synchronicity state of the channel response fragment, wherein the class of the 'synchronicity alignment label' indicates that the cross-channel response time difference data of the channel response fragment is in the normal synchronicity range judged by the delay correction model, and the class of the 'hysteresis alignment label' and the 'abnormal alignment label' respectively indicate that the response delay and the unexpected response state exist;
By screening based on delay alignment labels, channel response fragments meeting the synchronicity requirement can be dynamically selected under the condition of not depending on a fixed synchronicity threshold value, and a data basis is provided for subsequent matching value calculation and causal verification.
S142, extracting control instruction data corresponding to the synchronous channel response segment;
in a specific embodiment, records within the same time range are retrieved from the control instruction data according to the time stamp range in the sync channel response segment;
It should be noted that the extracted record is control instruction data corresponding to the synchronous channel response segments one by one.
S143, performing matching value calculation based on the time interval and the amplitude variation of the control instruction data and the channel response segment;
In a specific embodiment, aligning a time stamp field of control instruction data with a response starting time point of a channel response segment, and calculating the matching degree of the time stamp field and the response starting time point by combining the response amplitude change of the channel response segment;
it should be noted that the result of the matching degree calculation is a matching value, which is used to characterize the causal relationship strength between the command and the response.
Specifically, the step of calculating the matching value is:
S143.1, extracting an action type field and a time stamp field in control instruction data;
s143.2, extracting response amplitude values and response starting time points in the channel response fragments;
in a specific embodiment, the response starting time point of the first record of the channel response segment and the maximum response amplitude in the whole record are read;
it should be noted that, the response amplitude is used to measure the action intensity, and the response starting time point is used to align with the instruction time.
S143.3, performing difference calculation on the timestamp field of the control instruction data and the response starting time point of the channel response segment to obtain a time interval value;
in a specific embodiment, the timestamp field of the control instruction data is subtracted from the response start time point of the channel response segment;
It should be noted that the difference result is recorded as a time interval value.
And S143.4, taking the time interval value and the response amplitude value as joint input, and calculating to obtain a matching value.
In a specific embodiment, the logic formula for calculating the matching value is:
in the formula, In order to match the value of the value,For the time interval normalized value(s),In response to the normalized value of the amplitude value,、Normalizing values for time intervalsResponse amplitude normalization valueThe corresponding weighting coefficient is used to determine the weight of the object,+=1,>Preferably, the composition of the present invention, preferably,=0.7,β=0.3;
Wherein the time interval normalization valueThe calculation formula of (2) is as follows: In the step (c), As a value of the time interval it is,An average response delay time calculated based on the historical response delay time in the normal response state;
Response amplitude normalization value The calculation formula of (2) is as follows: wherein, the method comprises the steps of, In order to respond to the amplitude value,An average response amplitude calculated based on the historical response amplitude in the normal response state;
the matching value is Is a dimensionless scoring value, the value range is within [0,1], the matching valueThe closer to 1 the value of (c) means the more synchronous the time response between the control instruction data and the channel response segment and the more matched the action intensity;
s144, marking the channel response fragments with the matching values exceeding the set threshold as causal verification tags.
In a particular embodiment, when the value is matchedThe value is greater than a preset matching value thresholdWhen the corresponding channel response segment is judged to have causal relation with the control instruction data, so as to generate a causal verification tag;
the matching value threshold value The generation logic of (1) is as follows:
collecting a large number of historical samples under a normal operation state through a circuit breaker, respectively calculating the matching value of each sample to form a matching value set, and calculating the average value of the matching value set And standard deviationAnd according to the set confidence coefficient, calculating and generating a matching value threshold value;
Expressed as:, for the confidence coefficient, preferably, Taking a value of 95%;
It should be noted that: Namely the lower limit of the matching value which can be exceeded by 95% of historical samples in the normal state, and based on the lower limit, when detecting at a certain time >If not, judging that the response is normal, otherwise, considering that the command-response link is abnormal or synchronization deviation exists.
S15, constructing an operation response mapping chain based on the causal verification tags arranged in time sequence, and generating state evolution mark data according to continuous non-closed loop events in the mapping chain.
Specifically, the step of generating state evolution marking data according to continuous non-closed loop events in the mapping chain comprises the following steps:
s151, carrying out adjacent pairing connection on the causal verification tags arranged in time sequence to generate a mapping chain unit;
in a specific embodiment, the two adjacent causal verification tags are paired end to end according to the ascending order of the timestamp fields of the causal verification tags;
it should be noted that, each pair of head-to-tail pairing results forms a mapping chain unit including a start node and an end node.
S152, performing time sequence splicing processing based on all the mapping chain units, and constructing an operation response mapping chain;
In a specific embodiment, all the mapping chain units are spliced end to end according to the time sequence, and the end node of the former unit is aligned with the start node of the latter unit;
It should be noted that the complete structure obtained after the splicing is an operation response mapping chain, reflecting the operation-response causal evolution path arranged in time.
S153, detecting whether a mapping chain unit with an unclosed end node exists in the operation response mapping chain;
in a particular embodiment, checking whether the end node of each map chain element within the operation response map chain is simultaneously present in the start node of any other map chain element;
It should be noted that the mapping chain unit is spliced in time sequence to only represent the sequence of events, but the logic continuity of the operation-response causal chain is not guaranteed;
It will be appreciated that the temporal concatenation of map chain units only reflects the order in which the operational instruction data and channel response segments occur and does not represent a necessarily continuous causal link between these events. In actual operation, a situation may occur that the channel response segment is not triggered by the control command data, or that the channel response segment does not trigger the subsequent control command data, at this time, the link is logically broken, and a closed operation-response causal link cannot be formed. Thus, such breaks cannot be identified by means of time-sequential stitching alone, requiring a determination of whether there is an un-closed loop unit by detecting whether the end node reappears in the starting node of the subsequent map chain unit;
the generation of non-closed loop units results from logic breaks in the control chain, typically caused by contact aging, drive mechanism hysteresis, or control mismatch. The purpose of detecting the non-closed loop unit is to identify an abnormal break point of the operation response chain and provide a basis for the generation of the subsequent state evolution marker data.
S154, marking continuous non-closed-loop mapping chain units as state evolution marking data;
In a specific embodiment, a plurality of non-closed-loop mapped chain units that are temporally adjacent are aggregate labeled;
It should be noted that, the aggregated marking result is state evolution marking data, which is used for indicating an abnormal evolution state which is not closed in the operation link.
Specifically, the logic of the marker state evolution marker data is:
S154.1, extracting the starting nodes and the ending nodes of all mapping chain units in the operation response mapping chain;
In a particular embodiment, the read operation is responsive to a start node and an end node for each map chain element within the map chain, with all start nodes forming a start node list and all end nodes forming an end node list.
S154.2, screening out mapping chain units which are not present in any starting node of the ending node;
In a specific embodiment, the end node list is compared with the start node list, all end nodes not present in the start node list are screened out, and the corresponding mapping chain units are classified into a set of non-closed-loop units. The set of non-closed loop elements reflects the control instruction data and the location of occurrence of a break in the channel response segment link.
It should be noted that the mapping chain units where the end nodes are located are non-closed loop units.
S154.3, performing aggregation index processing on adjacent non-closed-loop mapping chain units which are continuous in time;
in a specific embodiment, the non-closed-loop unit sets are arranged in ascending order according to the time stamp, and aggregation indexes are executed on the non-closed-loop units with adjacent time intervals smaller than a preset clustering threshold value, and the non-closed-loop units are combined into a continuous abnormal evolution record.
It should be noted that the cluster threshold is determined based on a statistical distribution of time intervals of non-closed-loop events in the historical normal operating state.
And S154.4, outputting the non-closed-loop mapping chain unit after the aggregation index processing as state evolution marking data.
In a specific embodiment, the continuous abnormal evolution records formed after aggregation are packaged into state evolution marking data and are arranged in ascending order according to time stamps;
the method is characterized in that the packaged record is state evolution marking data and is used for representing the abnormal evolution process of an operation-response causal chain in the whole life cycle of the running state of the circuit breaker.
Arranging all state evolution marking data in ascending order according to time stamps, judging the concentration degree of abnormal events in time according to the time intervals between adjacent records, and when the time intervals are gradually shortened, indicating that the occurrence frequency of the abnormal events is increased, judging that the circuit breaker is in a state degradation stage, and when the time intervals are kept stable or prolonged, indicating that the circuit breaker is in a stable operation stage;
counting the quantity of state evolution marked data appearing in the same time range, and when a large quantity of state evolution marked data continuously appears in a short time, indicating that the operation-response link is interrupted in a large quantity, and judging that the circuit breaker approaches to a fault shutdown stage;
Comparing the time distribution of the state evolution mark data with the circuit breaker operation record, wherein scattered state evolution mark data at the initial stage of operation represent early debugging stages, and high-frequency state evolution mark data only appear after long-term operation represent aging degradation stages;
Through the analysis, the state evolution track of the circuit breaker from operation, stable operation to degradation failure can be reversely deduced based on the state evolution mark data, and full life cycle detection of the running state of the circuit breaker is realized.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present invention are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center over a wired network or a wireless network. The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
In the several embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely one, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The method comprises the steps of obtaining a plurality of data, wherein part of data in the formula is obtained by removing dimensions and taking the numerical calculation, the formula is a formula closest to the actual situation by simulating a large amount of collected data through software, and preset parameters and preset thresholds in the formula are set by a person skilled in the art according to the actual situation or are obtained through simulating the large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
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