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CN118129819B - Detection system and detection method for intelligent instrument and meter - Google Patents

Detection system and detection method for intelligent instrument and meter Download PDF

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Publication number
CN118129819B
CN118129819B CN202410317033.2A CN202410317033A CN118129819B CN 118129819 B CN118129819 B CN 118129819B CN 202410317033 A CN202410317033 A CN 202410317033A CN 118129819 B CN118129819 B CN 118129819B
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signal
detection
instrument
external data
module
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CN118129819A (en
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董桂宾
魏然
钱道华
朱浩田
陈升辉
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Hangzhou Xili Intelligent Technology Co ltd
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Hangzhou Xili Intelligent Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D18/00—Testing or calibrating apparatus or arrangements provided for in groups G01D1/00 - G01D15/00

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  • General Physics & Mathematics (AREA)
  • Testing Or Calibration Of Command Recording Devices (AREA)

Abstract

The invention relates to the technical field of intelligent detection, and particularly discloses a detection system and a detection method of an intelligent instrument, wherein the system comprises a signal interface module, a data scheduling module, a search engine module, a test management module and a data analysis module, wherein the signal interface module is used for connecting a target instrument through a universal interface and acquiring external data signals of the target instrument, the data scheduling module is used for receiving the external data signals through a controller, analyzing the external data signals to generate a scheduling strategy and sending a search instruction, the search engine module is used for receiving the search instruction and searching the position of an abnormal scheduling signal and determining the position information of the abnormal scheduling signal, the test management module is used for acquiring the position information of the abnormal scheduling signal to perform electric signal fault detection and judging the operation and maintenance of the target instrument, the data analysis module is used for analyzing the operation state of the external data signals and judging whether the analysis result meets the requirement, and the stable signal transmission for reducing the detection of the instrument and the accurate positioning and the extraction of a low-frequency fault signal are realized.

Description

Detection system and detection method for intelligent instrument and meter
Technical Field
The invention relates to the technical field of intelligent detection, in particular to a detection system and a detection method of an intelligent instrument.
Background
Along with the assembly and use of the electric automation instrument and meter, the industrial detection is facilitated, but the structure of the electric automation instrument and meter is more complex, the integration level is high, more complicated operation maintenance and maintenance processes are needed, more time is needed for checking and professional personnel is needed for carrying out manual maintenance once the fine problems occur in the instruments and meters, and more time cost and technical cost are relatively consumed.
The running state of the instrument can be automatically detected through the establishment of the detection system of the intelligent instrument, the detection system is not limited to the detection of instruments of the same type, the stability and the accuracy of the detection working state can be fully considered, the elements and the parts of each system are distributed step by step, the data are detected and stably acquired, the maintenance time of the instrument is shortened greatly, the maintenance efficiency of the instrument is improved effectively, and the maintenance cost is reduced.
However, the existing intelligent instruments and meters can realize the general detection of data and the automatic control and detection of detection information, but unstable conditions such as load fluctuation and the like are easy to occur in the intelligent detection process of some communication network detection equipment, particularly embedded instruments and meters, and because the embedded structure and distribution are complex, detection sites are usually required to be arranged, the acquisition of positioning information of signal transmission fault positions of the equipment is improved, if the state signals sent by the instrument and meter detection equipment have defects on transmission continuity, the analysis and information extraction difficulty of fault signals and relevant characteristics can be greatly improved, and the accuracy and reliability of the detection of low-frequency fault signals of the embedded intelligent instruments and meters are further reduced.
Disclosure of Invention
The invention aims to provide a detection system and a detection method of an intelligent instrument and meter, which solve the following technical problems:
How to realize the stable transmission of the detected signals of the instruments and the meters and improve the accurate positioning and extraction of the low-frequency fault signals of the instruments and the meters.
The aim of the invention can be achieved by the following technical scheme:
a detection system for an intelligent instrument, the system comprising:
the signal interface module is used for connecting a target instrument through a universal interface and acquiring an external data signal of the target instrument;
the data scheduling module is used for receiving the external data signals through the controller, analyzing the external data signals and generating a scheduling strategy;
The controller comprises an analysis unit which is used for analyzing the scheduling strategy result and judging whether the scheduling signal meets the requirement:
if yes, updating the signal association model;
if not, a search instruction is sent out;
the search engine module is used for receiving the search instruction and searching the position of the abnormal scheduling signal and determining the position information of the abnormal scheduling signal;
The data analysis module is used for analyzing the running state of the external data signal transmitted by the target instrument which runs normally and judging whether the analysis result meets the requirement:
if yes, continuing to operate;
If not, a first early warning signal is sent, and the target instrument is overhauled;
the data analysis module is used for carrying out running state analysis on the external data signals and judging whether an analysis result meets the requirements:
If yes, uploading the current external data signal;
If not, a second early warning signal is sent out, and the detection period of the target instrument is adjusted;
and the early warning module is used for executing the first early warning signal and the second early warning signal.
Preferably, the controller also comprises a data acquisition unit, an associated signal identification unit, a scheduling unit and a storage unit;
The data acquisition unit is used for acquiring external data signals of all points in the detection area of the target instrument;
the correlation signal identification unit is used for identifying and acquiring historical correlation frequency domain data signals of all points in the detection area;
The scheduling unit is used for inputting the frequency data of the historical associated frequency domain data signals into the signal association model, obtaining the prediction associated signal parameters, and generating a scheduling strategy by comparing the prediction associated signal parameters.
Preferably, the construction process of the signal association model is as follows:
Collecting historical external data signals and historical associated signal parameters of a plurality of time points in a detection area of a target instrument, selecting the historical associated signal parameters of each point and the historical external data signals acquired at the corresponding time points, and generating training samples;
building a basic model through a convolutional neural network model, and training the basic model through training samples of historical associated signal parameters to obtain a signal associated model of the historical associated signal parameters of each point.
Preferably, the scheduling policy generation method is as follows:
respectively establishing a time-varying curve of historical values of the historical correlation signal parameters of each point location according to the historical correlation signal parameters ;
Respectively establishing curves of the predicted values of the associated signal parameters of each point position along with the time according to the predicted associated signal parameters;
For each point location, the associated signal parameters willAnd (3) withBuilt in the same coordinate system, calculateHigher thanArea value of (2)Wherein, the method comprises the steps of,Is the number of the points;
area value is calculated Preset threshold corresponding to associated signal parameterAnd (3) performing comparison:
If it is ≥And sending out a retrieval instruction.
Preferably, the search engine module:
receiving external data through a receiver to identify data configuration information;
determining the corresponding route position according to the identified data configuration information and authorizing;
and determining the frequency domain signal information and the frequency domain signal transmission speed parameter of the corresponding point position of the authorized route position, and transmitting the frequency domain signal transmission speed parameter of the point position to the test management module.
Preferably, the test management module:
analyzing frequency domain signal transmission speed of a certain point position obtained in real time Comparing with a preset transmission speed threshold value:
if the transmission speed is If the signal belongs to the preset transmission speed threshold, the electric signal is converted into a data signal, otherwise, a first early warning signal is sent out, and the target instrument is overhauled.
Preferably, the method for analyzing the external data signal by the data analysis module is as follows:
Determining a current detection period Lower part (C)Detection of failure frequency at individual pointsPoint location detection failure time;
By the formulaObtaining the detection periodThe point location comprehensive operation efficiency coefficientWherein, the method comprises the steps of, wherein,Is the operation characteristic data of the instrument and meter,Is a weight coefficient, and>0。
Preferably, the point location is integrated into an operating efficiency coefficientAnd a threshold value of an integrated operation efficiency coefficient of a preset point positionAnd (3) performing comparison:
If it is <Judging that the operation efficiency is low, and sending out a second early warning signal;
If it is >Judging that the operation efficiency is higher, and prolonging the detection period of the target instrument;
If it is ≤≤And judging that the operation efficiency is normal, and uploading the current data signal.
The detection method of the intelligent instrument is applied to a detection system of the intelligent instrument, and the specific method comprises the following steps:
S1, connecting a target instrument by using a universal interface, and acquiring an external data signal of the target instrument;
S2, receiving an external data signal through a controller to construct a signal association model, generating a scheduling strategy and analyzing, and sending a retrieval instruction and realizing updating of the signal association model according to an analysis result;
s3, receiving a search instruction and carrying out abnormal scheduling signal position search to determine abnormal scheduling signal position information;
s4, acquiring position information of the abnormal scheduling signal to perform electric signal fault detection analysis, and judging whether the running state of the target instrument is normal or not, if so, acquiring a current external data signal, and if not, sending a first early warning signal and overhauling the target instrument;
s5, analyzing the external data signals obtained in the step S1, analyzing the detection period of the target instrument, and sending out a second early warning signal to realize the adjustment of the detection period of the target instrument.
The invention has the beneficial effects that:
(1) The invention ensures that unstable abnormal conditions in the data signal transmission process are found in time through the data scheduling module, ensures accurate screening of detection fault results through screening and positioning of the data signals, and ensures stable transmission of detected target signals of instruments and meters through the arrangement of the controller for receiving external data signals, analyzing the external data signals, generating scheduling strategies according to the analysis results of the external data signals, analyzing the scheduling strategy results and judging the range of the scheduling signals, further analyzing the rationality of the scheduling data and switching to the next process in time.
(2) According to the invention, the search engine module is arranged, so that the detection area marked in advance can be positioned in time according to the determination of the position information of the abnormal scheduling signal, the cost of manual detection and specialized training technology is reduced, and the consumption of time cost of fixed point information detection is reduced.
(3) The test management module is arranged to acquire the position information of the abnormal dispatching signals to detect the electric signal faults, judge the running state of the target instrument, send out the first early warning signals and overhaul the target instrument in time, so that the running state of the target instrument is found by the electric signal fault detection in time, the fault position and the timely overhaul of the fault transmission detail problems are judged, and the accurate positioning and extraction of the instrument and instrument low-frequency fault signals are further improved.
(4) By setting the data analysis module to analyze the running state of the external data signal transmitted by the target instrument which runs normally, judging the rationality of the analysis result, uploading the current external data signal or sending out a second early warning signal, further adjusting the detection period of the target instrument is realized, and the detection efficiency of the fault signal is improved.
Of course, it is not necessary for any one product to practice the invention to achieve all of the advantages set forth above at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a detection system module of an intelligent instrument and meter according to the present invention;
FIG. 2 is a schematic diagram of a controller unit of the data scheduling module according to the present invention;
Fig. 3 is a step diagram of a detection method of an intelligent instrument of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
The existing intelligent instrument and meter can realize the general detection of data and the automatic control and detection of detection information, but the unstable conditions such as load fluctuation and the like are easy to occur in the intelligent detection process of some communication network detection equipment, especially embedded instruments and meters, and because the embedded structure and distribution are complex, detection sites are usually required to be arranged, the acquisition of positioning information of the signal transmission fault position of the equipment is improved, if the state signal sent by the instrument and meter detection equipment has defects on the transmission continuity, the analysis and information extraction difficulty of fault signals and relevant characteristics can be greatly improved, and the accuracy and reliability of the detection of the low-frequency fault signal of the embedded intelligent instrument and meter are further reduced.
In order to solve the problem of low fault signal detection efficiency of an embedded intelligent instrument and meter caused by the defect of continuity of equipment operation signal transmission, the invention relates to a detection system of the intelligent instrument and meter, and the detection system is shown in fig. 1-2.
According to the embodiment, the signal interface module is arranged, the target instrument is connected through the universal interface, and the external data signal of the target instrument is acquired, so that the acquired data signal range is ensured to meet the requirement of intelligent detection through the use of the universal interface due to the wide application of the integrated technology and the application control technology in industrial control design, and in the detection of the intelligent instrument and instrument, the data ranges of different instruments and meters in the detection process are different. The data scheduling module is specifically arranged, the controller is specifically arranged to receive external data signals, analyze the external data signals and generate a scheduling strategy according to the analysis result of the external data signals, wherein the external data signals are digital signals, analog signals or pulse signals and the like acquired according to transmission characteristics, and are subjected to unified processing according to the acquired signal types in a specific operation process, so that the method is not limited to a certain type of signals. The data scheduling process is a process of further distributing and transmitting external data signals acquired by an interface, further perfecting of scheduling signals is guaranteed by judging distribution range values of preset standard scheduling signals, unstable abnormal conditions in the data signal transmission process, such as load fluctuation, short-time fault signals and the like, are guaranteed to be found in time by setting a data scheduling module, and accurate screening of detection fault results is guaranteed by screening and positioning the data signals.
The controller comprises an analysis unit, wherein the analysis unit is used for analyzing a scheduling strategy result and judging the range of a scheduling signal, further analyzing scheduling data reasonably, judging that if the scheduling strategy result is accordant with the range, updating a signal association model, if the scheduling strategy result is not accordant with the range, sending a retrieval instruction, and setting the signal association model can effectively improve the accuracy of detecting fault signals of the embedded intelligent instrument.
The embodiment further comprises a search engine module, wherein the search engine module is used for receiving the search instruction and searching the position of the abnormal scheduling signal so as to determine the position information of the abnormal scheduling signal, and the search engine module is used for timely positioning a detection area marked in advance according to the determination of the position information of the abnormal scheduling signal, so that the cost of manual detection and specialized training technology is reduced, and the consumption of the time cost of fixed point information detection is reduced. The method comprises the steps of setting a test management module, obtaining position information of an abnormal dispatching signal to detect an electric signal fault, judging whether a target instrument runs normally or not, if yes, continuing to run, if not, sending a first early warning signal, overhauling the target instrument, judging the fault position and timely overhauling the fault transmission detail problem according to the running state of the target instrument, which is found by the test management module, of the electric signal fault detection, and further improving the accurate positioning and extraction of the instrument and instrument low-frequency fault signal.
In addition, through setting up the operation state analysis of the data analysis module to the external data signal that the target instrument of normal operation transmits, judge whether the analysis result accords with the requirement, if yes, upload the current external data signal, if not, send the second early warning signal, adjust the detection cycle of the target instrument, set up early warning module and carry out first early warning signal and second early warning signal.
As an embodiment of the present invention, referring to fig. 2, the controller further includes a data acquisition unit, an associated signal identification unit, a scheduling unit, and a storage unit;
The data acquisition unit is used for acquiring external data signals of all points in the detection area of the target instrument;
The correlation signal identification unit is used for identifying and acquiring historical correlation frequency domain data signals of all points in the detection area;
the scheduling unit is used for inputting the frequency data of the history associated frequency domain data signals into the signal association model, obtaining the prediction associated signal parameters, and generating a scheduling strategy by comparing the prediction associated signal parameters.
According to the technical scheme, the controller is arranged to collect and analyze external data signals, and mainly comprises a data collecting unit, an associated signal identifying unit, a scheduling unit, a storage unit and an analysis unit, wherein the data collecting unit is used for collecting the external data signals of all points in a detection area of a target instrument, the associated signal identifying unit is used for identifying and acquiring historical associated frequency domain data signals of all points in the detection area, the scheduling unit is used for inputting frequency data of the historical associated frequency domain data signals into a signal association model, acquiring predicted associated signal parameters, analyzing and predicting associated signal parameters to generate a scheduling strategy, and finally the analysis unit is used for analyzing scheduling strategy results and judging the range of the scheduling signals, so that rationality of scheduling data is analyzed and the next processing is carried out in time.
As one embodiment of the invention, the construction process of the signal correlation model is as follows:
Collecting historical external data signals and historical associated signal parameters of a plurality of time points in a detection area of a target instrument, selecting the historical associated signal parameters of each point and the historical external data signals acquired at the corresponding time points, and generating training samples;
building a basic model through a convolutional neural network model, and training the basic model through training samples of historical associated signal parameters to obtain a signal associated model of the historical associated signal parameters of each point.
According to the technical scheme, in the embodiment, a scheme of a signal association model is built, specifically, historical external data signals and historical association signal parameters thereof in a detection area of a target instrument are collected, the historical association signal parameters of each point location are corresponding to the historical external data signals, signal data of a plurality of time points are obtained, the data are processed into training samples, then a basic model is built through a convolutional neural network model, the basic model is trained through training samples of the historical association signal parameters, the signal association model of the historical association signal parameters of each point location is obtained, and further a comparison basis is provided for comparison of the historical association signals and the prediction association signals.
As one embodiment of the present invention, a scheduling policy generation method includes:
respectively establishing a time-varying curve of historical values of the historical correlation signal parameters of each point location according to the historical correlation signal parameters ;
Respectively establishing curves of the predicted values of the associated signal parameters of each point position along with the time according to the predicted associated signal parameters;
For each point location, the associated signal parameters willAnd (3) withBuilt in the same coordinate system, calculateHigher thanArea value of (2)Wherein, the method comprises the steps of,Is the number of the points;
area value is calculated Preset threshold corresponding to associated signal parameterAnd (3) performing comparison:
If it is ≥And sending out a retrieval instruction.
Through the technical scheme, in the embodiment, the generation step of constructing the scheduling strategy is used for further analyzing the change of the associated signal parameters of all the detection points of the detection area, and the positioning and searching process of the external data signals corresponding to the associated signal parameters in the whole state is obtained. Firstly, respectively establishing curves of historical values of historical correlation signal parameters of all points along with time according to the historical correlation signal parametersThen the change curve of the predicted value of the associated signal parameter along with time is obtained in the same mode, then the size of the comparison curve is constructed in the same coordinate system, the curve has the change difference in the detection time according to the change difference, and the embodiment calculates the associated signal parameter of each point by aiming at each point in the same coordinate systemHigher thanArea value of (2)Wherein, the method comprises the steps of,Is the number of points and will be the area valuePreset threshold corresponding to associated signal parameterPerforming comparison and analysis according to the area valueThe size selection of (1) issues a retrieval instruction.
As one embodiment of the present invention, the search engine module:
receiving external data through a receiver to identify data configuration information;
determining the corresponding route position according to the identified data configuration information and authorizing;
and determining the frequency domain signal information and the frequency domain signal transmission speed parameter of the corresponding point position of the authorized route position, and transmitting the frequency domain signal transmission speed parameter of the point position to the test management module.
According to the technical scheme, the search engine module is set based on an existing upper computer program, signals of external data are received through a sensor probe to display the operation mode of the search engine module, for example, a oscillogram mode displays collected data, a dynamic change chart is displayed, the transmission state of frequency domain signals can be intuitively displayed, point position information detected by instrument equipment is determined according to the current change of the frequency domain signals, the specific steps are that firstly, the data configuration information identification is carried out through the external data received through a receiver, then, the corresponding route position of the external data is determined according to the identified data configuration information and authorized, finally, frequency domain signal information and frequency domain signal transmission speed parameters of the corresponding point position of the authorized route position are determined, and the frequency domain signal transmission speed parameters of the point position are transmitted to a test management module.
As an embodiment of the present invention, the test management module:
analyzing frequency domain signal transmission speed of a certain point position obtained in real time Comparing with a preset transmission speed threshold value:
if the transmission speed is If the signal belongs to the preset transmission speed threshold, the electric signal is converted into a data signal, otherwise, a first early warning signal is sent out, and the target instrument is overhauled.
By the technical scheme, the test management module in the embodiment is used for realizing timely overhaul of the target instrument, namely analyzing the frequency domain signal transmission speed of a certain point position acquired in real timeComparing with a preset transmission speed threshold value, if the transmission speed is equal to the preset transmission speed threshold valueIf the signal belongs to the preset transmission speed threshold, the electric signal is converted into a data signal, otherwise, a first early warning signal is sent out, and the target instrument is overhauled.
The frequency domain signal transmission rate here isRefers to the amount of data transmitted in the frequency domain in unit time, and the transmission speed is used for transmitting the dataThe method can ensure the transmission state of the frequency domain signal of a certain point position, further judge the timely discovery of the fault state of the target instrument, and can adopt two methods as units of transmission rate in order to unify measurement in the calculation process of the transmission speed value. One is the symbol rate, the number of symbols transmitted per unit time, in baud (baud), and is also called the baud rate. One digital pulse is one symbol. If the symbol width is T seconds, b=1/T. The other is the data transmission rate, the amount of information transmitted per second, in bits per second (b/s or bps), and is also called bit rate. If the number of discrete values that a symbol can take is M, then t=ts×log, r=rs/log, where Ts is the time required to send a binary symbol.
As one embodiment of the present invention, the method for analyzing the external data signal by the data analysis module is as follows:
Determining a current detection period Lower part (C)Detection of failure frequency at individual pointsPoint location detection failure time;
By the formulaObtaining the detection periodThe point location comprehensive operation efficiency coefficientWherein, the method comprises the steps of, wherein,Is the operation characteristic data of the instrument and meter,Is a weight coefficient, and>0。
Through the technical scheme, the data analysis module arranged in the embodiment analyzes the collection of the external data at the interface and judges the operation characteristic parameters in the current detection period stateBy means ofThe data operation efficiency state under the period of the collection can be reflected, and the operation characteristic data of all the electrical automation instruments and meters at all the points can be obtained in advanceAnd detection periodThe magnitude of the comprehensive operation efficiency coefficient of the detected i points can be analyzed.
As one embodiment of the invention, the point location comprehensive operation efficiency coefficientAnd a threshold value of an integrated operation efficiency coefficient of a preset point positionAnd (3) performing comparison:
If it is <Judging that the operation efficiency is low, and sending out a second early warning signal;
If it is >Judging that the operation efficiency is higher, and prolonging the detection period of the target instrument;
If it is ≤≤And judging that the operation efficiency is normal, and uploading the current data signal.
Through the technical scheme, the embodiment analyzes the point location comprehensive operation efficiency coefficientBy integrating the magnitude of the operation efficiency coefficient threshold with the preset point positionComparing the sizes and judging if<Judging that the operation efficiency is low, sending out a second early warning signal, if so>Judging that the operation efficiency is higher, and prolonging the detection period of the target instrument, if so≤≤And judging that the operation efficiency is normal, and uploading the current data signal.
The invention also designs a detection method of the intelligent instrument and meter, which is applied to a detection system of the intelligent instrument and meter, as shown in FIG. 3, and the specific method comprises the following steps:
S1, connecting a target instrument by using a universal interface, and acquiring an external data signal of the target instrument;
S2, receiving an external data signal through a controller to construct a signal association model, generating a scheduling strategy and analyzing, and sending a retrieval instruction and realizing updating of the signal association model according to an analysis result;
s3, receiving a search instruction and carrying out abnormal scheduling signal position search to determine abnormal scheduling signal position information;
s4, acquiring position information of the abnormal scheduling signal to perform electric signal fault detection analysis, and judging whether the running state of the target instrument is normal or not, if so, acquiring a current external data signal, and if not, sending a first early warning signal and overhauling the target instrument;
s5, analyzing the external data signals obtained in the step S1, analyzing the detection period of the target instrument, and sending out a second early warning signal to realize the adjustment of the detection period of the target instrument.
The foregoing is merely illustrative and explanatory of the principles of the invention, as various modifications and additions may be made to the specific embodiments described, or similar thereto, by those skilled in the art, without departing from the principles of the invention or beyond the scope of the appended claims.

Claims (6)

1.一种智能化仪器仪表的检测系统，其特征在于，所述系统包括：1. An intelligent instrument detection system, characterized in that the system comprises: 信号接口模块，用于通过通用接口连接目标仪器，并获取目标仪器的外部数据信号；A signal interface module, used to connect to a target instrument through a universal interface and obtain an external data signal of the target instrument; 数据调度模块，用于通过控制器接收外部数据信号，分析外部数据信号生成调度策略；A data scheduling module, used to receive external data signals through a controller, analyze the external data signals and generate a scheduling strategy; 所述控制器包括分析单元，所述分析单元用于分析调度策略结果并判断调度信号是否符合要求：The controller includes an analysis unit, which is used to analyze the scheduling strategy results and determine whether the scheduling signal meets the requirements: 若符合，则更新信号关联模型；If it meets the requirements, the signal association model is updated; 若不符合，则发出检索指令；If it does not match, a search instruction is issued; 搜索引擎模块，用于接收检索指令并检索异常调度信号位置，确定异常调度信号位置信息；A search engine module, used to receive a search instruction and search for the abnormal dispatch signal location, and determine the abnormal dispatch signal location information; 测试管理模块，用于获取异常调度信号位置信息进行电信号故障检测，判断目标仪器运行是否正常：The test management module is used to obtain the location information of abnormal dispatch signals to detect electrical signal faults and determine whether the target instrument is operating normally: 若是，则继续运行；If yes, continue running; 若否，则发出第一预警信号，并对目标仪器进行检修；If not, a first warning signal is issued and the target instrument is repaired; 数据分析模块，用于对正常运行的目标仪器传输的外部数据信号的运行状态分析，判断分析结果是否符合要求：The data analysis module is used to analyze the operating status of the external data signal transmitted by the normally operating target instrument and determine whether the analysis results meet the requirements: 若是，则上传当前外部数据信号；If yes, upload the current external data signal; 若否，则发出第二预警信号，调整目标仪器的检测周期；If not, a second warning signal is issued to adjust the detection cycle of the target instrument; 预警模块，用于执行第一预警信号和第二预警信号；An early warning module, used for executing a first early warning signal and a second early warning signal; 所述控制器还包括：数据采集单元、关联信号识别单元、调度单元、存储单元；The controller further includes: a data acquisition unit, a correlation signal recognition unit, a scheduling unit, and a storage unit; 所述数据采集单元用于采集目标仪器的检测区域内所有点位的外部数据信号；The data acquisition unit is used to collect external data signals of all points in the detection area of the target instrument; 所述关联信号识别单元用于识别并获取检测区域内所有点位的历史关联频域数据信号；The correlation signal identification unit is used to identify and obtain historical correlation frequency domain data signals of all points in the detection area; 所述调度单元用于将历史关联频域数据信号的频率数据输入信号关联模型中，获取预测关联信号参数，通过比对预测关联信号参数生成调度策略；The scheduling unit is used to input the frequency data of the historical correlation frequency domain data signal into the signal correlation model, obtain the predicted correlation signal parameters, and generate the scheduling strategy by comparing the predicted correlation signal parameters; 所述信号关联模型的构建过程为：The construction process of the signal association model is as follows: 采集目标仪器的检测区域内的若干时间点的历史外部数据信号及历史关联信号参数，选取各点位的历史关联信号参数与对应时间点获取的历史外部数据信号，生成训练样本；Collect historical external data signals and historical correlation signal parameters at several time points within the detection area of the target instrument, select the historical correlation signal parameters of each point and the historical external data signals obtained at the corresponding time point, and generate training samples; 通过卷积神经网络模型搭建基础模型，通过各历史关联信号参数的训练样本对基础模型进行训练，获得各个点位历史关联信号参数的信号关联模型；The basic model is built through the convolutional neural network model, and the basic model is trained through the training samples of each historical correlation signal parameter to obtain the signal correlation model of the historical correlation signal parameters of each point; 所述调度策略生成方法为：The scheduling strategy generation method is: 根据历史关联信号参数分别建立各个点位历史关联信号参数历史数值随时间变化的曲线；According to the historical correlation signal parameters, the curves of the historical values of the historical correlation signal parameters at each point changing with time are established respectively. ; 根据预测关联信号参数分别建立各个点位的关联信号参数预测值随时间变化的曲线；According to the predicted correlation signal parameters, the curves of the predicted values of the correlation signal parameters at each point changing with time are established. ; 针对每各点位的关联信号参数，将与在同一坐标系中建立，计算高于的面积值；其中，为点位数量；For the associated signal parameters of each point, and Established in the same coordinate system, calculation Higher than Area value ;in, is the number of points; 将面积值与关联信号参数对应的预设阈值进行比对：The area value Preset thresholds corresponding to associated signal parameters To compare: 若≥，则发出检索指令。like ≥ , a search instruction is issued. 2.根据权利要求1所述的一种智能化仪器仪表的检测系统，其特征在于，所述搜索引擎模块：2. The intelligent instrument detection system according to claim 1, characterized in that the search engine module: 通过接收机接收外部数据进行数据配置信息识别；Receiving external data through a receiver to identify data configuration information; 根据识别后的数据配置信息确定其对应路由位置并授权；Determine the corresponding routing location and authorize it according to the identified data configuration information; 确定授权后的路由位置对应点位的频域信号信息和频域信号传输速度参数，并将该点位的频域信号传输速度参数传输给测试管理模块。Determine the frequency domain signal information and frequency domain signal transmission speed parameters of the point corresponding to the authorized routing position, and transmit the frequency domain signal transmission speed parameters of the point to the test management module. 3.根据权利要求2所述的一种智能化仪器仪表的检测系统，其特征在于，所述测试管理模块：3. The intelligent instrument detection system according to claim 2, characterized in that the test management module: 分析实时获取的某个点位的频域信号传输速度与预设传输速度阈值进行比对：Analyze the frequency domain signal transmission speed of a certain point acquired in real time Compare with the preset transmission speed threshold: 若传输速度属于预设传输速度阈值，则将电信号转化成数据信号；否则，发出第一预警信号，并对目标仪器进行检修。If the transmission speed If it falls within the preset transmission speed threshold, the electrical signal is converted into a data signal; otherwise, a first warning signal is issued and the target instrument is repaired. 4.根据权利要求1所述的一种智能化仪器仪表的检测系统，其特征在于，所述数据分析模块对外部数据信号进行分析的方法为：4. The intelligent instrument detection system according to claim 1 is characterized in that the method in which the data analysis module analyzes the external data signal is: 确定当前检测周期下的个点位检测故障频率及点位检测故障时间；Determine the current detection cycle Next Fault frequency of each point detection And point detection fault time ; 通过公式获得该检测周期下的点位综合运行效率系数，其中，为仪器仪表的运行特征数据，为权重系数，且＞0。By formula Get the detection cycle The comprehensive operating efficiency coefficient of the point under ,in, is the operating characteristic data of the instrument, is the weight coefficient, and ＞0. 5.根据权利要求4所述的一种智能化仪器仪表的检测系统，其特征在于，将点位综合运行效率系数与预设点位综合运行效率系数阈值进行比对：5. According to the intelligent instrument detection system of claim 4, it is characterized in that the comprehensive operation efficiency coefficient of the point is The comprehensive operating efficiency coefficient threshold of the preset point To compare: 若＜，则判断运行效率偏低，发出第二预警信号；like ＜ , the operating efficiency is judged to be low and a second warning signal is issued; 若＞，则判断运行效率偏高，延长目标仪器检测周期；like ＞ , then the operating efficiency is judged to be high and the detection cycle of the target instrument is extended; 若≤≤，则判断运行效率正常，上传当前数据信号。like ≤ ≤ , then the operating efficiency is judged to be normal and the current data signal is uploaded. 6.一种智能化仪器仪表的检测方法，其特征在于，应用于如权利要求1-5中任意项所述的一种智能化仪器仪表的检测系统，具体方法包括：6. A method for detecting an intelligent instrument, characterized in that it is applied to a detection system for an intelligent instrument as claimed in any one of claims 1 to 5, and the specific method comprises: S1、利用通用接口连接目标仪器，获取目标仪器的外部数据信号；S1. Use a universal interface to connect to a target instrument and obtain an external data signal of the target instrument; S2、通过控制器接收外部数据信号构建信号关联模型，生成调度策略并分析，根据分析结果发出检索指令和实现信号关联模型更新；S2, receiving external data signals through the controller to build a signal association model, generate and analyze the scheduling strategy, issue a retrieval instruction and implement the signal association model update according to the analysis results; S3、接收检索指令并进行异常调度信号位置检索，确定异常调度信号位置信息；S3, receiving a search instruction and performing abnormal dispatch signal location search to determine abnormal dispatch signal location information; S4、获取异常调度信号位置信息进行电信号故障检测分析，判断目标仪器运行状态是否正常：若是，则获取当前外部数据信号；若否，则发出第一预警信号，并对目标仪器进行检修；S4. Obtain the abnormal dispatch signal location information to perform electrical signal fault detection and analysis to determine whether the target instrument is operating normally: if so, obtain the current external data signal; if not, issue the first warning signal and perform maintenance on the target instrument; S5、对步骤S4获取的外部数据信号进行分析，分析目标仪器检测周期发出第二预警信号，实现目标仪器的检测周期调整。S5, analyzing the external data signal obtained in step S4, analyzing the detection cycle of the target instrument to issue a second warning signal, and adjusting the detection cycle of the target instrument.
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