A detection system and detection method for intelligent instrumentation

Abstract

The present invention relates to the field of intelligent detection technology, and specifically discloses a detection system and a detection method for intelligent instruments and meters. The system comprises: a signal interface module, which is used to connect a target instrument through a universal interface and obtain an external data signal of the target instrument; a data scheduling module, which is used to receive an external data signal through a controller, analyze the external data signal to generate a scheduling strategy and issue a search instruction; a search engine module, which is used to receive a search instruction and retrieve the position of an abnormal scheduling signal, and determine the position information of the abnormal scheduling signal; a test management module, which is used to obtain the position information of the abnormal scheduling signal to perform electrical signal fault detection, determine the operation of the target instrument and perform maintenance; a data analysis module, which is used to analyze the operating status of the external data signal and determine whether the analysis result meets the requirements; the above realizes reducing the stable transmission of the detection signal of the instrument and meter and improving the accurate positioning and extraction of low-frequency fault signals.

Description

Technical Field

[0001] The present invention relates to the field of intelligent detection technology, and in particular to a detection system and a detection method for intelligent instruments and meters. Background Art

[0002] The assembly and use of electrical automation instruments and meters have brought convenience to industrial testing. However, the structure of electrical automation instruments and meters is more complex and highly integrated, requiring more cumbersome operation, repair and maintenance processes. Once such instruments and meters have minor problems, it takes a lot of time to troubleshoot and requires professionals to perform manual repairs, which relatively consumes more time and technical costs.

[0003] Through the establishment of intelligent instrument detection system, the operating status of instruments can be automatically detected. It is not limited to the detection of instruments and equipment of the same type. It can fully consider the stability and accuracy of the detection working status, and perform step-by-step allocation and data detection and stable acquisition of components and parts of each system, which greatly shortens the maintenance time of instruments, effectively improves the maintenance efficiency of instruments, and reduces maintenance costs.

[0004] However, although the existing intelligent instruments can realize general detection of data and automatic control and detection of detection information, it is easy to have unstable conditions such as load fluctuations during the intelligent detection process of some equipment in communication network detection, especially embedded instruments. In addition, due to the complex structure and distribution of embedded instruments, it is usually necessary to arrange detection sites to improve the acquisition of positioning information of the location of equipment signal transmission faults. If the status signal emitted by the instrument detection equipment has defects in transmission continuity, it will greatly increase the difficulty of analyzing and extracting information of the fault signal and its related characteristics, thereby reducing the accuracy and reliability of the detection of low-frequency fault signals of embedded intelligent instruments. Summary of the invention

[0005] The purpose of the present invention is to provide a detection system and detection method for intelligent instruments and meters to solve the following technical problems:

[0006] How to achieve stable transmission of detection signals of instruments and improve the accurate positioning and extraction of low-frequency fault signals of instruments.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A detection system for intelligent instruments and meters, the system comprising:

[0009] 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;

[0010] A data scheduling module, used to receive external data signals through a controller, analyze the external data signals and generate a scheduling strategy;

[0011] The controller includes an analysis unit, which is used to analyze the scheduling strategy results and determine whether the scheduling signal meets the requirements:

[0012] If it meets the requirements, the signal association model is updated;

[0013] If it does not match, a search instruction is issued;

[0014] 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;

[0015] 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:

[0016] If yes, continue running;

[0017] If not, a first warning signal is issued and the target instrument is repaired;

[0018] The data analysis module is used to analyze the operating status of external data signals and determine whether the analysis results meet the requirements:

[0019] If yes, upload the current external data signal;

[0020] If not, a second warning signal is issued to adjust the detection cycle of the target instrument;

[0021] The early warning module is used to execute the first early warning signal and the second early warning signal.

[0022] Preferably, the controller further comprises: a data acquisition unit, a correlation signal recognition unit, a scheduling unit, and a storage unit;

[0023] The data acquisition unit is used to collect external data signals of all points within the detection area of ​​the target instrument;

[0024] The correlation signal identification unit is used to identify and obtain historical correlation frequency domain data signals of all points in the detection area;

[0025] 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.

[0026] Preferably, the signal association model is constructed as follows:

[0027] 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;

[0028] 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.

[0029] Preferably, the scheduling strategy generation method is:

[0030] 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. ;

[0031] 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. ;

[0032] 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;

[0033] The area value Preset thresholds corresponding to associated signal parameters To compare:

[0034] like ≥ , a search instruction is issued.

[0035] Preferably, the search engine module:

[0036] Receiving external data through a receiver to identify data configuration information;

[0037] Determine the corresponding routing location and authorize it according to the identified data configuration information;

[0038] 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.

[0039] Preferably, the test management module:

[0040] Analyze the frequency domain signal transmission speed of a certain point acquired in real time Compare with the preset transmission speed threshold:

[0041] 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.

[0042] Preferably, the method in which the data analysis module analyzes the external data signal is:

[0043] Determine the current detection cycle Next Fault frequency of each point detection And point detection fault time ;

[0044] 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.

[0045] Preferably, the comprehensive operating efficiency coefficient of the point The comprehensive operating efficiency coefficient threshold of the preset point To compare:

[0046] like < , the operating efficiency is judged to be low and a second warning signal is issued;

[0047] like > , then the operating efficiency is judged to be high and the detection cycle of the target instrument is extended;

[0048] like ≤ ≤ , then the operating efficiency is judged to be normal and the current data signal is uploaded.

[0049] A detection method for intelligent instruments and meters is applied to a detection system for intelligent instruments and meters. The specific method includes:

[0050] S1. Use a universal interface to connect to a target instrument and obtain an external data signal of the target instrument;

[0051] 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;

[0052] S3, receiving a search instruction and performing abnormal dispatch signal location search to determine abnormal dispatch signal location information;

[0053] 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;

[0054] S5, analyzing the external data signal obtained in step S1, analyzing the detection cycle of the target instrument to issue a second warning signal, and adjusting the detection cycle of the target instrument.

[0055] Beneficial effects of the present invention:

[0056] (1) The present invention ensures timely discovery of unstable abnormal conditions in the data signal transmission process by setting up a data scheduling module, and ensures accurate screening of detection fault results by screening and locating such data signals; and by setting up a controller for receiving external data signals and analyzing the external data signals, generating a scheduling strategy based on the external data signal analysis results, analyzing the scheduling strategy results and determining the range of the scheduling signal, and then analyzing the rationality of the scheduling data and transferring it to the next step of processing in a timely manner, thereby ensuring stable transmission of the target signal detected by the instrument.

[0057] (2) The present invention can locate the pre-marked detection area in time according to the determination of the abnormal dispatch signal location information by setting up a search engine module, thereby reducing the cost of manual detection and professional training technology, and reducing the time cost of fixed-point information detection.

[0058] (3) By setting up a test management module, the abnormal dispatch signal location information is obtained to perform electrical signal fault detection, determine the operating status of the target instrument, issue the first warning signal, and promptly repair the target instrument; ensure timely electrical signal fault detection to discover the operating status of the target instrument, determine the fault location and timely repair of fault transmission details, thereby improving the accurate positioning and extraction of low-frequency fault signals of instruments and meters.

[0059] (4) By setting up a data analysis module to analyze the operating status of the external data signal transmitted by the normally operating target instrument, the rationality of the analysis result is judged to upload the current external data signal or issue a second warning signal, so as to further adjust the detection cycle of the target instrument and improve the detection efficiency of the fault signal.

[0060] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0062] Figure 1 This is a module flow chart of a detection system of an intelligent instrument of the present invention;

[0063] Figure 2 It is a schematic diagram of the structure of the controller unit of the data scheduling module of the present invention;

[0064] Figure 3 This is a step diagram of a detection method for an intelligent instrument of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] Although existing intelligent instruments and meters can realize general detection of data and automatic control and detection of detection information, for some equipment in communication network detection, especially the intelligent detection process of embedded instruments and meters, unstable conditions such as load fluctuations are prone to occur. In addition, due to the complex structure and distribution of embedded instruments, it is usually necessary to arrange detection sites to improve the acquisition of positioning information of the location of equipment signal transmission faults. If the status signal emitted by the instrument detection equipment has defects in transmission continuity, it will greatly increase the difficulty of analyzing and extracting information of the fault signal and its related characteristics, thereby reducing the accuracy and reliability of the detection of low-frequency fault signals of embedded intelligent instruments and meters.

[0067] In order to solve the problem of low efficiency of fault signal detection of embedded intelligent instrumentation caused by the above-mentioned signal transmission continuity defect of the equipment operation, the present invention is a detection system of intelligent instrumentation, please refer to Figure 1-2 As shown, the system provided by the present invention specifically includes: a signal interface module, a data scheduling module, a search engine module, a test management module, a data analysis module, and an early warning module.

[0068] In this embodiment, by setting a signal interface module, the target instrument is connected through a universal interface, and the external data signal of the target instrument is obtained. Due to the wide application of integrated technology and application control technology in industrial control design, different instruments and meters usually have different data ranges in the detection process in the detection of intelligent instruments and meters. The use of a universal interface ensures that the range of the collected data signal meets the needs of intelligent detection. By setting a data scheduling module, specifically, a controller is set to receive external data signals, analyze external data signals, and generate a scheduling strategy according to the analysis results of the external data signals; the external data signals here are digital signals, analog signals, or pulse signals obtained according to transmission characteristics, etc., and unified processing is performed according to the type of collected signals in the specific operation process, not limited to a certain type of signal. Among them, the "data scheduling" process is the process of further allocating and transmitting the external data signals obtained by the interface, and judging by the distribution range value of the pre-set standard scheduling signal to ensure the further improvement of the scheduling signal; by setting a data scheduling module, it is ensured that the unstable abnormal conditions in the data signal transmission process are discovered in time, such as load fluctuations, short fault signals, etc., and by screening and locating such data signals, accurate screening of the detection fault results is ensured.

[0069] Among them, the controller set up includes an analysis unit, which uses the analysis unit to analyze the scheduling strategy results and determine the range of the scheduling signal, and then analyzes the rationality of the scheduling data. If it is judged to be consistent, the signal association model is updated; if it is not consistent, a retrieval instruction is issued; setting the signal association model can effectively improve the accuracy of embedded intelligent instruments in detecting fault signals.

[0070] This embodiment also sets a search engine module to receive search instructions and retrieve the abnormal dispatch signal location, thereby determining the abnormal dispatch signal location information, and sets the search engine module to timely locate the pre-marked detection area according to the determination of the abnormal dispatch signal location information, thereby reducing the cost of manual detection and professional training technology, and reducing the time cost of fixed-point information detection. By setting a test management module, the abnormal dispatch signal location information is obtained to perform electrical signal fault detection to determine whether the target instrument is operating normally: if so, continue to operate; if not, issue a first warning signal and perform maintenance on the target instrument; according to the test management module, ensure timely detection of electrical signal faults to find the operating status of the target instrument, determine the fault location and the timely maintenance of the fault transmission details, thereby improving the accurate positioning and extraction of low-frequency fault signals of instruments and meters.

[0071] In addition, by setting up a data analysis module to analyze the operating status of the external data signal transmitted by the normally operating target instrument, it is determined whether the analysis result meets the requirements: if so, the current external data signal is uploaded; if not, a second warning signal is issued to adjust the detection cycle of the target instrument; the warning module is set to execute the first warning signal and the second warning signal.

[0072] As an embodiment of the present invention, please refer to Figure 2 As shown, the controller also includes: a data acquisition unit, a correlation signal recognition unit, a scheduling unit, and a storage unit;

[0073] The data acquisition unit is used to collect external data signals of all points in the detection area of ​​the target instrument;

[0074] The correlation signal identification unit is used to identify and obtain the historical correlation frequency domain data signals of all points in the detection area;

[0075] 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 a scheduling strategy by comparing the predicted correlation signal parameters.

[0076] Through the above technical scheme, in this embodiment, the controller is set to realize the collection and analysis of external data signals. Mainly, the controller includes a data collection unit, a correlation signal recognition unit, a scheduling unit, a storage unit, and an analysis unit; first, the data collection unit is used to collect external data signals of all points in the detection area of ​​the target instrument; then, the correlation signal recognition unit is used to identify and obtain the historical correlation frequency domain data signals of all points in the detection area; then, the scheduling unit is used to input the frequency data of the historical correlation frequency domain data signal into the signal correlation model, and obtain the predicted correlation signal parameters, and generate a scheduling strategy by analyzing the predicted correlation signal parameters, and finally, the scheduling strategy results are analyzed according to the set analysis unit and the range of the scheduling signal is judged, and then the rationality of the scheduling data is analyzed and transferred to the next step of processing in time.

[0077] As an implementation mode of the present invention, the process of constructing the signal association model is as follows:

[0078] 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;

[0079] 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.

[0080] Through the above technical scheme, in this embodiment, a scheme of building a signal correlation model is adopted. Specifically, by collecting the historical external data signals and the historical correlation signal parameters within the detection area of ​​the target instrument, the historical correlation signal parameters of each point are matched with the historical external data signals, and the signal data of multiple time points are obtained, and these data are processed into the form of training samples, and then a basic model is built through a convolutional neural network model; the basic model is trained by using the training samples of each historical correlation signal parameter to obtain a signal correlation model of the historical correlation signal parameters of each point; thereby providing a comparison basis for the comparison of the historical correlation signal and the predicted correlation signal.

[0081] As an implementation mode of the present invention, the scheduling strategy generation method is:

[0082] 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. ;

[0083] 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. ;

[0084] 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;

[0085] The area value Preset thresholds corresponding to associated signal parameters To compare:

[0086] like ≥ , a search instruction is issued.

[0087] Through the above technical solution, in this embodiment, by constructing the generation step of the scheduling strategy, further analysis is performed on the changes in the associated signal parameters of all points in the detection area, and the positioning retrieval process of the external data signal corresponding to the associated signal parameters in the overall state is obtained. The specific steps are: first, according to the historical associated signal parameters, a curve of the historical value of the historical associated signal parameters of each point changing with time is established. ; Then, the change curve of the predicted value of the associated signal parameter over time is obtained in the same way; Then, the size of the comparison curve is constructed in the same coordinate system. Such curves have different changes during the detection time according to the difference in changes. In this embodiment, the associated signal parameters of each point are calculated in the same coordinate system. Higher than Area value ;in, is the number of points, and the area value Preset thresholds corresponding to associated signal parameters Comparative analysis was performed based on the area value. Select the size to issue a retrieval command.

[0088] As an implementation mode of the present invention, the search engine module:

[0089] Receiving external data through a receiver to identify data configuration information;

[0090] Determine the corresponding routing location and authorize it according to the identified data configuration information;

[0091] 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.

[0092] Through the above technical scheme, the search engine module set in this embodiment is set based on the existing host computer program, and its operating mode is displayed by receiving the signal of external data through the sensor probe. For example, the waveform mode displays the collected data and presents it in a dynamically changing chart. It can intuitively display the transmission status of the frequency domain signal and determine the point location information detected by the instrument according to its current change; the specific steps are: first, receive external data through the receiver to identify the data configuration information; then, determine the corresponding routing position and authorize it according to the identified data configuration information; finally, 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.

[0093] As an implementation mode of the present invention, the test management module:

[0094] Analyze the frequency domain signal transmission speed of a certain point acquired in real time Compare with the preset transmission speed threshold:

[0095] 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.

[0096] Through the above technical solution, the setting of the test management module in this embodiment is used to realize timely maintenance of the target instrument: analyzing the frequency domain signal transmission speed of a certain point obtained in real time Compare with the preset transmission speed threshold: 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.

[0097] It should be noted that the frequency domain signal transmission speed here is It refers to the amount of data transmitted in the frequency domain per unit time; the transmission speed It can ensure the transmission status of the frequency domain signal at a certain point, and then determine the timely discovery of the fault status of the target instrument; in order to unify the measurement in the calculation process of the transmission speed value, two methods can be used as the unit of transmission rate. One is the code element rate, the number of code elements transmitted per unit time, the unit is baud (baud), so it is also called baud rate. One digital pulse is a code element. If the width of the code element is T seconds, then B=1 / T. The other is the data transmission rate, the amount of information transmitted per second, the unit is bit / second (b / s or bps), so it is also called bit rate. If the number of discrete values ​​that the code element can take is M, then T=Ts*㏒M, R=Rs / ㏒M, where Ts is the time required to send a binary symbol.

[0098] As an implementation mode of the present invention, the method for the data analysis module to analyze the external data signal is:

[0099] Determine the current detection cycle Next Fault frequency of each point detection And point detection fault time ;

[0100] 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.

[0101] Through the above technical solution, the data analysis module set in this embodiment analyzes the collection of external data at the interface to determine the operating characteristic parameters under the current detection cycle state. ;pass It can reflect the data operation efficiency status under the collection cycle, based on the operation characteristic data of all electrical automation instruments and meters obtained in advance. And detection cycle The comprehensive operating efficiency coefficient of the i points detected can be analyzed.

[0102] As an embodiment of the present invention, the point comprehensive operation efficiency coefficient The comprehensive operating efficiency coefficient threshold of the preset point To compare:

[0103] like < , the operating efficiency is judged to be low and a second warning signal is issued;

[0104] like > , then the operating efficiency is judged to be high and the detection cycle of the target instrument is extended;

[0105] like ≤ ≤ , then the operating efficiency is judged to be normal and the current data signal is uploaded.

[0106] Through the above technical solution, this embodiment analyzes the comprehensive operation efficiency coefficient of the point The size of the comprehensive operation efficiency coefficient threshold of the preset point Compare the size and judge: If < , the operating efficiency is judged to be low and a second warning signal is issued; if > , then the operating efficiency is judged to be high and the detection cycle of the target instrument is extended; if ≤ ≤ , then the operating efficiency is judged to be normal and the current data signal is uploaded.

[0107] The present invention also designs a detection method for intelligent instruments and meters, which is applied to a detection system for intelligent instruments and meters. Figure 3 As shown, the specific methods include:

[0108] S1. Use a universal interface to connect to a target instrument and obtain an external data signal of the target instrument;

[0109] 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;

[0110] S3, receiving a search instruction and performing abnormal dispatch signal location search to determine abnormal dispatch signal location information;

[0111] 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;

[0112] S5, analyzing the external data signal obtained in step S1, analyzing the detection cycle of the target instrument to issue a second warning signal, and adjusting the detection cycle of the target instrument.

[0113] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. An intelligent instrument detection system, characterized in that: The system comprises: 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; A data scheduling module, used to receive external data signals through a controller, analyze the external data signals and generate a scheduling strategy; The controller includes an analysis unit, which is used to analyze the scheduling strategy results and determine whether the scheduling signal meets the requirements: If it meets the requirements, the signal association model is updated; If it does not match, a search instruction is issued; 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; 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: If yes, continue running; If not, a first warning signal is issued and the target instrument is repaired; 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: If yes, upload the current external data signal; If not, a second warning signal is issued to adjust the detection cycle of the target instrument; An early warning module, used for executing a first early warning signal and a second early warning signal; The controller further includes: a data acquisition unit, a correlation signal recognition unit, a scheduling unit, and a storage unit; The data acquisition unit is used to collect external data signals of all points in the detection area of ​​the target instrument; The correlation signal identification unit is used to identify and obtain historical correlation frequency domain data signals of all points in the detection area; 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; The construction process of the signal association model is as follows: 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; 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; The scheduling strategy generation method is: 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. ; 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. ; 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; The area value Preset thresholds corresponding to associated signal parameters To compare: like ≥ , a search instruction is issued.

2. The intelligent instrument detection system according to claim 1 is characterized in that: The search engine module: Receiving external data through a receiver to identify data configuration information; Determine the corresponding routing location and authorize it according to the identified data configuration information; 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. The intelligent instrument detection system according to claim 2 is characterized in that: The test management module: Analyze the frequency domain signal transmission speed of a certain point acquired in real time Compare with the preset transmission speed threshold: 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. The intelligent instrument detection system according to claim 1 is characterized in that: The method by which the data analysis module analyzes the external data signal is: Determine the current detection cycle Next Fault frequency of each point detection And point detection fault time ; 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. The intelligent instrument detection system according to claim 4, characterized in that: The comprehensive operating efficiency coefficient of the point The comprehensive operating efficiency coefficient threshold of the preset point To compare: like < , the operating efficiency is judged to be low and a second warning signal is issued; like > , then the operating efficiency is judged to be high and the detection cycle of the target instrument is extended; like ≤ ≤ , then the operating efficiency is judged to be normal and the current data signal is uploaded.

6. A detection method for intelligent instruments and meters, characterized in that: A detection system for an intelligent instrument as claimed in any one of claims 1 to 5, wherein the specific method comprises: S1. Use a universal interface to connect to a target instrument and obtain an external data signal of the target instrument; 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, receiving a search instruction and performing abnormal dispatch signal location search to determine abnormal dispatch signal location information; 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, 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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