CN117348491B - Networking equipment data acquisition system and method based on industrial Internet - Google Patents
Networking equipment data acquisition system and method based on industrial Internet Download PDFInfo
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Abstract
The invention relates to the technical field of data acquisition, in particular to a networking equipment data acquisition system and method based on an industrial Internet, comprising a monitoring layer, an analysis layer and an acquisition layer; the invention avoids continuous operation data acquisition in the operation process of the industrial equipment by adaptively designing the operation data acquisition period of the industrial equipment, effectively reduces the operation burden of monitoring and managing the background of the industrial equipment by data acquisition, and reduces the adaptation of background calculation resources as much as possible.
Description
Technical Field
The invention relates to the technical field of data acquisition, in particular to a networking equipment data acquisition system and method based on an industrial Internet.
Background
The industrial Internet is a novel infrastructure, an application mode and industrial ecology which are deeply fused with a new generation of information communication technology and industrial economy, and a brand-new manufacturing and service system which covers a full industrial chain and a full value chain is constructed by comprehensively connecting people, machines, objects, systems and the like, so that an implementation way is provided for the development of industrialization, even industrialization digitization and networking intellectualization.
The invention patent with the application number 202011513750.0 discloses a data information acquisition method based on the industrial Internet, which is characterized by comprising the following steps: s1, setting a network shutdown multipath forwarding mode, and developing a gateway machine to establish a communication network and receive analysis service; s2, pre-identifying the grades of the data information types collected by the communication network, sequencing according to the grades, and defining the adjustment parameters of the data collection: s3, collecting data information of each data node of the industrial Internet through a communication network; s4, removing noise of the acquired data information: s5, extracting abnormal data, classifying the extracted abnormal data, judging the attribute of the extracted abnormal data, analyzing the error rate of the abnormal data, and analyzing the error rate of the abnormal data; s6, collecting and storing the collected data information; s7, checking the stored data information through the WEB server.
The application aims at solving the problems: at present, the industrial Internet is rapidly developing, and the acquisition and distribution of data are particularly important. However, the data acquisition in the prior art has the problems of inconvenient communication, inaccurate, timely and perfect acquired industrial data and the like.
However, at present, under the operating state of carrying on the industrial internet, the industrial equipment is subjected to data acquisition through the industrial internet, so that the problem that the operating cost of the data acquisition background in the industrial internet is increased is solved because the industrial equipment is more and the industrial equipment is subjected to continuous data acquisition, thereby causing the data acquisition background to have larger burden and further causing the data acquisition background to have huge computing power resources.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a networking equipment data acquisition system and method based on the industrial Internet, and solves the technical problems in the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme:
in a first aspect, an industrial internet-based networked device data acquisition system comprises a monitoring layer, an analysis layer and an acquisition layer;
the method comprises the steps that operation data and fault data of industrial equipment are uploaded through a monitoring layer, data screening and configuration of the operation data and the fault data are completed in the monitoring layer, an analysis layer synchronously receives the operation data and the fault data which are completed in configuration, the industrial equipment fault rate in a data acquisition period and an acquisition period acquisition stage of the industrial equipment is predicted based on the industrial equipment operation data and the fault data which are mutually configured, the acquisition layer receives the industrial equipment data acquisition period predicted by the analysis layer, the industrial equipment operation data and the fault data are acquired based on the data acquisition period, and the acquired industrial equipment operation data and the fault data are synchronously fed back to the monitoring layer;
The analysis layer comprises a receiving module, a prediction module and a storage module, wherein the receiving module is used for receiving the industrial equipment operation data and the fault data which are configured in the acquisition layer, the prediction module is used for reading the industrial equipment operation data and the fault data which are received by the receiving module, predicting the next data acquisition period of the industrial equipment by applying the industrial equipment operation data and the fault data, and acquiring the industrial equipment fault rate in the period, and the storage module is used for receiving the industrial equipment fault rate in the acquisition period which is predicted in the prediction module and storing the industrial equipment fault rate in the acquisition period which is predicted;
The prediction module predicts the next data acquisition period of the industrial equipment based on the operation data and the fault data of the industrial equipment as follows:
Wherein: t is the acquisition period; t 0 is the acquisition cycle base; p last is the operating power of the industrial equipment in the operating data of the timestamp prefix bit; p next is the industrial equipment operating power in the operation data set after the time stamp; r last is the output frequency of the finished product in the operation data of the timestamp front set; r next is the output frequency of the finished product in the operation data set after the time stamp; gamma is the failure rate of industrial equipment in the acquisition period acquisition stage; k is the yield of the output finished products of the current industrial equipment; q is a collection of stations on the industrial equipment; omega c is the weight of the station on the c-th industrial equipment;
when the receiving module operates to receive the configured industrial equipment operation data and fault data in the acquisition layer, the configured industrial equipment operation data and fault data are received in two groups, the weight is subjected to the setting logic that the weight is larger when the upper station of the industrial equipment is close to the front position of the industrial equipment and the weight is smaller when the upper station of the industrial equipment is close to the rear position of the industrial equipment.
Further, the monitoring layer comprises an uploading module, a screening module and a configuration module, wherein the uploading module is used for uploading operation data and fault data of the industrial equipment, the screening module is used for traversing and reading the operation data and the fault data of the industrial equipment uploaded by the uploading module, setting screening logic, screening the operation data and the fault data of the industrial equipment uploaded by the uploading module by applying the screening logic, the configuration module is used for receiving the operation data and the fault data of the residual industrial equipment after being processed by the screening module, and the mutual configuration of the operation data and the fault data of the industrial equipment is carried out based on a timestamp generated by the operation data and the fault data of the industrial equipment;
Wherein the operational data of the industrial device comprises: operating power, output product frequency, operating duration, fault data of the industrial equipment includes: and outputting the yield of finished products and fault source stations, continuously operating the monitoring layer twice when the system is operated for the first time, uploading operation data and fault quantity of industrial equipment twice, further monitoring the operation state of the acquisition layer after the monitoring layer is operated twice continuously, and executing third and subsequent industrial equipment operation data and fault data uploading operation by the monitoring layer after the monitoring layer monitors the operation of the acquisition layer.
Still further, the screening logic set in the screening module is expressed as:
Wherein: dR (a, b) is the difference rate of data a and data b; n a is a feature matrix of data a; n b is a feature matrix of data b; the characteristic vector is the characteristic vector of the 1 st group of data content in the characteristic matrix of the data a; /(I) The characteristic vector of the 1 st group of data content in the characteristic matrix of the data b; dx a-b is the Euclidean distance between the feature matrix of data a and the feature matrix of data b;
The characteristic matrix of the data consists of characteristic vectors of various data contents in the data, screening logic set in a screening module is applied to operation data and fault data of industrial equipment, after the difference rate dR (a, b) of the data a and the data b is obtained, the difference rate dR (a, b) is more than or equal to 25 percent or dR (a, b) is less than 25 percent, when dR (a, b) is less than 25 percent, one of the data a and the data b is deleted, when dR (a, b) is more than or equal to 25 percent, the data a and the data b are reserved, and the difference rate of the one data and other data is obtained, and the screening logic set in the screening module is applied after the detection layer is continuously operated for two times.
Further, the Euclidean distance between the data feature matrices is obtained by the following formula:
The Euclidean distance between the data feature matrixes applied in the screening logic set in the screening module is obtained based on the difference rate, and the target is obtained in an alternating and synchronous mode and applied in an alternating mode.
Furthermore, in the operation stage of the configuration module, the operation data and fault data of the industrial equipment remained after the operation and screening of the screening module are received, the generation time stamps of the received operation data and fault data of the industrial equipment are further read, each fault data is used as a configuration target, and the operation data and the configuration target of the industrial equipment before the generation time stamps of the fault data corresponding to the configuration target are mutually configured.
Furthermore, the failure rate gamma of the industrial equipment in the acquisition period acquisition stage is calculated by the following formula:
wherein: h is the number of days of operation of the industrial equipment; The average value of the running time of the industrial equipment up to day 1; g 1 is the number of failures by day 1 of the operation of the industrial equipment; f life cycle of industrial equipment;
Wherein, In/>Are known.
Further, the acquisition layer comprises an application module, a feedback module and a cloud database, wherein the application module is used for receiving the next data acquisition period of the industrial equipment, which is predicted by the operation of the prediction module in the analysis layer, acquiring the industrial equipment operation data by the application of the received acquisition period, the feedback module is used for acquiring the industrial equipment operation data acquired by the application of the acquisition period in the application module, feeding the industrial equipment operation data back to the uploading module in the monitoring layer, and the cloud database is used for receiving the industrial equipment operation data fed back to the uploading module in the monitoring layer by the feedback module and the industrial equipment fault rate prediction result in the acquisition period acquisition stage stored in the storage module;
The cloud database stores the industrial equipment operation data and the industrial equipment failure rate prediction result after receiving the industrial equipment operation data and the industrial equipment failure rate prediction result, and further carries out accurate trend analysis on the industrial equipment failure rate prediction result after storing the industrial equipment operation data and the industrial equipment failure rate prediction result.
Still further, the accurate trend analysis logic of the industrial equipment failure rate prediction result is expressed as:
wherein: τ is an accurate trend representation value of the industrial equipment failure rate prediction result; l is a set of industrial equipment failure rate prediction results; gamma 1 is the result of the 1 st industrial equipment failure rate prediction; is a correction factor;
Wherein the correction factor Is obeyed by the following values: under the condition that the correction factor corresponds to the product target gamma, industrial equipment does not fail, and the correction factor/>The value is 1, the industrial equipment fails, and the larger the corresponding gamma value is, the correction factor/>The larger the value, the more the correction factor/>The smaller the value is, the more accurate trend expression value corresponding to the industrial equipment fault rate is obtained synchronously when the system end user reads the calculated industrial equipment fault rate in the system, and the higher the accurate trend expression value is based on the accurate trend expression value, the higher the reliability of the industrial equipment fault rate estimation result is.
Furthermore, the uploading module is electrically connected with the screening module and the configuration module through a medium, the configuration module is electrically connected with the receiving module through a medium, the receiving module is electrically connected with the prediction module and the storage module through a medium, the storage module is electrically connected with the application module through a medium, the application module is electrically connected with the feedback module through a medium, and the storage module and the feedback module are connected with the cloud database through a wireless network.
In a second aspect, a method for acquiring networking equipment data based on industrial internet includes the following steps:
Step 1: uploading historical daily operation data and fault data of industrial equipment;
Step 11: a data screening stage and a configuration stage of operation data and fault data;
Step 12: a setting stage of data screening logic;
Step 2: receiving mutually configured industrial equipment operation data and fault data, acquiring parameters from the mutually configured industrial equipment operation data and fault data, predicting the next acquisition period of the industrial equipment operation data and fault data based on the acquired parameters, and acquiring the industrial equipment fault rate at the stage of the predicted acquisition period data;
step 21: a setting stage of the prediction acquisition period calculating logic and the failure rate calculating logic;
step 3: a predicted acquisition cycle application phase;
Step 31: analyzing the accurate trend of the industrial equipment failure rate prediction result;
Step 4: an industrial equipment operation data and fault data storage stage and a feedback stage which are acquired in a period are acquired;
and step 4 is executed by jumping to the step 1 when the collected industrial equipment operation data and fault data are fed back, and uploading operation is executed by feeding back the data in the feedback stage.
Compared with the prior art, the technical proposal provided by the invention has the following advantages that
The beneficial effects are that:
1. The invention provides a networking equipment data acquisition system based on an industrial Internet, which further analyzes historical operation data of industrial equipment in the operation process to realize the self-adaptive design of the operation data acquisition period of the industrial equipment, so as to avoid continuous operation data acquisition in the operation process of the industrial equipment, effectively reduce the operation load of a monitoring management background of the industrial equipment through data acquisition and reduce the adaptation of background calculation resources as much as possible, thereby further improving the data acquisition capacity of the background of monitoring management of the industrial equipment through data acquisition and facilitating the implementation of data acquisition monitoring management on a plurality of industrial equipment.
2. In the running process of the system, the system running processing data can be simplified in a screening way for the uploaded historical running data of the industrial equipment, so that the running speed of the system is improved, the running of the system is more stable, and the output result of the system is more accurate and effective.
3. The system can predict the failure rate of the industrial equipment while carrying out data acquisition cycle design configuration on the industrial equipment, and further analyzes the accurate trend of the failure rate prediction result on the basis of the failure rate prediction of the industrial equipment, so that auxiliary reference of a system end user is provided by the accurate trend analysis result, and the failure rate obtained by operation prediction in the system can be safely applied.
4. The invention provides a networking equipment data acquisition method based on an industrial Internet, which can further maintain the stability of system operation by executing steps in the method, and can further provide finer operation logic of the system in the executing process of the steps of the method, so as to ensure the technical scheme consisting of the system and the method, and the generated technical effect is more stable in the concrete implementation stage.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a schematic diagram of a networked device data acquisition system based on the industrial Internet;
FIG. 2 is a flow diagram of a method for networked device data collection based on the industrial Internet;
FIG. 3 is a schematic diagram of the system operation logic in the present invention;
fig. 4 is a diagram illustrating an example of the technical effect of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, 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. It will be apparent that the described embodiments are some, but not all, embodiments of the 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.
The invention is further described below with reference to examples.
Example 1:
The networking equipment data acquisition system based on the industrial Internet of the embodiment is shown in fig. 1, and comprises a monitoring layer, an analysis layer and an acquisition layer;
the method comprises the steps that operation data and fault data of industrial equipment are uploaded through a monitoring layer, data screening and configuration of the operation data and the fault data are completed in the monitoring layer, an analysis layer synchronously receives the operation data and the fault data which are completed in configuration, the industrial equipment fault rate in a data acquisition period and an acquisition period acquisition stage of the industrial equipment is predicted based on the industrial equipment operation data and the fault data which are mutually configured, the acquisition layer receives the industrial equipment data acquisition period predicted by the analysis layer, the industrial equipment operation data and the fault data are acquired based on the data acquisition period, and the acquired industrial equipment operation data and the fault data are synchronously fed back to the monitoring layer;
The analysis layer comprises a receiving module, a prediction module and a storage module, wherein the receiving module is used for receiving the industrial equipment operation data and the fault data which are configured in the acquisition layer, the prediction module is used for reading the industrial equipment operation data and the fault data which are received by the receiving module, predicting the next data acquisition period of the industrial equipment by applying the industrial equipment operation data and the fault data, and acquiring the industrial equipment fault rate in the period, and the storage module is used for receiving the industrial equipment fault rate in the acquisition period which is predicted in the prediction module and storing the industrial equipment fault rate in the acquisition period which is predicted;
The prediction module predicts the next data acquisition period of the industrial equipment based on the operation data and the fault data of the industrial equipment as follows:
Wherein: t is the acquisition period; t 0 is the acquisition cycle base; p last is the operating power of the industrial equipment in the operating data of the timestamp prefix bit; p next is the industrial equipment operating power in the operation data set after the time stamp; r last is the output frequency of the finished product in the operation data of the timestamp front set; r next is the output frequency of the finished product in the operation data set after the time stamp; gamma is the failure rate of industrial equipment in the acquisition period acquisition stage; k is the yield of the output finished products of the current industrial equipment; q is a collection of stations on the industrial equipment; omega c is the weight of the station on the c-th industrial equipment;
When the receiving module operates and receives the configured industrial equipment operation data and fault data in the acquisition layer, the configured industrial equipment operation data and fault data are received in two groups, the weight is subjected to value compliance, the higher the upper station of the industrial equipment is close to the front position on the industrial equipment, the larger the weight value is, the lower the upper station of the industrial equipment is close to the rear position on the industrial equipment, and the lower the weight value is set logic;
The monitoring layer comprises an uploading module, a screening module and a configuration module, wherein the uploading module is used for uploading operation data and fault data of the industrial equipment, the screening module is used for traversing and reading the operation data and the fault data of the industrial equipment uploaded by the uploading module, screening logic is set, the operation data and the fault data of the industrial equipment uploaded by the uploading module are screened by the screening logic, the configuration module is used for receiving the operation data and the fault data of the residual industrial equipment after being processed by the screening module, and the mutual configuration of the operation data and the fault data of the industrial equipment is carried out based on a timestamp generated by the operation data and the fault data of the industrial equipment;
Wherein the operational data of the industrial device comprises: operating power, output product frequency, operating duration, fault data of the industrial equipment includes: outputting the yield of finished products and fault source stations, continuously operating the monitoring layer twice when the system is operated for the first time, uploading operation data and fault quantity of industrial equipment twice, further monitoring the operation state of the acquisition layer after the monitoring layer is operated for two times, and executing third and subsequent industrial equipment operation data and fault data uploading operation by the monitoring layer after the monitoring layer monitors the operation of the acquisition layer;
the industrial equipment fault rate gamma in the acquisition period acquisition stage is calculated by the following formula:
wherein: h is the number of days of operation of the industrial equipment; The average value of the running time of the industrial equipment up to day 1; g 1 is the number of failures by day 1 of the operation of the industrial equipment; f life cycle of industrial equipment;
Wherein, In/>Are known;
The acquisition layer comprises an application module, a feedback module and a cloud database, wherein the application module is used for receiving the next data acquisition period of the industrial equipment, which is predicted by the operation of the prediction module in the analysis layer, acquiring the industrial equipment operation data by applying the received acquisition period, the feedback module is used for acquiring the industrial equipment operation data acquired by the application acquisition period in the application module, feeding the industrial equipment operation data back to the uploading module in the monitoring layer, and the cloud database is used for receiving the industrial equipment operation data fed back to the uploading module in the monitoring layer by the feedback module and the industrial equipment fault rate prediction result in the acquisition period acquisition stage stored in the storage module;
The cloud database stores the industrial equipment operation data and the industrial equipment failure rate prediction result after receiving the industrial equipment operation data and the industrial equipment failure rate prediction result, and further carries out accurate trend analysis on the industrial equipment failure rate prediction result after storing the industrial equipment operation data and the industrial equipment failure rate prediction result;
The uploading module is electrically connected with the screening module and the configuration module through a medium, the configuration module is electrically connected with the receiving module through the medium, the receiving module is electrically connected with the prediction module and the storage module through the medium, the storage module is electrically connected with the application module through the medium, the application module is electrically connected with the feedback module through the medium, and the storage module and the feedback module are connected with the cloud database through a wireless network.
In this embodiment, the uploading module operates the operation data and fault data of the uploading industrial equipment, the screening module traverses and reads the operation data and fault data of the industrial equipment uploaded by the uploading module in real time, sets screening logic, screens the operation data and fault data of the industrial equipment uploaded by the uploading module by using the screening logic, the configuration module synchronously receives the operation data and fault data of the residual industrial equipment after being processed by the screening module, generates a time stamp based on the operation data and fault data of the industrial equipment to mutually configure the operation data and fault data of the industrial equipment, the receiving module post-operates and receives the operation data and fault data of the industrial equipment which are configured in the acquisition layer, the prediction module reads the operation data and fault data of the industrial equipment received by the receiving module, predicts the next data acquisition period of the industrial equipment by applying the operation data and fault data of the industrial equipment, and the fault rate of the industrial equipment in the acquisition period acquisition stage, the storage module further operates and receives the fault rate of the industrial equipment in the acquisition period, stores the predicted fault rate of the industrial equipment in the acquisition period acquisition stage, finally receives the next data period of the industrial equipment predicted by the operation of the prediction module in the application module, feeds back the operation data of the industrial equipment in the application module to the operation layer, and the operation data is fed back to the operation data in the acquisition module in the application layer, and the industrial equipment fault rate prediction result in the acquisition period acquisition stage stored in the storage module;
The necessary operation logic is provided for the operation of the acquisition layer in the system through the industrial equipment data acquisition period prediction formula and the industrial equipment fault rate prediction formula, and the system is further enabled to stably operate to bring monitoring management based on continuous data acquisition to the industrial equipment;
Referring to fig. 4, the system operation logic is substituted into an application scene, and each industrial device in the industrial device group is configured with different data acquisition periods through analysis and processing of the system, so that the system can be applied to serve more industrial devices at the same time, and the data acquisition effect is stable, effective and reliable.
Example 2:
on the aspect of implementation, on the basis of embodiment 1, this embodiment further specifically describes, with reference to fig. 1, a networked device data acquisition system based on the industrial internet in embodiment 1:
The screening logic set in the screening module is expressed as:
Wherein: dR (a, b) is the difference rate of data a and data b; n a is a feature matrix of data a; n b is a feature matrix of data b; the characteristic vector is the characteristic vector of the 1 st group of data content in the characteristic matrix of the data a; /(I) The characteristic vector of the 1 st group of data content in the characteristic matrix of the data b; dx a-b is the Euclidean distance between the feature matrix of data a and the feature matrix of data b;
The characteristic matrix of the data consists of characteristic vectors of various data contents in the data, screening logic set in a screening module is applied to operation data and fault data of industrial equipment, after the difference rate dR (a, b) of the data a and the data b is obtained, the difference rate dR (a, b) is more than or equal to 25 percent or dR (a, b) is less than 25 percent, when dR (a, b) is less than 25 percent, one of the data a and the data b is deleted, when dR (a, b) is more than or equal to 25 percent, the data a and the data b are reserved, and the difference rate of the one data and other data is obtained, and the screening logic set in the screening module is applied after the detection layer is continuously operated for two times;
the Euclidean distance between the data feature matrices is calculated by the following formula:
The Euclidean distance between the data feature matrixes applied in the screening logic set in the screening module is obtained based on the difference rate, and the target is obtained in an alternating and synchronous mode and applied in an alternating mode.
Through the formula calculation, necessary operation logic support is provided for the operation of the screening module, so that the screening module can stably screen the industrial equipment operation data and fault data uploaded by the uploading module.
As shown in fig. 1, in the operation stage of the configuration module, the operation data and fault data of the industrial equipment remaining after the operation and screening of the screening module are received, the generation time stamps of the received operation data and fault data of the industrial equipment are further read, each fault data is used as a configuration target, and the operation data of the industrial equipment and the configuration target before the generation time stamps of the fault data corresponding to the configuration target are mutually configured.
Through the arrangement, the specified configuration logic is provided for the operation data and fault data of the industrial equipment.
As shown in fig. 1, the accurate trend analysis logic of the industrial equipment failure rate prediction result is expressed as:
wherein: τ is an accurate trend representation value of the industrial equipment failure rate prediction result; l is a set of industrial equipment failure rate prediction results; gamma 1 is the result of the 1 st industrial equipment failure rate prediction; is a correction factor;
wherein the correction factor Is obeyed by the following values: under the condition that the correction factor corresponds to the product target gamma, industrial equipment does not fail, and the correction factor/>The value is 1, the industrial equipment fails, and the larger the corresponding gamma value is, the correction factor/>The larger the value, the more the correction factor/>The smaller the value is, the more accurate trend expression value corresponding to the industrial equipment fault rate is obtained synchronously when the system end user reads the calculated industrial equipment fault rate in the system, and the higher the accurate trend expression value is based on the accurate trend expression value, the higher the reliability of the industrial equipment fault rate estimation result is.
Through the arrangement, the accurate trend of the industrial equipment failure rate prediction result is calculated, so that the accurate trend calculation result is used as a reference, and the industrial equipment failure rate predicted in the application system can be more safely and stably obtained by a system end user.
Example 3:
on the aspect of implementation, on the basis of embodiment 1, this embodiment further specifically describes, with reference to fig. 2, a networked device data acquisition system based on the industrial internet in embodiment 1:
The networking equipment data acquisition method based on the industrial Internet comprises the following steps:
Step 1: uploading historical daily operation data and fault data of industrial equipment;
Step 11: a data screening stage and a configuration stage of operation data and fault data;
Step 12: a setting stage of data screening logic;
Step 2: receiving mutually configured industrial equipment operation data and fault data, acquiring parameters from the mutually configured industrial equipment operation data and fault data, predicting the next acquisition period of the industrial equipment operation data and fault data based on the acquired parameters, and acquiring the industrial equipment fault rate at the stage of the predicted acquisition period data;
step 21: a setting stage of the prediction acquisition period calculating logic and the failure rate calculating logic;
step 3: a predicted acquisition cycle application phase;
Step 31: analyzing the accurate trend of the industrial equipment failure rate prediction result;
Step 4: an industrial equipment operation data and fault data storage stage and a feedback stage which are acquired in a period are acquired;
And step 4, when the feedback stage of the collected operation data and fault data of the industrial equipment is performed, the step1 is skipped to perform uploading operation by feeding back the data in the feedback stage.
In summary, in the above embodiment, the system further analyzes the uploading of the historical operation data of the industrial equipment in the operation process to realize the adaptive design of the operation data acquisition period of the industrial equipment, so as to avoid continuous operation data acquisition in the operation process of the industrial equipment, effectively reduce the operation burden of monitoring and managing the industrial equipment by data acquisition, and reduce the adaptation of background computing resources as much as possible, thereby further improving the data acquisition capacity of the background monitoring and managing the industrial equipment by data acquisition, and facilitating the implementation of data acquisition, monitoring and management on a plurality of industrial equipment; meanwhile, in the running process of the system, the uploaded historical running data of the industrial equipment can be further reduced in a screening mode, so that the running speed of the system is improved, the running of the system is more stable, and the output result of the system is more accurate and effective; in addition, the system can predict the failure rate of the industrial equipment while carrying out data acquisition cycle design configuration on the industrial equipment, and further analyzes the accurate trend of the failure rate prediction result on the basis of the failure rate prediction of the industrial equipment, so that auxiliary reference of a system end user is provided by the accurate trend analysis result, and the failure rate obtained by operation prediction in the system can be safely applied; the method provided in the embodiment can further maintain the stability of the system operation, and in the step execution process of the method, finer operation logic of the system can be further provided, so that the technical scheme consisting of the system and the method is ensured, and the generated technical effect is more stable in the specific implementation stage.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (3)
1. The networking equipment data acquisition system based on the industrial Internet is characterized by comprising a monitoring layer, an analysis layer and an acquisition layer;
the method comprises the steps that operation data and fault data of industrial equipment are uploaded through a monitoring layer, data screening and configuration of the operation data and the fault data are completed in the monitoring layer, an analysis layer synchronously receives the operation data and the fault data which are completed in configuration, the industrial equipment fault rate in a data acquisition period and an acquisition period acquisition stage of the industrial equipment is predicted based on the industrial equipment operation data and the fault data which are mutually configured, the acquisition layer receives the industrial equipment data acquisition period predicted by the analysis layer, the industrial equipment operation data and the fault data are acquired based on the data acquisition period, and the acquired industrial equipment operation data and the fault data are synchronously fed back to the monitoring layer;
The analysis layer comprises a receiving module, a prediction module and a storage module, wherein the receiving module is used for receiving the industrial equipment operation data and the fault data which are configured in the acquisition layer, the prediction module is used for reading the industrial equipment operation data and the fault data which are received by the receiving module, predicting the next data acquisition period of the industrial equipment by applying the industrial equipment operation data and the fault data, and acquiring the industrial equipment fault rate in the period, and the storage module is used for receiving the industrial equipment fault rate in the acquisition period which is predicted in the prediction module and storing the industrial equipment fault rate in the acquisition period which is predicted;
The prediction module predicts the next data acquisition period of the industrial equipment based on the operation data and the fault data of the industrial equipment as follows:
Wherein: t is the acquisition period; t 0 is the acquisition cycle base; p last is the operating power of the industrial equipment in the operating data of the timestamp prefix bit; p next is the industrial equipment operating power in the operation data set after the time stamp; r last is the output frequency of the finished product in the operation data of the timestamp front set; r next is the output frequency of the finished product in the operation data set after the time stamp; gamma is the failure rate of industrial equipment in the acquisition period acquisition stage; k is the yield of the output finished products of the current industrial equipment; q is a collection of stations on the industrial equipment; omega c is the weight of the station on the c-th industrial equipment;
When the receiving module operates to receive the configured industrial equipment operation data and fault data in the acquisition layer, the configured industrial equipment operation data and fault data are received in two groups, the weight is subjected to value compliance, the weight value is larger when the upper station of the industrial equipment is close to the upper front position of the industrial equipment, and the weight value is smaller when the upper station of the industrial equipment is close to the upper rear position of the industrial equipment;
The monitoring layer comprises an uploading module, a screening module and a configuration module, wherein the uploading module is used for uploading operation data and fault data of industrial equipment, the screening module is used for traversing and reading the industrial equipment operation data and the fault data uploaded by the uploading module, screening logic is set, the industrial equipment operation data and the fault data uploaded by the uploading module are screened by the screening logic, the configuration module is used for receiving the residual industrial equipment operation data and the residual fault data which are processed by the screening module, and the industrial equipment operation data and the fault data are mutually configured based on a timestamp generated by the industrial equipment operation data and the fault data;
Wherein the operational data of the industrial device comprises: operating power, output product frequency, operating duration, fault data of the industrial equipment includes: outputting the yield of finished products and fault source stations, continuously operating the monitoring layer twice when the system is operated for the first time, uploading operation data and fault quantity of industrial equipment twice, further monitoring the operation state of the acquisition layer after the monitoring layer is operated for two times, and executing third and subsequent industrial equipment operation data and fault data uploading operation by the monitoring layer after the monitoring layer monitors the operation of the acquisition layer;
The screening logic set in the screening module is expressed as:
Wherein: dR (a, b) is the difference rate of data a and data b; n a is a feature matrix of data a; n b is a feature matrix of data b; the characteristic vector is the characteristic vector of the 1 st group of data content in the characteristic matrix of the data a; /(I) The characteristic vector of the 1 st group of data content in the characteristic matrix of the data b; dx a-b is the Euclidean distance between the feature matrix of data a and the feature matrix of data b;
The characteristic matrix of the data consists of characteristic vectors of various data contents in the data, screening logic set in a screening module is applied to operation data and fault data of industrial equipment, after the difference rate dR (a, b) of the data a and the data b is obtained, the difference rate dR (a, b) is more than or equal to 25 percent or dR (a, b) is less than 25 percent, when dR (a, b) is less than 25 percent, one of the data a and the data b is deleted, when dR (a, b) is more than or equal to 25 percent, the data a and the data b are reserved, and the difference rate of the one data and other data is obtained, and the screening logic set in the screening module is applied after the detection layer is continuously operated for two times;
The Euclidean distance between the data feature matrices is calculated by the following formula:
The Euclidean distance between the data feature matrixes applied in the screening logic set in the screening module is obtained based on the difference rate, and the target is obtained in an alternating and synchronous way and applied in an alternating way;
the configuration module operation stage is used for receiving the residual industrial equipment operation data and fault data after the screening module operation screening, further reading the generation time stamps of the received industrial equipment operation data and fault data, and mutually configuring the industrial equipment operation data and the configuration targets before the generation time stamps of the fault data corresponding to the configuration targets by taking each fault data as the configuration targets;
the industrial equipment fault rate gamma in the acquisition period acquisition stage is calculated by the following formula:
wherein: h is the number of days of operation of the industrial equipment; The average value of the running time of the industrial equipment up to day 1; g 1 is the number of failures by day 1 of the operation of the industrial equipment; f life cycle of industrial equipment;
Wherein, In/>Are known;
the acquisition layer comprises an application module, a feedback module and a cloud database, wherein the application module is used for receiving the next data acquisition period of the industrial equipment, which is predicted by the operation of the prediction module in the analysis layer, acquiring the industrial equipment operation data by the application of the received acquisition period, the feedback module is used for acquiring the industrial equipment operation data acquired by the application acquisition period in the application module, feeding the industrial equipment operation data back to the uploading module in the monitoring layer, and the cloud database is used for receiving the industrial equipment operation data fed back to the uploading module in the monitoring layer by the feedback module and the industrial equipment fault rate prediction result in the acquisition period acquisition stage stored in the storage module;
The cloud database stores the industrial equipment operation data and the industrial equipment failure rate prediction result after receiving the industrial equipment operation data and the industrial equipment failure rate prediction result, and further carries out accurate trend analysis on the industrial equipment failure rate prediction result after storing the industrial equipment operation data and the industrial equipment failure rate prediction result;
The accurate trend analysis logic of the industrial equipment failure rate prediction result is expressed as follows:
wherein: τ is an accurate trend representation value of the industrial equipment failure rate prediction result; l is a set of industrial equipment failure rate prediction results; gamma 1 is the result of the 1 st industrial equipment failure rate prediction; is a correction factor;
Wherein the correction factor Is obeyed by the following values: under the condition that the correction factor corresponds to the product target gamma, industrial equipment does not fail, and the correction factor/>The value is 1, the industrial equipment fails, and the larger the corresponding gamma value is, the correction factor/>The larger the value, the more the correction factor/>The smaller the value is, the more accurate trend expression value corresponding to the industrial equipment fault rate is obtained synchronously when the system end user reads the calculated industrial equipment fault rate in the system, and the higher the accurate trend expression value is based on the accurate trend expression value, the higher the reliability of the industrial equipment fault rate estimation result is.
2. The internet-based networking device data acquisition system according to claim 1, wherein the uploading module is electrically connected with the screening module and the configuration module through a medium, the configuration module is electrically connected with the receiving module through a medium, the receiving module is electrically connected with the predicting module and the storing module through a medium, the storing module is electrically connected with the application module through a medium, the application module is electrically connected with the feedback module through a medium, and the storing module and the feedback module are connected with the cloud database through a wireless network.
3. A method for acquiring networking equipment data based on industrial internet, which is an implementation method for the networking equipment data acquisition system based on industrial internet as claimed in claim 2, and is characterized by comprising the following steps:
Step 1: uploading historical daily operation data and fault data of industrial equipment;
Step 11: a data screening stage and a configuration stage of operation data and fault data;
Step 12: a setting stage of data screening logic;
Step 2: receiving mutually configured industrial equipment operation data and fault data, acquiring parameters from the mutually configured industrial equipment operation data and fault data, predicting the next acquisition period of the industrial equipment operation data and fault data based on the acquired parameters, and acquiring the industrial equipment fault rate at the stage of the predicted acquisition period data;
step 21: a setting stage of the prediction acquisition period calculating logic and the failure rate calculating logic;
step 3: a predicted acquisition cycle application phase;
Step 31: analyzing the accurate trend of the industrial equipment failure rate prediction result;
Step 4: an industrial equipment operation data and fault data storage stage and a feedback stage which are acquired in a period are acquired;
and step 4 is executed by jumping to the step 1 when the collected industrial equipment operation data and fault data are fed back, and uploading operation is executed by feeding back the data in the feedback stage.
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